Practices for Collecting, Managing, and Using Light Detection and Ranging Data (2025)

Chapter: Appendix B: Detailed Questionnaire Results

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Page 134
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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APPENDIX B

Detailed Questionnaire Results

Number of Responses/Response Rate:

All 50 state and District of Columbia DOTs responded, representing a 100% response rate (51/51).

Demographic Information:

The hexagon map shows the distribution of survey respondents by title represented with four fill patterns. A diagonal crosshatch pattern marks states in which the respondent was an engineer—Kansas, Minnesota, Nebraska, Missouri, Mississippi, and Utah—accounting for 11.8 percent, with N equal to 6. A diagonal line pattern marks states in which the respondent was a manager—Alabama, Arizona, Florida, Georgia, Indiana, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Montana, New Jersey, New York, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Vermont, Virginia, Washington, Montana, New Mexico, Iowa, Indiana, and the District of Columbia—totaling 58.8 percent, with N equal to 30. A crosshatch pattern marks states in which the respondent was a surveyor—California, Connecticut, Hawaii, Idaho, Nevada, North Carolina, Oregon, South Dakota, West Virginia, Illinois, and Wyoming—totaling 21.6 percent, with N equal to 11. A horizontal line pattern marks states in which the respondent was a technician—Alaska, Delaware, New Hampshire, and Wisconsin, totaling 7.8 percent, with N equal to 4. The legend defines each pattern with its corresponding role type, percentage, and number of respondents. The hexagon map shows the distribution of survey respondents by their division within the United States state departments of transportation using 11 fill patterns. A pattern of yellow diagonal lines indicates Asset Management for Nebraska, accounting for 2.0 percent, with N equal to 1. A pattern of horizontal lines indicates Aviation for Alaska and New Hampshire, totaling 3.9 percent, with N equal to 2. A pattern of stars overlaid with diagonal lines indicates Construction for Utah, also 2.0 percent, with N equal to 1. A circle pattern designates Design for North Dakota, Missouri, and Kansas, totaling 5.9 percent, with N equal to 3. A dotted fill pattern designates Engineering for Massachusetts and Mississippi, totaling 3.9 percent, with N equal to 2. A diagonal crosshatch pattern indicates I T or Data for Florida, Georgia, the District of Columbia, Kentucky, West Virginia, Colorado, and Iowa, totaling 13.7 percent, with N equal to 7. A star pattern designates Maintenance and Operations for Montana and Tennessee, totaling 3.9 percent, with N equal to 2. A crosshatch pattern designates Planning for Arizona, South Dakota, and Washington, totaling 5.9 percent, with N equal to 3. A pattern of green diagonal lines designates Survey for Alabama, California, Connecticut, Delaware, Hawaii, Idaho, Illinois, Indiana, Texas, Louisiana, Maine, Vermont, Maryland, Michigan, Minnesota, Nevada, New Mexico, New York, North Carolina, Ohio, Oklahoma, Arkansas, Oregon, Pennsylvania, Rhode Island, South Carolina, Virginia, Wisconsin, and Wyoming, totaling 56.8 percent, with N equal to 29. A pattern of circles overlaid by diagonal lines indicates Traffic for New Jersey, totaling 2.0 percent, with N equal to 1. All fill patterns are defined in the legend along with their respective division types, percentages, and sample sizes.

Page 135
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Use of lidar data within your DOT:

  1. When did your DOT start to utilize lidar data?

The hexagon map shows when the United States state departments of transportation began using Lidar, using four distinct fill patterns to represent timeframes. A diagonal line pattern marks states that began using Lidar over 10 years ago—Alabama, Alaska, Arkansas, California, the District of Columbia, Florida, Idaho, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Nevada, New York, North Carolina, Ohio, Oregon, Pennsylvania, Tennessee, Texas, Utah, West Virginia, Washington, and Wisconsin—accounting for 49.1 percent, with N equal to 25. A horizontal line pattern marks states that began using Lidar within the last 10 years—Colorado, Hawaii, Illinois, Louisiana, North Dakota, Oklahoma, Maine, Maryland, Mississippi, Massachusetts, Rhode Island, South Carolina, and Wyoming—accounting for 25.5 percent, with N equal to 13. A crosshatch pattern marks states that adopted Lidar within the last 5 years—Connecticut, Indiana, Montana, New Hampshire, New Jersey, New Mexico, South Dakota, Vermont, and Virginia—totaling 17.6 percent, with N equal to 9. A blank fill marks states that indicated no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend provides usage categories, corresponding pattern styles, percentages, and the sample size N for each group.

1A. If your DOT is not using lidar data, please indicate the main reasons from the list below. Note for all applicable tables: hyphens indicate no state response.

Reason Arizona Delaware Georgia Nebraska
Lack of trust in lidar data quality - - - -
Software compatibility - - - -
Difficulties in obtaining similar results to traditional workflows - - - -
Limited experience, training, and capabilities X - - -
Insufficient IT infrastructure (data storage, network latency, software tools, etc.) X - - -
Other methods provide higher ROI X - - -
Effort required to extract information from lidar data X - - -
Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements. - - - -
Other (Please specify) We pursued it years ago but at the time it was not trustworthy. None Did not specify reasons. Unsure of which Assets we wish to collect with Lidar and how to manage them once collected.
Page 136
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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  1. Which of the following best describes the use of lidar within your DOT? (Single Response)

A hexagon map categorizes the levels of Lidar data usage by each United States state department of transportation, using six distinct fill patterns with state abbreviations inside each hexagon. Diagonal lines represent full integration into workflows across several departments for various applications and include Maine, New Jersey, the District of Columbia, Maryland, Oklahoma, Arkansas, North Carolina, Alabama, and Kentucky, totaling 17.6 percent, with sample size N equal to 9. A diagonal crosshatch pattern appears in Vermont, indicating rare Lidar usage, making up 2.0 percent, with N equal to 1. A crosshatch pattern indicates scattered usage without centralized oversight and includes Hawaii, Montana, Idaho, Minnesota, South Dakota, Texas, Louisiana, Michigan, Kansas, Virginia, New Hampshire, Massachusetts, Rhode Island, and Connecticut, making up 27.5 percent, with N equal to 19. Horizontal lines indicate states where some departments fully integrate Lidar while others use it occasionally, and include Alaska, Washington, Oregon, California, Nevada, Utah, Wyoming, North Dakota, Colorado, Wisconsin, Illinois, Indiana, Missouri, Mississippi, Tennessee, West Virginia, New York, Pennsylvania, and Florida, totaling 37.3 percent, with N equal to 14. A dotted pattern representing other states includes New Mexico, Iowa, Ohio, and South Carolina, totaling 7.8 percent, with N equal to 4. Another four states, Arizona, Nebraska, Georgia, and Delaware, have no pattern, which indicates no Lidar usage, also totaling 7.8 percent, with N equal to 4. The legend at the bottom defines each pattern and includes corresponding percentages and sample sizes, with N referring to the number of states in each group.

State DOT Other Response
Iowa We’re more organized then scattered but not quite fully integrated.
New Mexico Only know of Survey and Lands Engineering usage
Ohio Centralized data collection and processing for entire department.
South Carolina Feature extracted data from aerial/mobile lidar is used for design and pavement cross slope analysis, but point cloud is only used by survey department. SCDOT uses consultants for all aerial/mobile mapping.
  1. Please indicate the frequency of usage of different lidar platforms by your DOT regardless of lidar sensor, scanning mechanism (solid-state, flash, etc.), or application (topographic or bathymetric).
Page 137
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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A hexagon map depicts the comparative usage rates of airborne Lidar systems by United States state departments of transportation, with each state labeled and categorized using one of six fill patterns. A hexagon with a horizontal line patterns indicates states that never use airborne Lidar, including Hawaii, Colorado, Arkansas, and Mississippi, accounting for 7.8 percent, with sample size N equal to 4. A crosshatch pattern indicates rare usage limited to research or pilot projects and includes Wyoming, Minnesota, Vermont, New Hampshire, and Florida, totaling 9.8 percent, with N equal to 5. A repeating star-like symbol pattern represents occasional project usage and includes Oregon, Nevada, Idaho, Utah, New Mexico, South Dakota, Kansas, Louisiana, Michigan, Illinois, Indiana, West Virginia, Pennsylvania, Connecticut, Massachusetts, Maine, and Rhode Island, for a total of 33.3 percent and N equal to 17. A dotted grid pattern marks states where airborne Lidar is used routinely and includes Alaska, California, Washington, North Dakota, Oklahoma, Texas, Wisconsin, Missouri, Kentucky, Tennessee, Ohio, Alabama, Virginia, North Carolina, South Carolina, New York, New Jersey, Maryland, and the District of Columbia, along with others, totaling 37.4 percent and N equal to 19. A mesh square fill is used for states that are unsure, including Montana and Iowa, making up 3.9 percent, with N equal to 2. No fill pattern indicates no Lidar usage and includes Arizona, Georgia, Nebraska, and Delaware, totaling 7.8 percent, with N equal to 4. The legend at the bottom assigns each pattern to its respective usage category and shows the associated percentages and sample sizes, with N referring to the number of states in each group. The hexagon map shows comparative helicopter Lidar usage across the United States state departments of transportation using six distinct fill patterns, each corresponding to a usage category. A pattern of horizontal lines represents states that never use helicopter Lidar, including Ohio, Indiana, Pennsylvania, Kansas, Louisiana, Mississippi, Colorado, Hawaii, New Hampshire, New York, North Dakota, Minnesota, South Dakota, New Mexico, Utah, Nevada, Idaho, Oregon, and Wyoming, totaling 37.4 percent, with sample size N equal to 19. An open crosshatch pattern indicates rare usage for research or pilot projects and includes Alaska, Washington, Kentucky, West Virginia, Virginia, North Carolina, Vermont, and Maine, totaling 15.7 percent, with N equal to 8. A repeating star pattern marks states that use Lidar occasionally and includes California, Wisconsin, Oklahoma, Illinois, Florida, Arkansas, Alabama, Tennessee, and Massachusetts, totaling 17.6 percent, with N equal to 9. A dotted fill pattern indicates routine usage and includes Texas, Missouri, South Carolina, and Maryland, totaling 7.8 percent, with N equal to 4. A tight crosshatch pattern represents uncertainty about usage and includes Montana, Iowa, Michigan, the District of Columbia, New Jersey, Connecticut, and Rhode Island, totaling 13.7 percent, with N equal to 7. No fill pattern indicates no Lidar usage and includes Delaware, Arizona, Nebraska, and Georgia, totaling 7.8 percent, with N equal to 4. The legend assigns each fill pattern to its corresponding category, including percentage values and sample sizes. The hexagon map shows comparative terrestrial Lidar system usage by United States state departments of transportation using five fill patterns. A horizontal line pattern marks one state, Oklahoma, that never uses terrestrial Lidar, accounting for 2.0 percent, with a sample size N equal to 1. A star pattern represents states that use Lidar occasionally for projects: Utah, Idaho, New Mexico, South Dakota, North Dakota, Illinois, Michigan, Louisiana, Connecticut, Rhode Island, Vermont, Virginia, South Carolina, Alabama, New Hampshire, and Hawaii. This group totals 31.4 percent, with N equal to 16. A dotted fill pattern is used for states that use Lidar routinely: Alaska, Washington, Oregon, California, Nevada, Wyoming, Texas, Wisconsin, Missouri, Indiana, Ohio, Kentucky, West Virginia, Arkansas, Tennessee, New Jersey, Massachusetts, Kansas, Colorado, Minnesota, Pennsylvania, Maine, New York, North Carolina, Florida, and Maryland. These states make up 51.0 percent, with N equal to 26. A tight crosshatch pattern marks states that are unsure about usage: Montana, Iowa, Mississippi, and the District of Columbia. This group totals 7.8 percent, with N equal to 4. No fill pattern is used for the states with no Lidar usage, Arizona, Georgia, Nebraska, and Delaware, which also total 7.8 percent, with N equal to 4. The legend at the bottom defines each pattern and its corresponding usage category, including all percentages and sample sizes, where N refers to the number of states in each group.

Page 138
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows comparative vehicle-mounted mobile Lidar system usage by United States state departments of transportation using six fill patterns. A horizontal line pattern marks 2 states, Indiana and Hawaii, that never use vehicle-mounted Lidar, accounting for 3.9 percent, with a sample size N equal to 2. An open crosshatch pattern overlaid with diagonal lines marks 2 states, Washington and North Dakota, that use Lidar rarely, for research or pilot projects, also accounting for 3.9 percent, with N equal to 2. A star pattern represents 20 states that use Lidar occasionally for projects: Idaho, Nevada, Wyoming, South Dakota, Iowa, Wisconsin, Illinois, New Mexico, Oklahoma, Louisiana, Arkansas, West Virginia, Pennsylvania, New Jersey, Connecticut, Rhode Island, Vermont, New Hampshire, Massachusetts, and Maryland. This group totals 39.2 percent, with N equal to 20. A dotted pattern shows 22 states that use Lidar routinely: Alaska, Montana, Minnesota, Michigan, New York, Maine, Ohio, Virginia, Kentucky, Missouri, Colorado, Utah, California, Oregon, Kansas, Texas, Alabama, Mississippi, South Carolina, North Carolina, Tennessee, and Florida, making up 43.2 percent, with N equal to 22. A tight crosshatch pattern marks 1 state, the District of Columbia, that is unsure about usage, equal to 2.0 percent, with N equal to 1. No fill pattern is used for 4 states with no Lidar usage: Georgia, Delaware, Nebraska, and Arizona, totaling 7.8 percent, with N equal to 4. The legend at the bottom defines each fill pattern with its associated usage category, percentage, and sample size, where N refers to the number of states in each category. The hexagon map shows comparative usage of U A S-mounted mobile Lidar systems by United States state departments of transportation using six fill patterns. A horizontal line pattern marks states that never use U A S-mounted Lidar: Hawaii, New Mexico, Ohio, New York, and Minnesota. This group totals 9.8 percent, with a sample size N equal to 5. An open crosshatch pattern represents states that use it rarely for research or pilot projects: Idaho, Wyoming, Texas, Wisconsin, Iowa, Illinois, Pennsylvania, Connecticut, Florida, Alabama, West Virginia, and Vermont. This group totals 23.5 percent, with N equal to 12. A star pattern marks states using Lidar occasionally for projects: Washington, Nevada, Utah, North Dakota, South Dakota, Michigan, Indiana, Virginia, South Carolina, the District of Columbia, New Jersey, Maryland, Massachusetts, Rhode Island, Missouri, Mississippi, Oklahoma, and Louisiana. This group totals 35.3 percent, with N equal to 18. A dotted pattern indicates routine usage and includes Alaska, Oregon, California, Colorado, Kansas, Arkansas, Kentucky, Tennessee, North Carolina, New Hampshire, and Maine. This group totals 21.6 percent, with N equal to 11. A tight crosshatch pattern marks the single state that is unsure about usage, Montana, equal to 2.0 percent, with N equal to 1. No fill pattern is used for states that reported no Lidar usage: Arizona, Nebraska, Georgia, and Delaware. This group totals 7.8 percent, with N equal to 4. The legend at the bottom defines each pattern with its associated usage type, percentage, and sample size, where N refers to the number of states in each group. The hexagon map shows comparative pocket Lidar system usage by United States state departments of transportation using five fill patterns. A horizontal line pattern marks states that never use pocket Lidar: Hawaii, Idaho, Wyoming, New Mexico, Texas, Oklahoma, Colorado, South Dakota, Minnesota, Wisconsin, Illinois, Missouri, Arkansas, Louisiana, Massachusetts, Tennessee, Alabama, West Virginia, Ohio, Michigan, New York, New Jersey, Maryland, Mississippi, Connecticut, Rhode Island, Maine, and Florida. This group accounts for 54.9 percent, with a sample size N equal to 28. An open crosshatch pattern marks states that use pocket Lidar rarely for research or pilot projects: Oregon, California, Nevada, Utah, North Dakota, Kansas, Iowa, Pennsylvania, Kentucky, and the District of Columbia. This group totals 19.6 percent, with N equal to 10. A dotted fill pattern marks 1 state, Alaska, that uses pocket Lidar routinely, accounting for 2.0 percent, with N equal to 1. A tight crosshatch pattern designates states that are not sure about usage: Washington, Montana, New Hampshire, Vermont, Indiana, North Carolina, South Carolina, and Virginia. This group accounts for 15.7 percent, with N equal to 8. No fill pattern is used for states that reported no Lidar usage: Arizona, Georgia, Nebraska, and Delaware. This group totals 7.8 percent, with N equal to 4. The legend at the bottom defines each pattern with its usage type, percentage, and sample size, where N refers to the number of states in each category.

Page 139
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows comparative usage rates of other Lidar systems by United States state departments of transportation using four fill patterns. A horizontal line pattern marks states that never use other Lidar systems—New Mexico and Rhode Island—accounting for 3.9 percent, with N equal to 2. A open crosshatch pattern overlaid with diagonal lines designates Idaho, the single state that uses other Lidar systems rarely, for research or pilot projects, accounting for 2.0 percent, with N equal to 1. A tight grid pattern marks states that are not sure about other Lidar system usage—Alabama, Alaska, Arkansas, California, Colorado, Connecticut, the District of Columbia, Florida, Hawaii, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nevada, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming—accounting for 86.3 percent, with N equal to 44. A blank fill marks states that indicated no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern with usage category, percentage, and sample size.

State DOT Other Text
Hawaii Looking into Mobile Lidar.
Idaho Fixed LiDAR in Salt Sheds to determine inventory.
Ohio It should be noted that this is what we own - we do not specify data collection methods to consultants. Our specs are performance-based.
  1. Approximately what percentage of the following types of lidar data used by your DOT is collected by external firms? [Editor Note: 4A is implied.]

The hexagon map shows the percentage of airborne Lidar data collection handled by external firms across the United States state departments of transportation using eight fill patterns. A diagonal line pattern marks states that report no airborne Lidar usage—Arkansas, Colorado, Hawaii, Iowa, Montana, and Mississippi—totaling 11.8 percent, with N equal to 6. A tight vertical line pattern marks states that report 0 percent external collection—North Dakota, Ohio, and Vermont—totaling 5.9 percent, with N equal to 3. A star pattern marks Louisiana, the single state reporting 30 percent external collection. A dotted fill marks Missouri, the single state reporting 40 percent. A horizontal line pattern marks, Utah, the single state reporting 90 percent. A vertical stripe pattern marks states that report 100 percent of airborne Lidar data is collected by external firms, accounting for 66.5 percent, with N equal to 34. These states are Alabama, Alaska, California, Connecticut, the District of Columbia, Idaho, Illinois, Indiana, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, New Hampshire, New Jersey, New Mexico, New York, Nevada, North Carolina, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Texas, Tennessee, Virginia, Washington, West Virginia, Wisconsin, and Wyoming. A blank fill marks states that indicated no Lidar usage: Arizona, Delaware, Georgia, and Nebraska, totaling 7.8 percent, with N equal to 4. The legend defines each fill pattern along with usage percentage, description, and sample size.

Page 140
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the percentage of helicopter Lidar data collection handled by external firms across the United States state departments of transportation, using six fill patterns. A pattern of open diagonal lines marks states that report no helicopter Lidar usage, accounting for 51.0 percent, with N equal to 26. These states are Colorado, Connecticut, the District of Columbia, Hawaii, Idaho, Indiana, Kansas, Louisiana, Michigan, Minnesota, Mississippi, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Dakota, Ohio, Oregon, Pennsylvania, Rhode Island, Iowa, South Dakota, Utah, and Wyoming. A pattern of tight vertical lines marks states that report 0 percent external collection—Kentucky and Vermont—totaling 3.9 percent, with N equal to 2. A pattern of tight diagonal lines marks Missouri, the single state reporting 10 percent external collection. A star pattern marks Florida, the single state reporting 30 percent external collection. A pattern of vertical lines marks states that report 100 percent of helicopter Lidar data handled by external firms, accounting for 33.3 percent, with N equal to 17. These states are Alabama, Alaska, Arkansas, California, Illinois, Maine, Maryland, Massachusetts, North Carolina, Oklahoma, South Carolina, Texas, Tennessee, Virginia, West Virginia, Washington, and Wisconsin. A blank fill marks states that indicated no usage of Lidar data—Arizona, Delaware, Georgia, and Nebraska—totaling 7.8 percent, with N equal to 4. The legend defines each fill pattern along with the corresponding usage percentage, description, and sample size. The hexagon map shows the percentage of terrestrial tripod Lidar data collection handled by external firms for asset management by United States state departments of transportation, using 14 fill patterns. A pattern of wide-spaced green diagonal lines marks the District of Columbia, which reported no terrestrial tripod Lidar usage, accounting for 2.0 percent. A pattern of closely spaced vertical lines marks states that reported 0 percent external handling—Arkansas, Hawaii, Massachusetts, New Hampshire, Nevada, Wyoming, Ohio, Washington, and West Virginia—totaling 17.7 percent, with sample size N equal to 9. A pattern of closely spaced pink diagonal lines marks states that reported 10 percent handling—California, Minnesota, North Dakota, Oregon, and Pennsylvania—accounting for 9.8 percent, with sample size N equal to 5. A pattern of closely spaced blue diagonal lines marks states that reported 20 percent handling—Missouri, Colorado, and New York—accounting for 5.9 percent, with sample size N equal to 3. A star pattern marks states that reported 30 percent handling—Wisconsin and Indiana—accounting for 3.9 percent, with sample size N equal to 2. A dotted pattern marks Connecticut, the single state that reported 40 percent handling, accounting for 2 percent. A pattern of red circles marks states that reported 50 percent handling—New Mexico, Kansas, Illinois, Kentucky, Tennessee, New Jersey, and Maine—accounting for 13.7 percent, with sample size N equal to 7. A pattern of yellow circles marks states that reported 60 percent handling—Alabama and Florida—accounting for 3.9 percent, with sample size N equal to 2. A diagonal crosshatch pattern marks states that reported 70 percent handling—Texas and Louisiana—accounting for 3.9 percent, with sample size N equal to 2. A crosshatch pattern marks states that reported 80 percent handling—South Dakota, Michigan, Virginia, North Carolina, and Vermont—accounting for 9.8 percent, with sample size N equal to 5. A pattern of horizontal lines marks South Carolina, the single state that reported 90 percent handling, accounting for 2 percent. A pattern of vertical lines marks states that reported 100 percent handling—Alaska, Idaho, Utah, Maryland, and Rhode Island—accounting for 9.8 percent, with sample size N equal to 5. A closely spaced crosshatch pattern marks states that did not respond to the question—Montana, Iowa, Oklahoma, and Mississippi—accounting for 9.8 percent, with sample size N equal to 5. A blank fill indicates states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—also 7.8 percent, with N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows the percentage of vehicle-mounted Lidar data collection handled by external firms for asset management by United States state departments of transportation, using 12 fill patterns. A pattern of widely spaced diagonal lines marks states that reported no terrestrial tripod Lidar usage—Hawaii, the District of Columbia, and Indiana—accounting for 5.9 percent, with sample size N equal to 3. A tight vertical line pattern marks states that report 0 percent external handling—Montana, Oregon, Ohio, and New Hampshire—accounting for 7.8 percent, with N equal to 4. A narrowly spaced pattern of diagonal lines marks states that reported 10 percent handling—the District of Columbia and Hawaii—totaling 3.9 percent, with N equal to 2. A star pattern marks California, which reported 30 percent handling, accounting for 2.0 percent. A dotted fill pattern marks Missouri, which reported 40 percent, totaling 2.0 percent. A pattern of red circles marks states that reported 50 percent handling—Kentucky and Massachusetts—totaling 3.9 percent, with N equal to 2. A pattern of yellow circles marks Alabama, which reported 60 percent handling, accounting for 2.0 percent. A diagonal crosshatch pattern marks states that reported 70 percent handling—Florida, Idaho, and Louisiana—totaling 5.9 percent, with N equal to 3. A crosshatch pattern marks states that reported 80 percent handling—Arkansas and Pennsylvania—totaling 3.9 percent, with N equal to 2. A horizontal line pattern marks Minnesota, which reported 90 percent handling, accounting for 2.0 percent. A vertical stripe pattern marks states that reported 100 percent external handling, accounting for 52.9 percent, with N equal to 27. These states include Alaska, Washington, Nevada, Utah, Colorado, New Mexico, Texas, Oklahoma, Kansas, South Dakota, Iowa, Illinois, Michigan, Wisconsin, Virginia, West Virginia, Tennessee, North Carolina, South Carolina, Maryland, Connecticut, Rhode Island, New Jersey, New York, Vermont, Wyoming, and Maine. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—totaling 7.8 percent, with N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the percentage of U A S-mounted Lidar data collection handled by external firms for asset management by United States state departments of transportation using 10 fill patterns. A tight pattern of vertical lines marks states that reported 0 percent external handling—Alaska, the District of Columbia, Vermont, New Hampshire, Nevada, Wyoming, and Florida—totaling 13.7 percent, with sample size N equal to 7. A right diagonal stripe pattern marks states that reported 10 percent handling—Washington, North Dakota, Mississippi, Alabama, and North Carolina—accounting for 9.8 percent, with N equal to 5. A left diagonal strip pattern marks states that reported 20 percent handling—California, Oregon, Arkansas, Missouri, and Michigan—also totaling 9.8 percent, with N equal to 5. A star pattern marks states that reported 30 percent handling—Indiana and Louisiana—totaling 3.9 percent, with N equal to 2. A pattern of circles pattern marks states that reported 50 percent handling—Massachusetts, Maryland, Iowa, Illinois, Kentucky, Kansas, and West Virginia—accounting for 13.7 percent, with N equal to 7. A diagonal crosshatch pattern marks Colorado, the single state that reported 70 percent, accounting for 2.0 percent. A horizontal line pattern marks states that reported 90 percent—Pennsylvania, Tennessee, and Utah—accounting for 5.9 percent, with N equal to 3. A vertical stripe pattern marks states that reported 100 percent handling—Texas, Oklahoma, Idaho, Wisconsin, Virginia, South Carolina, New Jersey, Connecticut, Rhode Island, South Dakota, and Maine—accounting for 21.6 percent, with N equal to 11. A tight diagonal crosshatch pattern marks states that did not respond to this question—Hawaii, Montana, New Mexico, New York, Minnesota, and Ohio—totaling 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Delaware, Georgia, Arizona, and Nebraska—accounting for 7.8 percent, with sample size N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows the percentage of pocket Lidar data collection handled by external firms for asset management by United States state departments of transportation, using six fill patterns. A left diagonal line pattern marks states that reported no pocket Lidar usage, accounting for 70.6 percent, with sample size N equal to 36. These states include Hawaii, Maine, Maryland, Connecticut, Vermont, New Hampshire, New York, New Jersey, Massachusetts, Rhode Island, Michigan, Indiana, Ohio, Virginia, West Virginia, Illinois, Arkansas, Tennessee, North Carolina, South Carolina, Florida, Arkansas, Alabama, Mississippi, Washington, Idaho, Montana, Minnesota, Wisconsin, South Dakota, Colorado, Louisiana, Texas, New Mexico, Oklahoma, and Wyoming. A tight vertical line pattern marks states that reported 0 percent external handling—Oregon, Nevada, North Dakota, Kentucky, and Utah—accounting for 9.8 percent, with N equal to 5. A right diagonal line pattern marks states that reported 10 percent handling—California, Pennsylvania, and Kansas—totaling 5.9 percent, with N equal to 3. A pattern of circles marks Iowa, the single state that reported 50 percent handling, accounting for 2.0 percent. A vertical stripe pattern marks states that reported 100 percent handling—Alaska and the District of Columbia—accounting for 3.9 percent, with N equal to 2. A blank fill marks states that reported no Lidar usage—Georgia, Arizona, Delaware, and Nebraska—totaling 7.8 percent, with N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows the percentage of other Lidar data collection handled by external firms for asset management by United States state departments of transportation, using three fill patterns. A crosshatch pattern marks Idaho, the single state that reported 0 percent external handling, accounting for 2.0 percent. A blank fill marks states that reported no Lidar usage—Georgia, Arizona, Delaware, and Nebraska—accounting for 7.8 percent, with sample size N equal to 4. A diagonal line pattern marks the remaining 46 states, which reported no other Lidar system usage—accounting for 90.2 percent. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the percentage of other Lidar data collection handled by external firms for asset management by United States state departments of transportation, specifically addressing “other” systems such as fixed Lidar units, using three fill patterns. A diagonal stripe pattern marks Idaho, the single state that uses fixed Lidar units to measure salt inventory, accounting for 2.0 percent. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with sample size N equal to 4. A diagonal line pattern marks the remaining 46 states, which reported no other Lidar system usage, accounting for 90.2 percent. The legend defines each pattern by Lidar usage description, total percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Idaho Fixed lidar unit to measure salt inventory

4B. Approximately what percentage of the lidar data used by your DOT is processed by external firms?

The hexagon map shows the percentage of Lidar data processing handled by external firms for asset management by United States state departments of transportation, using 11 fill patterns. A tight vertical line pattern marks states that reported 0 percent external processing—Ohio and Hawaii—accounting for 3.9 percent, with a sample size N equal to 2. A left diagonal stripe pattern marks states that reported 10 percent external processing—Arkansas and Missisippi—accounting for 3.9 percent, with N equal to 2. A right diagonal stripe pattern marks states that reported 20 percent—Washington and Oregon—accounting for 3.9 percent, with N equal to 2. A star pattern marks states that reported 30 percent—California and Maine—accounting for 3.9 percent, with N equal to 2. A pattern of red circles marks states that reported 50 percent—Vermont, New Hampshire, New Jersey, West Virginia, Louisiana, Nevada, and Wyoming—accounting for 13.7 percent, with N equal to 7. A pattern of yellow circles marks states that reported 60 percent—Alaska, Indiana, and Wisconsin—totaling 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that reported 70 percent—Connecticut, Pennsylvania, New York, Virginia, Illinois, Kentucky, Colorado, North Dakota, Idaho, Missouri, Kansas, and Alabama—accounting for 23.6 percent, with N equal to 12. A crosshatch pattern marks states that reported 80 percent—Iowa, New Mexico, and Florida—accounting for 5.9 percent, with N equal to 3. A horizontal line fill pattern marks states that reported 90 percent—South Dakota, Utah, Oklahoma, Texas, Tennessee, South Carolina, Minnesota, and Michigan—accounting for 15.7 percent, with N equal to 8. A vertical stripe pattern marks states that reported 100 percent—Montana, Massachusetts, Rhode Island, North Carolina, Maryland, and the District of Columbia—totaling 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—totaling 7.8 percent, with N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group.

4C. Approximately what percentage of the lidar data used by your DOT is downloaded from public domain repositories (e.g., USGS 3D elevation program (3DEP), lidar consortiums, open topography)?

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the percentage of Lidar data downloaded from public domain repositories by United States state departments of transportation, using 11 fill patterns. A pattern of tight vertical lines marks states that reported 0 percent Lidar data downloaded—Hawaii, Maryland, and New Hampshire—accounting for 5.9 percent, with sample size N equal to 3. A right diagonal pattern marks states that reported 10 percent downloaded—Arkansas, California, Florida, Idaho, Minnesota, Missouri, Mississippi, New Jersey, North Dakota, Texas, Tennessee, West Virginia, Wisconsin, and Vermont—accounting for 27.4 percent, with N equal to 14. A left diagonal pattern marks states that reported 20 percent downloading—Alaska, Oregon, Washington, Colorado, South Dakota, New Mexico, North Carolina, South Carolina, New York, and Michigan—accounting for 19.6 percent, with N equal to 10. A star pattern marks states that reported 30 percent—Maine, Illinois, and Ohio—accounting for 5.9 percent, with N equal to 3. A dotted pattern marks states that reported 40 percent—Indiana, Kansas, and Virginia—accounting for 5.9 percent, with N equal to 3. A circle pattern marks states that reported 50 percent—Nevada, Iowa, Louisiana, the District of Columbia, Connecticut, and Rhode Island—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch fill pattern marks states that reported 70 percent—Pennsylvania and Kentucky—accounting for 3.9 percent, with N equal to 2. A crosshatch pattern marks Alabama, the single state that reported 80 percent, accounting for 2.0 percent. A vertical line pattern marks Montana, the single state that reported 100 percent, accounting for 2.0 percent. A diagonal crosshatch pattern marks states that did not respond to this question—Utah, Wyoming, Oklahoma, and Massachusetts—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Georgia, Nebraska, and Delaware—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage percentage, total percentage, and sample size, where N is the number of states in each group.

  1. How is your DOT approaching the transition from 2D to 3D workflows in the context of lidar data?

The hexagon map shows transition strategies from 2 D to 3 D workflows in departments of transportation using Lidar across the United States states, using 8 fill patterns. A horizontal line fill pattern marks states that reported a comprehensive shift to 3 D workflows—Arkansas, Kentucky, Kansas, Louisiana, Missouri, North Carolina, Ohio, and Illinois—accounting for 15.7 percent, with sample size N equal to 8. A crosshatch pattern marks states that reported gradual implementation across projects—Connecticut, Idaho, Indiana, Maine, New York, Virginia, West Virginia, New Jersey, Maryland, the District of Columbia, Florida, Tennessee, Texas, and Wyoming—accounting for 27.4 percent, with N equal to 14. A diagonal crosshatch pattern marks Rhode Island, the single state that reported no transition in place and primarily 2 D workflows—accounting for 2.0 percent. A diagonal line pattern marks states that reported specific projects focused on 3 D workflows—Alaska, Alabama, California, Colorado, Hawaii, Iowa, Minnesota, Nevada, New Mexico, Oregon, South Dakota, Pennsylvania, and Utah—accounting for 25.5 percent, with N equal to 13. A circle pattern representing high definition mapping infrastructure (H D M I) or base maps for autonomous vehicles is shown in the legend but is not present on any state, accounting for 0.0 percent, with N equal to 0. A dotted fill pattern marks states that reported other strategies—Massachusetts, Oklahoma, South Carolina, Washington, and Mississippi—accounting for 9.8 percent, with N equal to 5. A tight crosshatch pattern marks states that reported they are not sure—New Hampshire, Vermont, Montana, North Dakota, Michigan, and Wisconsin—accounting for 11.8 percent, with N equal to 6. A blank pattern marks states that reported no Lidar usage—Georgia, Arizona, Delaware, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by workflow strategy, total percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Oklahoma We are still using bare earth lidar models, have not started using the full lidar point clouds.
South Carolina Contractors are creating 3D models for construction, but SCDOT policy at this moment is 2D plans control construction projects.
Washington Our statewide project development approach is in 3D. Lidar is included in our 3D field data/terrains when available.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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  1. How many staff members are currently allocated to lidar efforts within your DOT?

The hexagon map shows staff allocation for Lidar efforts in departments of transportation across the United States states, using five fill patterns. A horizontal line pattern marks states that reported extensive staff, for example, 6 or more dedicated personnel—Alaska, Arkansas, California, Colorado, Illinois, Florida, Mississippi, New York, Mississippi, New Jersey, the District of Columbia, and Maryland—accounting for 23.5 percent, with sample size N equal to 12. A crosshatch pattern marks states that reported limited staff, for example, 1 or 2 individuals—Montana, South Dakota, Iowa, Wisconsin, Kentucky, Virginia, South Carolina, Massachusetts, New Hampshire, Rhode Island, and Vermont—accounting for 21.6 percent, with N equal to 11. A diagonal line pattern marks states that reported moderate staff, for example, 3 to 5 individuals or a small team—Alabama, Connecticut, Hawaii, Indiana, Maine, Minnesota, Nevada, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, Kansas, Louisiana, Oregon, Pennsylvania, Utah, Texas, Wyoming, and West Virginia—accounting for 39.3 percent, with N equal to 20. A tight crosshatch pattern marks states that responded “Not sure”—Idaho, Michigan, Missouri, and Tennessee—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Delaware, Florida, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by staff level, total percentage, and sample size, where N is the number of states in each group.

Lidar Data Applications within your DOT

  1. For each application, indicate the approximate level of usage of lidar data by your DOT (Never, Rarely, Sometimes, Regularly, Routine)

The hexagon map shows levels of Lidar data usage in D O T roadway design projects across the United States, using seven fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—the District of Columbia and Wyoming—accounting for 3.9 percent, with sample size N equal to 2. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Minnesota, Massachusetts, Vermont, and New Mexico—accounting for 7.8 percent, with N equal to 4. A dotted pattern overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Alaska, Connecticut, Florida, Iowa, Louisiana, Mississippi, Kansas, Maine, Maryland, New Hampshire, North Dakota, South Carolina, Texas, Virginia, West Virginia, and Washington—accounting for 31.5 percent, with N equal to 16. A vertical line fill pattern marks states that reported using Lidar data routinely, that is, consistently and as part of standard practice—Alabama, Arkansas, Tennessee, North Carolina, Kentucky, Missouri, Colorado, California, Oklahoma, Oregon, Ohio, New Jersey, New York, Wisconsin, and Michigan—accounting for 29.4 percent, with N equal to 15. A circle pattern marks states that reported sometimes using Lidar data—Hawaii, Idaho, Nevada, Pennsylvania, Indiana, Illinois, Rhode Island, South Dakota, Utah—accounting for 17.6 percent, with N equal to 9. A tight crosshatch pattern marks Montana, the single state that gave no response to this question, accounting for 2.0 percent. A blank pattern marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows levels of Lidar data usage in D O T roadway environmental analysis projects across the United States, using seven fill patterns. A horizontal line pattern marks states that reported never using Lidar data—Utah, Wyoming, New Mexico, Oklahoma, Minnesota, Indiana, Illinois, Mississippi, Pennsylvania, South Carolina, Tennessee, the District of Columbia, Maryland, and Vermont—accounting for 27.5 percent, with sample size N equal to 14. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Florida, Idaho, Nevada, North Carolina, South Dakota, Iowa, Massachusetts, New Hampshire, and West Virginia—accounting for 17.6 percent, with N equal to 9. A dotted pattern overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Alaska, Washington, Arkansas, Kentucky, Ohio, and Wisconsin—accounting for 11.8 percent, with N equal to 6. A vertical line pattern marks Missouri, the single state that reported routine usage of Lidar data, that is, consistently and as part of standard practice, accounting for 2.0 percent. A circle pattern overlaid with diagonal lines marks states that reported sometimes using Lidar data—Alabama, Connecticut, Maine, Rhode Island, Virginia, Michigan, Louisiana, Kansas, Texas, Colorado, North Dakota, Oregon, and California—accounting for 25.5 percent, with N equal to 13. A tight crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, New Jersey, and New York—accounting for 7.8 percent, with N equal to 4. A blank pattern marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows levels of Lidar data usage for construction quality control in D O T roadway projects across the United States, using six fill patterns. A horizontal line pattern marks states that reported never using Lidar data—Colorado, North Dakota, Idaho, Nevada, South Dakota, Indiana, Minnesota, Mississippi, the District of Columbia, Wyoming, New Mexico, and Vermont—accounting for 23.5 percent, with sample size N equal to 12. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Utah, Iowa, Illinois, Missouri, Kansas, Michigan, South Carolina, Florida, Connecticut, Massachusetts, and Maine—accounting for 21.6 percent, with N equal to 11. A dotted pattern overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Alaska, Washington, Oregon, New York, Arkansas, and Maryland—accounting for 11.8 percent, with N equal to 6. A circle pattern overlaid with diagonal lines marks states that reported sometimes using Lidar data—California, Texas, Oklahoma, Wisconsin, Louisiana, Kentucky, Tennessee, Alabama, North Carolina, Virginia, West Virginia, Ohio, Pennsylvania, New Hampshire, and Rhode Island—accounting for 29.4 percent, with N equal to 15. A crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, and New Jersey—accounting for 5.9 percent, with N equal to 3. A blank pattern marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows levels of Lidar data usage in D O T roadway as-built projects across the United States, using seven fill patterns. A horizontal line pattern marks states that reported never using Lidar data—Florida, Oregon, Nevada, Idaho, North Dakota, Wyoming, South Dakota, Iowa, Illinois, Missouri, Kansas, Oklahoma, New Mexico, Indiana, Mississippi, the District of Columbia, and Texas—accounting for 33.3 percent, with sample size N equal to 17. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Maine, Massachusetts, Vermont, Connecticut, North Carolina, South Carolina, Kentucky, Michigan, Ohio, Colorado, and Utah—accounting for 21.6 percent, with N equal to 11. A dotted pattern overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Alaska, Washington, and Maryland—accounting for 5.9 percent, with N equal to 3. A vertical line pattern marks Minnesota, the single state that reported using Lidar data routinely, that is, consistently and as part of standard practice—accounting for 2.0 percent, with N equal to 1. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar data—California, Wisconsin, Arkansas, Louisiana, Tennessee, Alabama, Virginia, West Virginia, Pennsylvania, Rhode Island, and New Hampshire—accounting for 21.6 percent, with N equal to 11. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, New Jersey, and New York—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows levels of Lidar data usage in other D O T roadway projects across the United States, using five fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—Arkansas, Nevada, New Mexico, Louisiana, North Carolina, and Massachusetts—accounting for 11.8 percent, with sample size N equal to 6. A pattern of dots overlaid with diagonal lines marks Alabama, the single state that reported using Lidar data regularly, that is, frequently but not constantly, accounting for 2.0 percent, with N equal to 1. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar data—California, Hawaii, Mississippi, and South Carolina—accounting for 7.8 percent, with N equal to 4. A diagonal crosshatch pattern marks states that gave no response to this question—Alaska, Washington, Montana, North Dakota, Minnesota, Wisconsin, Oregon, Idaho, Wyoming, South Dakota, Iowa, Utah, Illinois, Indiana, Colorado, Oklahoma, Texas, Kansas, Tennessee, Florida, Missouri, Kentucky, West Virginia, Virginia, the District of Columbia, Michigan, Maryland, Connecticut, New Jersey, Pennsylvania, Ohio, New York, Rhode Island, New Hampshire, Vermont, and Maine—accounting for 70.6 percent, with N equal to 36. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows types of Lidar data usage in other D O T roadway projects across the United States, using eight fill patterns. A diagonal line fill pattern marks Alabama, the single state reporting 3 D visualization or animations, accounting for 2.0 percent. A crosshatch pattern marks Hawaii, the single state that reported only being able to speak to its section, accounting for 2.0 percent. A dotted pattern marks South Carolina, the single state that reported contractors using U A S for borrow quantities, accounting for 2.0 percent. A horizontal line fill pattern marks California, which reported currently working on a project where as-builts are collected using Lidar and some construction quality control is done, such as underground utilities, using Lidar, accounting for 2.0 percent. A pattern of circles marks New Mexico, the single state that responded “not applicable” to the question, accounting for 2.0 percent. An open diagonal crosshatch pattern marks Massachusetts, the single state that reported a preliminary design study, accounting for 2.0 percent. A tight crosshatch pattern marks states that gave no response to this question—Alaska, Arkansas, Colorado, Connecticut, the District of Columbia, Florida, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Wyoming, Missouri, Montana, Nevada, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, and Wisconsin—accounting for 80.2 percent, with N equal to 41. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage type, total percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Alabama 3D Visualization/Animations
California Currently working on project where as-builts are collected using LiDAR and some Construction Quality Control is done using LiDAR such as underground utilities.
Hawaii Can only speak to our section
Mississippi Preliminary design study
New Mexico Not Applicable
South Carolina Contractors using UAS for borrow quantities
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows levels of Lidar data usage in D O T operations, maintenance, and safety bridge inspection projects across the United States, using seven fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—Alabama, Mississippi, Minnesota, North Dakota, Indiana, New Hampshire, Oklahoma, New Mexico, Wyoming, and Vermont—accounting for 19.6 percent, with sample size N equal to 10. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—California, the District of Columbia, Connecticut, Idaho, Illinois, Iowa, Missouri, Maryland, Massachusetts, Nevada, Ohio, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Texas, Utah, and Wisconsin—accounting for 37.3 percent, with N equal to 19. A pattern of dots overlaid by diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Maine, Kansas, Virginia, and Tennessee—accounting for 7.8 percent, with N equal to 4. A vertical line pattern marks states that reported using Lidar data routinely, that is, consistently and as part of standard practice—Alaska, Washington, and Louisiana—accounting for 5.9 percent, with N equal to 3. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar data: Arkansas, Florida, Kentucky, Michigan, North Carolina, West Virginia, Colorado, and New York—accounting for 15.7 percent, with N equal to 8. A diagonal crosshatch fill pattern marks states that gave no response to this question—Hawaii, Montana, and New Jersey—accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows levels of Lidar data usage in D O T operations, maintenance, and safety slope stability projects across the United States, using seven fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—Florida, Nevada, Utah, Wyoming, Minnesota, New Mexico, Oklahoma, and the District of Columbia—accounting for 15.7 percent, with sample size N equal to 8. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Massachusetts, Rhode Island, Connecticut, Texas, Illinois, Indiana, Kentucky, and Wisconsin—accounting for 15.7 percent, with N equal to 8. A pattern of dots overlaid by diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—California, Oregon, Idaho, Louisiana, Ohio, Kansas, Arkansas, Missouri, Michigan, and New York—accounting for 19.6 percent, with N equal to 10. A vertical line pattern marks states that reported using Lidar data routinely, that is, consistently and as part of standard practice—Alaska, Colorado, Tennessee, and Washington, accounting for 7.8 percent, with N equal to 4. A pattern of circles overlaid by diagonal lines marks states that reported sometimes using Lidar data—Alabama, Iowa, Maine, Maryland, New Hampshire, North Carolina, North Dakota, Pennsylvania, South Dakota, Vermont, Virginia, and West Virginia—accounting for 23.6 percent, with N equal to 12. A crosshatch fill pattern marks states that gave no response to this question—Hawaii, Montana, Mississippi, New Jersey, and South Carolina—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. The hexagon map shows levels of Lidar data usage in D O T operations, maintenance, and safety hydrological studies projects across the United States, using seven fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—Minnesota, Wyoming, Utah, South Dakota, Indiana, Kentucky, Maryland, New Hampshire, New Mexico, Oklahoma, and Vermont—accounting for 21.6 percent, with sample size N equal to 11. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Idaho, Massachusetts, Rhode Island, and Connecticut—accounting for 7.8 percent, with N equal to 4. A dotted pattern overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Arkansas, Texas, Tennessee, South Carolina, Washington, Oregon, Colorado, Pennsylvania, the District of Columbia, Maine, and Virginia—accounting for 21.6 percent, with N equal to 11. A vertical line pattern marks states reported using Lidar data routinely, that is, consistently and as part of standard practice—Alaska, Alabama, California, Missouri, and New York—accounting for 9.8 percent, with N equal to 5. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar data—Florida, Illinois, Iowa, Kansas, Louisiana, Michigan, North Dakota, Nevada, North Carolina, Ohio, West Virginia, and Wisconsin—accounting for 23.6 percent, with N equal to 12. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, Mississippi, and New Jersey—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows levels of Lidar data usage in road safety analysis projects for D O T operations, maintenance, and safety across the United States, using seven fill patterns. A horizontal line fill pattern marks states that reported never using Lidar data—Illinois, Nevada, New Mexico, Oklahoma, South Dakota, Wyoming, and Vermont—accounting for 13.7 percent, with sample size N equal to 7. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Indiana, Idaho, Utah, Colorado, Texas, Iowa, Missouri, Kentucky, Florida, Maryland, Connecticut, Massachusetts, Rhode Island, and Maine, which, accounting for 27.5 percent, with N equal to 14. A pattern of dots overlaid with diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not constantly—Oregon, Alabama, the District of Columbia, Arkansas, Kansas, New York, and North Carolina—accounting for 13.7 percent, with N equal to 7. A vertical line pattern marks Alaska, the single state that reported using Lidar data routinely, that is, consistently and as part of standard practice—accounting for 2.0 percent. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar data—California, Washington, North Dakota, Minnesota, Wisconsin, Louisiana, Mississippi, Tennessee, Virginia, West Virginia, Ohio, Michigan, Pennsylvania, and New Hampshire—accounting for 27.5 percent, with N equal to 14. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, New Jersey, and South Carolina—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, total percentage, and sample size, where N is the number of states in each group. A hexagon map shows levels of Lidar data usage in state D O T operations, maintenance, and safety projects for the Highway Performance Management System using seven distinct fill patterns. A horizonal striped pattern marks states that never use Lidar—South Dakota, Iowa, Wisconsin, Indiana, Ohio, Vermont, Missouri, Kentucky, New Mexico, and Oklahoma—accounting for 19.6 percent, with sample size N equal to 10. A crosshatch pattern overlaid with diagonal lines marks states that use Lidar rarely, in research or pilot projects—Washington, Idaho, Colorado, Wyoming, Minnesota, Texas, Michigan, West Virginia, Massachusetts, Maryland, Connecticut, Rhode Island, and Maine—accounting for 25.7 percent, with N equal to 13. A pattern of dots overlaid by diagonal lines marks states that use Lidar regularly, that is, frequently but not constantly—Kansas and North Carolina—accounting for 3.9 percent, with N equal to 2. A vertical line fills marks states that use Lidar routinely, that is, consistently and as part of standard practice—Alaska, California, Nevada, Utah, Illinois, Tennessee, Mississippi, Florida, and the District of Columbia—accounting for 17.6 percent, with N equal to 9. A pattern of circles overlaid by diagonal lines marks states that use Lidar sometimes—Oregon, North Dakota, Louisiana, Arkansas, Alabama, Virginia, Pennsylvania, New York, and New Hampshire—also accounting for 17.6 percent, with N equal to 9. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, South Carolina, New Jersey, and Hawaii—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—also accounting for 7.8 percent, with N equal to 4. The legend defines these seven categories with their respective fill patterns and proportions. A hexagon map shows levels of Lidar data usage in other state D O T operations, maintenance, and safety projects using six distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data—Alabama, Arkansas, Idaho, Louisiana, Nevada, and New Mexico—accounting for 11.8 percent, with sample size N equal to 6. A crosshatch pattern overlaid with diagonal lines marks Massachusetts, the single state that reported using Lidar data rarely, that is, for research or pilot projects, accounting for 2.0 percent. A pattern of dots overlaid by diagonal lines marks states that reported using Lidar data regularly, that is, frequently but not consistently—California, New York, and Mississippi—accounting for 5.9 percent, with N equal to 3. A pattern of circles overlaid with diagonal lines marks Hawaii, the single state that reported using Lidar data sometimes—accounting for 2.0 percent. A diagonal crosshatch pattern marks states that did not respond—Alaska, Florida, Colorado, Connecticut, the District of Columbia, Illinois, Indiana, Iowa, Kansas, Kentucky, Maine, Maryland, Michigan, Minnesota, Missouri, Montana, New Hampshire, New Jersey, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming—accounting for 70.5 percent, with N equal to 36. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
California Slope Stability is done using photogrammetry UAS to produce a point cloud .las file.
Hawaii Can only speak to our section
Mississippi Digital road network (MLRS) update and maintenance
New Mexico Not Applicable
New York Vertical clearances

The hexagon map shows levels of Lidar data usage in D O T mapping projects by U S state using seven distinct fill patterns. A horizontal line pattern marks Vermont, the single state to report never using Lidar data for mapping, accounting for 2.0 percent. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar data rarely, for research or pilot projects—Iowa, Kentucky, and Massachusetts—accounting for 5.9 percent, with sample size N equal to 3. A pattern of dots overlaid by diagonal lines marks states that reported using Lidar regularly, that is, frequently but not constantly—Alabama, Idaho, Louisiana, New Hampshire, Nevada, South Carolina, Virginia, and Washington—accounting for 15.7 percent, with N equal to 8. A vertical line pattern marks states that reported using Lidar data routinely, that is, consistently and as part of regular practice—California, Colorado, Illinois, Missouri, New York, North Carolina, Ohio, Oklahoma, Oregon, Wyoming, Tennessee, West Virginia, and Wisconsin—accounting for 25.5 percent, with N equal to 13. A pattern of circles overlaid with diagonal lines marks states that reported using Lidar sometimes—Connecticut, Florida, Hawaii, Indiana, New Mexico, Rhode Island, and Utah—accounting for 13.7 percent, with N equal to 7. A diagonal crosshatch pattern marks states that gave no response—Alaska, Arkansas, the District of Columbia, Kansas, Maine, Maryland, Michigan, Minnesota, Mississippi, Montana, New Jersey, North Dakota, Pennsylvania, South Dakota, and Texas—accounting for 29.4 percent, with N equal to 15. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group. The hexagon map shows Lidar data usage in D O T asset management projects by U S state using seven distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data for asset management—Connecticut, Iowa, North Dakota, Oklahoma, Pennsylvania, Vermont, Wisconsin, and Wyoming—accounting for 15.7 percent, with sample size N equal to 8. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar rarely, for research or pilot projects—Colorado, Florida, Maine, Massachusetts, Rhode Island, South Carolina, South Dakota, and Texas, which report rare use, accounting for 15.7 percent, with N equal to 8. A pattern of dots overlaid with diagonal lines marks states that reported using Lidar regularly, that is, frequently but not consistently—California, Idaho, Maryland, Michigan, New Hampshire, Ohio, Kansas, Louisiana, Alabama, Oregon, and Washington—accounting for 21.6 percent, with N equal to 11. A vertical pattern marks states that reported using Lidar routinely, that is, consistently and as part of standard practice—Alaska, Minnesota, New York, Nevada, Tennessee, and Utah—accounting for 11.8 percent, with N equal to 6. A pattern of circles overlaid with diagonal lines marks states that reported using Lidar sometimes—Arkansas, Illinois, Indiana, Kentucky, Mississippi, Missouri, New Mexico, North Carolina, Virginia, and West Virginia—accounting for 19.6 percent, with N equal to 10. A diagonal crosshatch pattern marks states that gave no response—the District of Columbia, Hawaii, Montana, and New Jersey—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—also accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows Lidar data usage in D O T emergency response projects by U S state using seven distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data for emergency response projects—the District of Columbia, Idaho, Illinois, Iowa, Kansas, Minnesota, Missouri, New Mexico, Nevada, North Dakota, Oklahoma, Pennsylvania, South Dakota, Vermont, and Wyoming—accounting for 29.4 percent, with sample size N equal to 15. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar rarely, for research or pilot projects—Connecticut, Florida, Kentucky, Indiana, Maine, Utah, Virginia, Washington, West Virginia, and Rhode Island—accounting for 19.6 percent, with N equal to 10. A pattern of dots overlaid with diagonal lines marks states that reported using Lidar regularly, that is, frequently but not consistently—California, New Hampshire, and Tennessee—accounting for 5.9 percent, with N equal to 3. A vertical line pattern marks Alaska, the single state that reported using Lidar routinely, that is, consistently and as part of standard practice—accounting for 2.0 percent. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar—Alabama, Arkansas, Louisiana, Maryland, Massachusetts, Michigan, Mississippi, New York, North Carolina, Oregon, Colorado, Texas, and Wisconsin—accounting for 25.5 percent, with N equal to 13. A diagonal crosshatch pattern marks states that gave no response—Hawaii, Montana, New Jersey, Ohio, and South Carolina—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group. The hexagon map shows Lidar data usage in D O T crash reconstruction for quick clearance projects by U S state using six distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data in crash reconstruction—Alabama, Colorado, the District of Columbia, Idaho, Illinois, Indiana, Iowa, Kansas, Maine, Maryland, Mississippi, New Hampshire, New Mexico, New York, Nevada, North Carolina, North Dakota, Oklahoma, Pennsylvania, South Dakota, Tennessee, Vermont, West Virginia, Wisconsin, and Wyoming—accounting for 49.1 percent, with sample size N equal to 25. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar rarely, for research or pilot projects—Connecticut, Kentucky, Massachusetts, Michigan, Rhode Island, Virginia, and Washington—accounting for 13.7 percent, with N equal to 7. A vertical line pattern marks states that reported using Lidar routinely, that is, consistently and as part of standard practice—Alaska and Minnesota—accounting for 3.9 percent, with N equal to 2. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar—Arkansas, California, Florida, Louisiana, Missouri, Oregon, Texas, and Utah—accounting for 15.7 percent, with N equal to 8. A diagonal crosshatch pattern marks states that gave no response—Hawaii, Montana, New Jersey, Ohio, South Carolina—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group. The hexagon map shows levels of Lidar data usage in other D O T projects (1) by U S state, using seven distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data for other D O T projects—Arkansas, Illinois, North Carolina, and Nevada—accounting for 7.8 percent, with sample size N equal to 4. A crosshatch pattern overlaid with diagonal lines marks states that reported using Lidar rarely, for research or pilot projects—Idaho, Iowa, and Massachusetts—accounting for 5.9 percent, with N equal to 3. A pattern of dots overlaid with diagonal lines marks Wisconsin, the single state that reported using Lidar regularly, that is, frequently but not consistently—accounting for 2.0 percent. A vertical line pattern marks states that reported using Lidar routinely, that is, consistently and as part of standard practice—New York and Oregon—accounting for 3.9 percent, with N equal to 2. A pattern of circles overlaid with diagonal lines marks West Virginia, the single state that reported sometimes using Lidar, accounting for 2.0 percent. A diagonal crosshatch pattern marks states that gave no response—Alaska, Alabama, California, Colorado, Connecticut, the District of Columbia, Florida, Hawaii, Indiana, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, Montana, New Hampshire, New Jersey, New Mexico, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, and Wyoming—accounting for 70.6 percent, with N equal to 36. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Hawaii Can only speak to our section
Idaho Salt Inventory
Iowa In support of roadway inventory and LRS
New Mexico Not Applicable
New York Sidewalks and Curb Ramps
Oregon Vertical clearance
West Virginia Monitoring (Bridge/Tunnel)
Wisconsin Wall Monitoring

The hexagon map shows Lidar data usage in other D O T projects (2) by U S states, using six distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data for other D O T projects—Arkansas, Illinois, New Mexico, and Nevada—accounting for 7.8 percent, with sample size N equal to 4. A crosshatch pattern overlaid with diagonal lines marks Massachusetts, the single state that reported using Lidar rarely, for research or pilot projects, accounting for 2.0 percent. A pattern of dots overlaid with diagonal lines marks states that reported using Lidar regularly, that is, frequently but not consistently—New York and Wisconsin—accounting for 3.9 percent, with N equal to 2. A pattern of circles overlaid with diagonal lines marks states that reported sometimes using Lidar—Idaho and Iowa—accounting for 3.9 percent, with N equal to 2. A diagonal crosshatch pattern marks states that gave no response—Alaska, Alabama, California, Colorado, Connecticut, the District of Columbia, Florida, Hawaii, Indiana, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, Montana, New Hampshire, New Jersey, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, Wyoming, and West Virginia—accounting for 74.6 percent, with N equal to 38. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Idaho Slide Monitoring
Iowa Vertical Clearance Inventory
New Mexico Not Applicable
New York Culverts
Wisconsin Bridge Vertical Clearance
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows Lidar data usage in other D O T projects (3) by U S state, using four distinct fill patterns. A horizontal line pattern marks states that reported never using Lidar data in other D O T projects—Arkansas, Illinois, New Mexico, and Nevada—accounting for 7.8 percent, with sample size N equal to 4. A crosshatch pattern overlaid with diagonal lines marks Massachusetts, the single state that reported using Lidar rarely, for research or pilot projects, accounting for 2.0 percent. A crosshatch pattern marks states that gave no response—Alaska, Alabama, California, Colorado, Connecticut, the District of Columbia, Florida, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, Montana, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming—accounting for 82.4 percent, with N equal to 42. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage level, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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  1. For each application, please indicate the main challenges from the list below:

Roadway Projects

State DOT Lack of trust in lidar data quality Software compatibility Difficulties in obtaining similar results to traditional workflows Limited experience, training, and capabilities Insufficient IT infrastructure (data storage, network latency, software tools, etc.) Other methods provide higher ROI Effort required to extract information from lidar data Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements Not Sure
Alabama - - - X - - X X -
Alaska - X - - X X - X -
Arizona
Arkansas - - - - - - - - -
California - - - - - - X - -
Colorado X X - - X - X X -
Connecticut X - - X X X X - -
Delaware
District of Columbia - - - - - - - - -
Florida - - - - X - - X -
Georgia
Hawaii - - - - X - - - -
Idaho - - - X - - X X -
Illinois - - - - X - - - -
Indiana X - X X X X - X -
Iowa - X - X X X X X -
Kansas - X - X - X X X -
Kentucky - - - - - - - X -
Louisiana - - X - - - - - -
Maine - - - X - - X X -
Maryland - - - - - - - - -
Massachusetts - X - X - X - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Michigan - - - - - - - - -
Minnesota - - - - - - X X -
Mississippi - - - X - - - - -
Missouri - - - - X - X - -
Montana X - - - - - X X -
Nebraska
Nevada - X - X - X - X -
New Hampshire X X X X X - X X -
New Jersey - - - - - - - - -
New Mexico - X X X - - X - -
New York - - - - X - X X -
North Carolina - - - X X - - - -
North Dakota - - - - - - - X -
Ohio - - - - - - - - -
Oklahoma - X - X - - X X -
Oregon - - - X - - - - -
Pennsylvania - X - - X - - - -
Rhode Island - - - X X - - - -
South Carolina - - - X X - - - -
South Dakota - - X - - - X - -
Tennessee - - - - X - X X -
Texas X - X X X - X X -
Utah - - X - - - X - -
Vermont - - - - - - - - -
Virginia - - - X X - X X -
Washington - - - X - - - - -
West Virginia - - - - X - - X -
Wisconsin - - - - - - - - -
Wyoming - - - - - - - - -
Total 6 10 7 20 19 7 20 21 0
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Operations, Maintenance, and Safety

State DOT Lack of trust in lidar data quality Software compatibility Difficulties in obtaining similar results to traditional workflows Limited experience, training, and capabilities Insufficient IT infrastructure (data storage, network latency, software tools, etc.) Other methods provide higher ROI Effort required to extract information from lidar data Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements Not Sure
Alabama - X - X - - X - -
Alaska - - - - X X - X -
Arizona
Arkansas - - - - - - - X -
California - - - X - - - X -
Colorado X X X X X - X - -
Connecticut X - - X X X - X -
Delaware
District of Columbia - - - - - - - - -
Florida - X - X X - X X -
Georgia
Hawaii - - - - - - - - -
Idaho - X - X - - X - -
Illinois X X X - X - X X -
Indiana - - - - X - - X -
Iowa - X - X X X X X -
Kansas - - - - - - - - X
Kentucky - - - X - - X X -
Louisiana - - - - - - - - -
Maine - - - X - - X - -
Maryland - - - - - - - - -
Massachusetts - X X X - - X X -
Michigan - - - X X - - X X
Minnesota - - - - - - X X -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Mississippi - - - X - - - - -
Missouri - - - - - - - - X
Montana X - - - - - - - -
Nebraska
Nevada - - - - - - - - X
New Hampshire - - - - X - - - X
New Jersey - - - - - - - - -
New Mexico - - - X - - X - -
New York - - - - - - - - X
North Carolina - - - X X - - - -
North Dakota - - - - - - - - X
Ohio - - - - - - - - -
Oklahoma - - - - - - - - X
Oregon - - - X - - - X -
Pennsylvania - - - - - - - - -
Rhode Island - - - X X - - - -
South Carolina - - - X X - - - -
South Dakota - - - X - - - - X
Tennessee X - X X - - X - -
Texas - - - - - - - - -
Utah - - - - X - X - -
Vermont - - - - - - - - X
Virginia - - - - - - - - -
Washington - - - X - - - - -
West Virginia - - - - X - - - X
Wisconsin - - - - - - - - X
Wyoming - - - - - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Mapping

State DOT Lack of trust in lidar data quality Software compatibility Difficulties in obtaining similar results to traditional workflows Limited experience, training, and capabilities Insufficient IT infrastructure (data storage, network latency, software tools, etc.) Other methods provide higher ROI. Effort required to extract information from lidar data Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements Not Sure
Alabama - - - X - - X - -
Alaska - - - - X - - X -
Arizona
Arkansas - - - - - - - - -
California - - - - - - X - -
Colorado X X X - X - X X -
Connecticut X - - X X X X - -
Delaware
District of Columbia - - - - - - - - -
Florida - - - - X - - - -
Georgia
Hawaii - - - - - - - - -
Idaho - - - X - - X - -
Illinois - - X - X - - X -
Indiana - X - X - - X X -
Iowa - X - X X X X X -
Kansas - - - - - - - - X
Kentucky - - - X - X - X -
Louisiana - - - X - - - - -
Maine - - - X - - X X -
Maryland - - - X X - X - -
Massachusetts - X X X X - X X -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Michigan - - - X X - - X X
Minnesota - - - - - - X X -
Mississippi - - - X - - - - -
Missouri - - - - X - - - -
Montana X - - - - - X X -
Nebraska
Nevada - - - - X X X X -
New Hampshire X X X X X - - - X
New Jersey - - - - - - - - -
New Mexico - - - X - - X - -
New York - - - - X - X X -
North Carolina - - - X X - - - -
North Dakota - - - - - - - - X
Ohio - - - - - - - - -
Oklahoma - X - X - - X X -
Oregon - - - X - - - - -
Pennsylvania - - - - X - - - -
Rhode Island - - - X X - - - -
South Carolina - - - - X - - - -
South Dakota - - X - - - X - -
Tennessee - - - - X - X X -
Texas X - X X X - X X -
Utah - - - - - - X - -
Vermont - - - - - - - - X
Virginia X - - X X - X X -
Washington - - - X - - - - -
West Virginia - - - - X - - X -
Wisconsin - - - - - - - - -
Wyoming - - - - - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Asset Management

State DOT Lack of trust in lidar data quality Software compatibility Difficulties in obtaining similar results to traditional workflows Limited experience, training, and capabilities Insufficient IT infrastructure (data storage, network latency, software tools, etc.) Other methods provide higher ROI Effort required to extract information from lidar data Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements Not Sure
Alabama - X - X - - X X -
Alaska - - - - X X - X -
Arizona
Arkansas X X X X X X X X -
California - - - - - - X - -
Colorado - X - - X - X - -
Connecticut - - - - - - - - X
Delaware
District of Columbia - - - - - - - - -
Florida - X - X X - X X -
Georgia
Hawaii - - - - - - - - -
Idaho - X - X - - X - -
Illinois X X X X X - X X -
Indiana - - - - - - - - -
Iowa - X - X X X X X -
Kansas X - X - X - - X -
Kentucky - - - X - - X X -
Louisiana - - - - - - X - -
Maine - - - X - - X - -
Maryland - - - - - - - - -
Massachusetts - X X X X - X X -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Michigan - - - X X - - X X
Minnesota - - - - - - X X -
Mississippi - - - X - - - - -
Missouri - - - - - - - - X
Montana X - - - - - - - X
Nebraska
Nevada - - - - - - X - -
New Hampshire - - - - X - - - X
New Jersey - - - - - - - - -
New Mexico - - X - - - X X -
New York - - - X - - - - X
North Carolina - - - X X - - - -
North Dakota - - - - - - - - X
Ohio - - - - - - - - -
Oklahoma - - - - - - - - X
Oregon - - X - X - X - -
Pennsylvania - - - X - - - - -
Rhode Island - - - X X - - - -
South Carolina - - - X X - - - -
South Dakota - - - X - - - - X
Tennessee - X - - - - X X -
Texas - - - - - - - - -
Utah - - - - X - - - -
Vermont - - - - - - - - X
Virginia - - - - - - - - -
Washington - - - X - - - - -
West Virginia - - - - X - - - X
Wisconsin - - - - - - - - X
Wyoming - - - - - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Emergency Response

State DOT Lack of trust in lidar data quality Software compatibility Difficulties in obtaining similar results to traditional workflows Limited experience, training, and capabilities Insufficient IT infrastructure (data storage, network latency, software tools, etc.) Other methods provide higher ROI Effort required to extract information from lidar data Lidar data needs to be supplemented with additional data sources to meet project or reporting requirements Not Sure
Alabama - - - - - - - - -
Alaska - - - - X X - X -
Arizona
Arkansas - - - - - - - - -
California - - - - - - - - -
Colorado - - - X X - - - -
Connecticut - - - - - - - - X
Delaware
District of Columbia - - - - - - - - -
Florida - - - X X - - - -
Georgia
Hawaii - - - - - - - - -
Idaho - - - X - - X - X
Illinois - X - X X - - X -
Indiana - - - - X - - - -
Iowa - X - X X X X X -
Kansas - - - - - - - - X
Kentucky - - - X - X - X -
Louisiana - - - - - - - - -
Maine - - - X - - X - -
Maryland - - - - - - - - -
Massachusetts - X X X X - X X -
Michigan - - - X X - - X X
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Minnesota - - - - - - X X -
Mississippi - - - X - - - - -
Missouri - - - - - - - - X
Montana X - - - - - - - X
Nebraska
Nevada - - - - - - - - X
New Hampshire - - - - X - - - X
New Jersey - - - - - - - - -
New Mexico - - - - - - - - -
New York - - - X - - - - X
North Carolina - - - X X - - - -
North Dakota - - - - - - - - X
Ohio - - - - - - - - -
Oklahoma - - - - - - - - X
Oregon - - X - - - X - -
Pennsylvania - - - X - - - - -
Rhode Island - - - X X - - - -
South Carolina - - - X - - - - -
South Dakota - - - X - - - - X
Tennessee - - - X X - X X -
Texas - - - - - - - - -
Utah - - - - - - X - -
Vermont - - - - - - - - X
Virginia - - - - - - - - -
Washington - - - X - - - - -
West Virginia - - - - X - - - X
Wisconsin - - - - - - - - X
Wyoming - - - - - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT (Optional) Note other key challenges here not listed above.
Alabama The key challenge has been formatting the data for the average user.
California IT infrastructure used to be a huge issue, but we recently invested a lot in our storage and network capacity.
We have many staff who are trained in the extraction of LiDAR data but it is still slow going. We have been investigating AI/ML software to hopefully solve this issue but so far have not found anyone who has solved this issue for us.
Colorado Inadequate computer processing support, consultant deliverables, QA/QC of data collected perform incorrectly
Iowa Costly to acquire, process, and store
Kentucky Storage Costs
Ohio We have been using LiDAR at ODOT for 20 years, the only challenge we have is end users understanding where their data comes from.
Rhode Island Equipment and Personnel
South Carolina SCDOT cannot answer some of these challenges since Lidar is only incorporated in Survey/Mapping and Pavement Quality workflow processes on a regular basis. Design is using extracted features.
Wisconsin No challenges using for roadway and mapping projects. Unsure about the other groups challenges because I do not typically work with those areas.

Data Life Cycle (Collection, Processing, Storage, Retention)

  1. How often does your DOT collect network level lidar data for asset management?

The hexagon map shows the frequency of network-level Lidar data collection in asset management projects by United States state departments of transportation using nine fill patterns. A horizontal line pattern indicates states that collect data annually—Alaska, Indiana, Kentucky, West Virginia, the District of Columbia, California, and Tennessee—accounting for 13.7 percent, with a sample size N equal to 7. A loose diagonal crosshatch pattern marks states that collect data biannually (every 2 years)—North Dakota, Massachusetts, Oregon, Utah, Oklahoma, and Kansas—totaling 11.8 percent, with N equal to 6. A pattern of small circles indicates states that collect data only for specific projects—Texas, Mississippi, North Carolina, Virginia, New Jersey, New Hampshire, and Maine—totaling 13.7 percent, with N equal to 7. A pattern of diagonal lines marks states that have completed just one statewide collection of data—Wyoming and Alabama—totaling 3.9 percent, with N equal to 2. A crosshatch pattern marks states that do not collect network level Lidar data for asset management—South Dakota, Colorado, Florida, South Carolina, Pennsylvania, and Vermont—totaling 11.8 percent, with N equal to 6. A dotted pattern designates states that responded “other”—Washington, Idaho, Nevada, New Mexico, Minnesota, Wisconsin, Iowa, Illinois, Arkansas, Ohio, New York—accounting for 21.6 percent, with N equal to 11. A tight crosshatch pattern indicates states that responded “not sure”—Hawaii, Michigan, Missouri, Louisiana, Maryland, Connecticut, and Rhode Island—accounting for 13.7 percent, with a sample size N equal to 7. A tight diagonal crosshatch pattern designates the single state that did not respond to the question—Montana—totaling 2.0 percent, with N equal to 1. No fill pattern indicates states that reported no Lidar usage—Delaware, Nebraska, Georgia, and Arizona—totaling 7.8 percent, with N equal to 4. The legend defines each pattern with its usage frequency, percentage, and sample size, where N refers to the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Arkansas Collection has been done on a pilot project, but not statewide.
Illinois Our DOT collects uncontrolled road inventory data every 2 years for condition ratings and limited use in Planning & Maintenance and also collects specific controlled roadway project data as needed.
Iowa Only collected on structural vertical clearances
Minnesota 2nd statewide collect is being completed now. They are working toward an established frequency.
Nevada Multiple collections have been completed. Not sure how often.
New Mexico Survey/Geomatics Professionals are not involved in these projects.
New York We are just getting started with network level collection.
Ohio The team just invested into LiDAR and will be starting a collection cycle - traditional LiDAR for design mapping is project based.
Washington Data is currently only collected for specific projects. However, we’re piloting statewide/network level collection and feature extraction.
Wisconsin WisDOT currently does not do this but may in the near future.
  1. How does your DOT manage the retention of lidar data?

The hexagon map shows Lidar data retention practices in D O Ts using seven patterns with usage categories and sample sizes. A crosshatch pattern marks states that regularly purge older lidar data and retain only the most current—Michigan and Tennessee—accounting for 3.9 percent, with sample size N equal to 2. A diagonal pattern marks states that retain all historical lidar data indefinitely—North Dakota, Wisconsin, New York, Wyoming, Ohio, Connecticut, Utah, Colorado, Virginia, the District of Columbia, Maryland, Oklahoma, Arkansas, North Carolina, Louisiana, Alabama, Alaska, and Florida—accounting for 35.3 percent, with N equal to 18. A horizontal line pattern marks states that retain specific datasets based on project requirements—Vermont, South Dakota, Illinois, Pennsylvania, New Jersey, California, Nevada, New Mexico, and Texas—accounting for 21.6 percent, with N equal to 11. A dotted pattern marks states that responded “other”—Maine, Washington, Oregon, Iowa, Missouri, Kentucky, Kansas, South Carolina, and Mississippi—accounting for 17.6 percent, with N equal to 9. A tight crosshatch pattern marks states that responded that they were not sure—New Hampshire, Massachusetts, Rhode Island, Idaho, Indiana, and Hawaii—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch pattern marks Montana, the single state that did not respond response to this question, accounting for 2.0 percent. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Iowa Currently no standard or policy for retention.
Kansas We have only collected statewide data twice with mobile lidar. We do not have a full plan on how to store/retain.
Kentucky Regular retention schedule based on LiDAR and Project.
Maine We currently “retain indefinitely”, but plan on “sunsetting” datasets eventually.
Mississippi Recent data is retained on premise cloud storage (approx. 3 yrs.). Older data is moved to cold storage (hard drives/disk).
Montana Retention schedule being developed.
Oregon Retain data required by ORS data retention schedules. Currently retaining for 10 years.
South Carolina Survey Department stores point cloud data off network on flash drives.
Washington We currently retain all historic lidar data indefinitely but are also considering the requirements and impacts of network level data.
  1. How does your agency primarily store and access lidar data?

A hexagon map shows utilization of stand-alone desktop computers as Lidar data storage in D O Ts using five patterns with categories and sample sizes. A tight horizontal line pattern marks states that reported never using stand-alone desktop computers as Lidar data storage—North Dakota, Minnesota, Wisconsin, Massachusetts, Oregon, South Dakota, Connecticut, Utah, Missouri, Kentucky, New Mexico, Oklahoma, Kansas, Louisiana, and Alabama—accounting for 29.4 percent, with sample size N equal to 15. An open horizontal line pattern marks states that reported stand-alone desktop computers as the primary storage system—Michigan, Illinois, and New Jersey—accounting for 5.9 percent, with N equal to 3. A diagonal line pattern marks states that reported some used of stand-alone desktop computers—New Hampshire, Alaska, Washington, New York, Idaho, Wyoming, Indiana, Pennsylvania, California, Nevada, Colorado, West Virginia, Virginia, Maryland, Tennessee, Texas, Mississippi, Hawaii, and Florida—accounting for 37.3 percent, with N equal to 19. A diagonal crosshatch pattern marks states that did not respond to this question—Maine, Vermont, Rhode Island, Montana, Iowa, Ohio, District of Columbia, Arkansas, North Carolina, and South Carolina—accounting 19.6 percent, with N equal to 10. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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A hexagon map shows utilization of on-premises network servers as Lidar data storage in D O Ts using five patterns with categories and sample sizes. A tight horizontal line pattern marks states that reported never using on-premises network servers—Kentucky, Kansas, and Texas—accounting for 5.9 percent, with sample size N equal to 3. A diagonal line pattern marks states that reported using on-premises network servers as the primary storage system—Maine, New Hampshire, Washington, North Dakota, Minnesota, Wisconsin, Oregon, Idaho, Wyoming, South Dakota, Pennsylvania, California, Colorado, Missouri, Maryland, Oklahoma, Arkansas, Tennessee, North Carolina, Mississippi, Alabama, and Florida—accounting for 43.2 percent, with N equal to 22. An open horizontal line pattern marks states that reported some usage of on-premises network servers—Alaska, Michigan, New York, Massachusetts, Iowa, Illinois, Indiana, Ohio, Connecticut, Nevada, Utah, West Virginia, Virginia, New Mexico, and Louisiana—accounting for 29.4 percent, with N equal to 15. A diagonal crosshatch pattern marks states that did not respond to this question—Vermont, Rhode Island, Montana, New Jersey, the District of Columbia, Hawaii, and South Carolina—accounting for 13.7 percent, with N equal to 7. No fill pattern marks Nebraska, Delaware, Arizona, and Georgia, represented as no lidar usage, accounting 7.8 percent, with N equal to 4. A hexagon map shows utilization of cloud-based solutions for Lidar data storage in D O Ts using five patterns with categories usage and sample sizes. A tight horizontal line pattern marks states that reported never using cloud-based solutions—New Hampshire, New York, South Dakota, Missouri, West Virginia, Maryland, Texas, and Mississippi—accounting for 15.7 percent, with sample size N equal to 8. An open horizontal line pattern marks states that reported using cloud-based solutions as the primary storage system—Alaska, Maine, Vermont, Washington, Idaho, Wyoming, Connecticut, Utah, Colorado, Kentucky, Virginia, the District of Columbia, Tennessee, Oklahoma, and Louisiana—accounting for 29.4 percent, with N equal to 15. A diagonal line pattern marks states that reported some use of cloud-based solutions—North Dakota, Minnesota, Wisconsin, Michigan, Oregon, Massachusetts, Illinois, Indiana, Ohio, California, Nevada, New Mexico, Kansas, Alabama, and Florida—accounting for 29.5 percent, with N equal to 15. A diagonal crosshatch pattern marks states that did not respond to this question—Montana, Rhode Island, Iowa, Pennsylvania, New Jersey, Arkansas, North Carolina, Hawaii, and South Carolina—accounting for 17.6 percent, with N equal to 9. A blank fill marks states that reported no Lidar usage—Nevada, Delaware, Arizona, and Georgia—accounting for 7.8 percent, with a N equal to 4.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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A hexagon map shows utilization of external drives as a Lidar data storage method in D O Ts by U S state using five distinct fill patterns. A tight horizontal line pattern marks states that reported never using external drives—Oregon, North Dakota, South Dakota, Minnesota, Wisconsin, New Mexico, Kansas, Missouri, Kentucky, and Maryland—accounting for 19.6 percent, with sample size N equal to 10. An open horizontal line pattern marks states that reported using external drives as the primary Lidar data storage system—Iowa, Illinois, Michigan, Maine, New Jersey, Connecticut, Colorado, Utah, Louisiana, Texas, South Carolina, and Vermont—accounting for 23.5 percent, with N equal to 12. A diagonal line pattern marks states that reported some use of external drives—Alabama, Alaska, Arkansas, Florida, Hawaii, California, Idaho, Nevada, Wyoming, Oklahoma, Tennessee, Mississippi, Indiana, West Virginia, Virginia, Pennsylvania, New York, Massachusetts, and New Hampshire—accounting for 37.3 percent, with N equal to 19. A diagonal crosshatch pattern marks states that did not respond to this question—Washington, Montana, Ohio, North Carolina, the District of Columbia, and Rhode Island—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by usage category, percentage, and sample size, where N is the number of states in each group. The hexagon map shows utilization of other technologies for Lidar data storage in D O Ts by U S state using four distinct fill patterns. A diagonal line pattern marks Idaho, the single state that reported using other technologies as the primary Lidar data storage system, accounting for 2.0 percent. A horizontal line pattern marks Missouri, the single state that reported some use of other technologies, accounting for 2.0 percent. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. A diagonal crosshatch pattern marks the remaining 45 states, which gave no response to this question, accounting for 88.2 percent. The legend defines each pattern by storage use category, percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Connecticut Newer datasets all on external cloud service
Hawaii Data is moved off once project is complete.
Idaho Hosted by consultants that collected the data
Missouri While processing on workstation
Washington Our network LiDAR data is stored in a cloud solution.

Data Mining:

  1. How does your DOT approach lidar data processing workflows to meet specific project requirements? (Select all that apply)
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State Using predominately commercial software without customization Developing in-house customized workflows Utilizing third-party software with customization options (e.g. scripting) Collaborating with external experts for customization Other (please specify) Not sure
Alabama X X X X X -
Alaska X X X X - -
Arizona
Arkansas X - - - - -
California X - - X - -
Colorado X - - - - -
Connecticut - - X - - -
Delaware
District of Columbia - X X - - -
Florida X - - - - -
Georgia
Hawaii X - - - - -
Idaho X - - X - -
Illinois X X - - - -
Indiana X - - - - -
Iowa - - - X - -
Kansas - - X X - -
Kentucky X - - X - -
Louisiana X - X X - -
Maine X X - X - -
Maryland X - - - - -
Massachusetts X - - - - -
Michigan X - - X - -
Minnesota X - - - - -
Mississippi X - - - - -
Missouri X - - - - -
Montana
Nevada X - - - - -
New Hampshire X - - - - -
New Jersey - - - - - -
New Mexico X - X - - -
New York X - - - - -
North Carolina - - X - - -
North Dakota X X X X - -
Ohio X - - - - -
Oklahoma X X X X - -
Oregon X - X - - -
Pennsylvania - X X - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Rhode Island - - - - X -
South Carolina X - - - - -
South Dakota - - - - X -
Tennessee X - - - - -
Texas X X - - - -
Utah X - - - - -
Vermont X - - - - -
Virginia X - X - - -
Washington - - X - - -
West Virginia - X X - - -
Wisconsin X X - - - -
Wyoming X - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Alabama Two contractors provide software with good response to software enhancements and updates.
Rhode Island Consultants
South Dakota All Processing of LiDAR data is done by consultants
  1. What strategies has your DOT implemented to enhance the efficiency of lidar data processing and analysis workflows?
State Utilizing parallel processing techniques Implementing automated data processing pipelines Investing in high-performance computing resources External entities to assist in data processing Utilizing artificial intelligence Other (please specify) Not sure
Alabama X X X X X - -
Alaska - X - X X - -
Arizona
Arkansas - - X - - - -
California - - X - - X -
Colorado - - X X - X -
Connecticut X - X X - - -
Delaware
District of Columbia - - X X X - -
Florida - - X X - - -
Georgia
Hawaii - - - - - - X
Idaho - - X X - X -
Illinois - - X X - - -
Indiana - - - X - - -
Iowa - - - X - - -
Kansas - - - X - X -
Kentucky - - X - - - -
Louisiana - X X X - -
Maine X X X X - - -
Maryland - - X - - - -
Massachusetts - - - X X - -
Michigan - - - - - - X
Minnesota - - X - - - -
Mississippi - - X - - - -
Missouri - - X - - - -
Montana - - X X - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Nebraska
Nevada - - X - - - -
New Hampshire - - - - - - X
New Jersey - - - - - - X
New Mexico - X - - - - -
New York - - X - - - -
North Carolina X X - - X - -
North Dakota X - X - X - -
Ohio X X X - - - -
Oklahoma - - - X - - -
Oregon - - X - - - -
Pennsylvania - X - - - - -
Rhode Island - - - - - X -
South Carolina - - - X - - -
South Dakota - - - - - X -
Tennessee - - - X - - -
Texas - - X X - - -
Utah - - - X - - -
Vermont - X X X - - -
Virginia - - - X - - -
Washington - X X - - X -
West Virginia - X X X X - -
Wisconsin - X - X - - -
Wyoming - - - - - - -
State DOT Other Text
California We have been investigating AI/ML solutions.
Colorado We use the Survey Manual.
Idaho Consultants process LiDAR data and produce traditional deliverables; sometimes using AI.
Kansas Currently we have a vendor collect and process the data.
Rhode Island Consultants
South Dakota All processing of LiDAR data is done by consultants.
Washington Investigating AI options and capabilities
Page 172
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Data Management and Governance Practices

  1. How does your DOT manage lidar data in terms of data access and user permissions?
State DOT Strict access controls User training on data handling Regular audits of data access Collaboration platforms Other (please specify) Not sure
Alabama X X - X X -
Alaska - X - X - -
Arizona
Arkansas X - - - - -
California X - - - X -
Colorado X - - - X -
Connecticut X - - - - -
Delaware
District of Columbia - - - X - -
Florida - - - X - -
Georgia
Hawaii - - - - - X
Idaho - - - - X -
Illinois X - - X - -
Indiana - - - X - -
Iowa - - - X - -
Kansas X X - - - -
Kentucky - - X X - -
Louisiana - - - - - X
Maine X X - - - -
Maryland X - - X - -
Massachusetts - - - - - X
Michigan X - - - - -
Minnesota - - - - X -
Mississippi - X - - - -
Missouri X - - - - -
Montana - - - X X X
Nebraska
Nevada - - - - - X
New Hampshire - X - - - -
New Jersey X - - - - -
New Mexico X - - - - -
New York X - - - - -
North Carolina - - - - X -
North Dakota - X - - - -
Ohio - X - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Oklahoma X - - - - -
Oregon X X - - - -
Pennsylvania - - - - - X
Rhode Island - - - - - X
South Carolina - - - - X -
South Dakota - - - - X -
Tennessee X - - - - -
Texas - X - - - -
Utah - X - - - -
Vermont X X - - - -
Virginia - X - - - -
Washington X - - - - -
West Virginia X X - X - -
Wisconsin X - - - - -
Wyoming X - - - - -
State DOT Other (please specify)
Alabama Strict access to source data. Data packages are delivered for users.
California LiDAR data access is controlled through our Active Directory allowing those with access rights to use the data. Those without rights have to request the data.
Colorado Determining data access goals.
Idaho LiDAR is available to internal users/partners in “read only” access or browser-based interfaces for download.
Minnesota No permissions needed. Internal access.
Montana Available on data storage system
North Carolina Lidar Data is on backed up Storage. Tools (scripts) are used for democratized access to the Lidar and derivatives.
South Carolina No controls or policy
South Dakota Secured Server grant permission to access
  1. How does your DOT handle data privacy concerns with lidar data?
State DOT Data masking Restricting access Not collecting data in sensitive areas No specific measures in place Independent audit Other (please specify) Not sure
Alabama - - - X - - -
Alaska X X X - - - -
Arizona
Arkansas - - X - - - -
California - X - - - - -
Colorado - X X - - - -
Connecticut X X - X - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Delaware
District of Columbia - X - - - - -
Florida - - X X - - -
Georgia
Hawaii - - - - - - X
Idaho - - - X - - -
Illinois - X - - - - -
Indiana - - X - - - -
Iowa - - - X - - -
Kansas - X - - - X -
Kentucky - - - X - X -
Louisiana - - - - - - X
Maine - X - - - - -
Maryland - - - - - - X
Massachusetts - - - - - - X
Michigan - - - - - - X
Minnesota - - - X - - -
Mississippi - - X - - - -
Missouri - X - - - - -
Montana - X - X - - X
Nebraska
Nevada - - - - - - X
New Hampshire - - - X - - -
New Jersey - X - - - - -
New Mexico - X - - - - -
New York - - - X - - -
North Carolina - - - - - X -
North Dakota - - X X - - -
Ohio - - - X - - -
Oklahoma - - - X - - -
Oregon - - X X - - -
Pennsylvania - - - X - - -
Rhode Island - - - - - - X
South Carolina - - - X - - -
South Dakota - X - - - - -
Tennessee - - - X - X X
Texas - - - X - - -
Utah X - X - - - -
Vermont - - - - - - X
Virginia - X - - - - -
Washington - X - - - - -
West Virginia - - X - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Wisconsin - X - - - X -
Wyoming - - - X - - -
State DOT Other Text
Kansas In user licensing agreement
Kentucky This is considered public information.
North Carolina Coordination with sensitive areas for their requirement on what can be accessed
Tennessee Third party vendor may use specific data privacy measures but I’m not familiar with their practices.
Wisconsin Only the photogrammetry unit has access to project specific lidar data, as other groups would not know how to process the data. County lidar datasets are controlled by the photogrammetry unit as well, but other groups may access as needed, although the photo. unit takes care of all requests for data.
  1. What steps does your DOT take to enhance the accessibility of lidar data for diverse user groups?
State DOT User-friendly interfaces for data access or processing Providing data in multiple formats Conducting outreach and training programs No efforts in place Other (please specify) Not sure
Alabama X X X - X -
Alaska X X X - - -
Arizona
Arkansas - - - - X -
California X X - - - -
Colorado - X - X - -
Connecticut - X - X - -
Delaware
District of Columbia X X - - - -
Florida - - - X - -
Georgia
Hawaii - - - - - X
Idaho X X X - - -
Illinois - - X - - -
Indiana X - - - - -
Iowa - - - X - -
Kansas X X X - - -
Kentucky X - X - - -
Louisiana - - X - - -
Maine - - - X - -
Maryland - - - - X -
Massachusetts - - - - - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Michigan - - - - - X
Minnesota - - - X - -
Mississippi - - - - - -
Missouri - X - - - -
Montana X - - X - -
Nebraska
Nevada X X - - - -
New Hampshire - - - X - -
New Jersey - - - - - X
New Mexico X - - - - -
New York - - - X X -
North Carolina X X X - - -
North Dakota - - - X - -
Ohio - - - X - -
Oklahoma - - - X - -
Oregon - X X - - -
Pennsylvania - - - X - -
Rhode Island - - - - - X
South Carolina - - - X - -
South Dakota - - - X - -
Tennessee X X X - X -
Texas - - X - - -
Utah X - X - - -
Vermont - - - X - -
Virginia - - X - - -
Washington X X X - - -
West Virginia - X - - - -
Wisconsin - - - X - -
Wyoming X - - - - -
State DOT Other - Text
Alabama Recent asset management collection provided through vendor web interface
Arkansas Data is provided in industry standard .las or .laz format.
Maryland Provided to groups when requested
New York We will be sharing statewide Mobile LiDAR data within the agency on a free web viewer.
Tennessee Vendor provides lidar extracted surface layer behind 360 degree imagery and also provides option to download point cloud data from their server.
  1. To what extent does your DOT share/utilize lidar data with the following departments or external entities?
Page 177
Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and local municipalities using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data with local municipalities—Vermont, Minnesota, Wisconsin, New York, Wyoming, South Dakota, Iowa, and Indiana—accounting 15.7 percent, with a sample size N equal to 8. An open horizontal line pattern marks states that reported sharing Lidar data rarely or upon request—Maine, New Hampshire, Washington, North Dakota, Massachusetts, Oregon, Idaho, Illinois, Ohio, Pennsylvania, New Jersey, Connecticut, California, Nevada, Utah, Colorado, Missouri, West Virginia, Virginia, Maryland, New Mexico, Oklahoma, Kansas, Arkansas, South Carolina, Texas, Louisiana, Florida, and Mississippi—accounting 56.8 percent, with N equal to 29. A diagonal line pattern marks Alabama, the single state that reported regularly sharing Lidar data, accounting for 2 percent. A dotted pattern marks states that reported routinely sharing Lidar data—Alaska, Kentucky, and Tennessee—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to this question—Montana, Michigan, Rhode Island, the District of Columbia, North Carolina, and Hawaii—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and planning departments using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Vermont, Wyoming, and Iowa—accounting for 7.8 percent, with a sample size N equal to 4. A diagonal line pattern marks states that reported sharing data rarely or upon request—Maine, New Hampshire, North Dakota, Minnesota, Wisconsin, New York, Massachusetts, Indiana, Pennsylvania, New Jersey, Connecticut, Colorado, Missouri, West Virginia, Virginia, New Mexico, Kansas, South Carolina, Texas, Louisiana, Alabama, and Florida—accounting for 43.2 percent, with N equal to 22. An open horizontal line pattern marks states that reported sharing data regularly—Washington, Idaho, South Dakota, Illinois, Ohio, California, Utah, Maryland, and Arkansas—accounting for 17.6 percent, with N equal to 9. A dotted pattern marks states that reported sharing data routinely—Alaska, Oregon, Nevada, Kentucky, Tennessee, and Mississippi—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, Michigan, Rhode Island, the District of Columbia, and North Carolina—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and environmental departments using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Vermont, Minnesota, Iowa, Illinois, Indiana, and Oklahoma—accounting for 11.8 percent, with sample size N equal to 6. An open horizontal line pattern marks states that reported sharing data rarely or upon request—Maine, New Hampshire, Wisconsin, New York, Massachusetts, South Dakota, Pennsylvania, New Jersey, Connecticut, Nevada, Colorado, West Virginia, Virginia, New Mexico, Kansas, South Carolina, Texas, Louisiana, Mississippi, and Florida—accounting for 39.2 percent, with N equal to 20. A diagonal line pattern marks states that reported sharing data regularly—Alabama, Washington, North Dakota, Oregon, Idaho, Wyoming, Ohio, California, Utah, Maryland, and Arkansas—accounting for 21.6 percent, with N equal to 11. A dotted pattern marks states that reported sharing data routinely—Alaska, Missouri, Kentucky, the District of Columbia, and Tennessee—accounting for 9.8 percent, with N equal to 5. A diagonal crosshatch pattern marks states that did not respond to this question—Montana, Michigan, Rhode Island, and North Carolina—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and urban developments using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Vermont, Minnesota, Wisconsin, South Dakota, Iowa, Illinois, Indiana, Ohio, Connecticut, and California—accounting for 19.6 percent, with sample size N equal to 10. A diagonal line pattern marks states that reported sharing data rarely or upon request—Maine, New Hampshire, New York, Massachusetts, Washington, Oregon, Idaho, Pennsylvania, New Jersey, Nevada, Colorado, Missouri, West Virginia, Virginia, Maryland, New Mexico, Kansas, Arkansas, South Carolina, Texas, Louisiana, Mississippi, Alabama, and Florida—accounting for 47.2 percent, with a sample size N equal to 24. An open horizontal line pattern marks states that reported sharing data regularly—Alaska, North Dakota, Wyoming, and Utah—accounting for 7.8 percent, with N equal to 4. A dotted pattern marks states that reported sharing data routinely—Kentucky, the District of Columbia, Oklahoma, and Tennessee—accounting for 7.8 percent, with N equal to 4. A diagonal crosshatch pattern marks states that gave no response to this question—Montana, Michigan, Rhode Island, Hawaii, and North Carolina—accounting for 9.8 percent, with a sample size N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of lidar data between D O Ts and bridge or structures departments using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—New Hampshire, Minnesota, and Iowa—accounting for 5.9 percent, with sample size N equal to 3. A diagonal line pattern marks states that reported sharing data rarely or upon request—Wisconsin, New York, Idaho, South Dakota, Illinois, Indiana, Ohio, Pennsylvania, New Jersey, Connecticut, Nevada, Colorado, Kentucky, West Virginia, New Mexico, South Carolina, Texas, Louisiana, Mississippi, Alabama, and Florida—accounting for 41.2 percent, with N equal to 21. An open horizontal line pattern marks states that reported sharing data regularly—Maine, Vermont, Washington, North Dakota, Massachusetts, Oregon, Wyoming, California, Utah, Virginia, Kansas, and Arkansas—accounting for 23.5 percent, with N equal to 12. A dotted pattern marks states that reported sharing data routinely—Alaska, Missouri, the District of Columbia, Maryland, Oklahoma, and Tennessee—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch pattern marks states that gave no response to this question—Montana, Michigan, Rhode Island, North Carolina, and Hawaii—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and geotechnical departments using six distinct fill patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Minnesota, South Carolina, Oklahoma, South Dakota, and Iowa—accounting for 9.8 percent, with sample size N equal to 5. An open horizontal line pattern marks states that reported sharing data rarely or upon request—Florida, Idaho, Nevada, Utah, Colorado, New Mexico, Texas, Kansas, Louisiana, Illinois, Indiana, Wisconsin, Pennsylvania, Connecticut, New Jersey, Maryland, Mississippi, Massachusetts, New Hampshire, Virginia, West Virginia, and Maine—accounting for 43.2 percent, with N equal to 22. A diagonal line pattern marks states that reported sharing data regularly—Alabama, Arkansas, California, New York, North Dakota, Ohio, Oregon, Vermont, Washington, and Wyoming—accounting for 19.6 percent, with N equal to 10. A dotted fill pattern marks states that reported sharing data routinely—Alaska, the District of Columbia, Missouri, and Tennessee—accounting for 7.8 percent, with N equal to 4. A crosshatch pattern marks states that gave no response to this question—Hawaii, Michigan, Montana, Kentucky, North Carolina, and Rhode Island—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and asset management departments by U S state using six distinct fill patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—North Dakota, Iowa, Oklahoma, Vermont, and Wyoming—accounting for 9.8 percent, with sample size N equal to 5. An open horizontal line pattern marks states that reported sharing data rarely or upon request—Colorado, New Mexico, Texas, Wisconsin, Illinois, Indiana, Kentucky, Louisiana, Mississippi, Florida, South Dakota, South Carolina, Virginia, West Virginia, Pennsylvania, Missouri, Massachusetts, Maryland, Connecticut, Maine, and New Hampshire—accounting for 41.2 percent, with N equal to 21. A diagonal line pattern marks states that reported sharing data regularly—Arkansas, California, Minnesota, Kansas, Oregon, Utah, and Washington—accounting for 13.7 percent, with N equal to 7. A dotted fill pattern marks states that reported sharing data routinely—Alaska, Alabama, the District of Columbia, Idaho, New York, Nevada, Ohio, and Tennessee—accounting for 15.7 percent, with N equal to 8. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Michigan, Montana, New Jersey, Rhode Island, and North Carolina—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and hydrological departments by U S state using six distinct fill patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Indiana, Iowa, Minnesota, New Hampshire, Oklahoma, South Dakota, and Wyoming—accounting for 13.7 percent, with sample size N equal to 7. An open horizontal line pattern marks states that reported sharing data rarely or upon request—Colorado, Connecticut, Florida, Idaho, Kansas, Kentucky, Louisiana, Maryland, Massachusetts, Mississippi, New Mexico, Ohio, Pennsylvania, Oregon, South Carolina, Texas, Utah, Vermont, West Virginia, and Wisconsin—accounting for 39.3 percent, with N equal to 20. A diagonal line pattern marks states that reported sharing data regularly—California, Nevada, Illinois, Maine, North Dakota, Virginia, and Washington—accounting for 13.7 percent, with N equal to 7. A dotted pattern marks states that reported sharing data routinely—Alaska, Alabama, Arkansas, New York, Missouri, and Tennessee—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Montana, New Jersey, Rhode Island, the District of Columbia, North Carolina, and Michigan—accounting for 13.7 percent, with N equal to 7. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and survey or G I S [geographic information system] departments by U S states, using six distinct fill patterns. A tight horizontal line pattern marks Iowa, the single state that reported never sharing or using Lidar data, accounting for 2.0 percent. A diagonal line pattern marks states that reported sharing data rarely or upon request—Colorado, Louisiana, Mississippi, and Pennsylvania—accounting for 7.8 percent, with sample size N equal to 4. An open horizontal line pattern marks states that reported sharing data regularly—Connecticut, Indiana, New Jersey, Kansas, Massachusetts, Minnesota, New Mexico, South Carolina, Utah, Virginia, and Washington—accounting for 21.6 percent, with N equal to 11. A dotted pattern marks states that reported sharing data routinely—Alaska, Alabama, Arkansas, California, the District of Columbia, Florida, Idaho, Illinois, Kentucky, Maine, Maryland, Missouri, Nevada, New Hampshire, New York, Oklahoma, Oregon, Ohio, North Dakota, South Dakota, Tennessee, Texas, Vermont, West Virginia, Wyoming, and Wisconsin—accounting for 51.0 percent, with N equal to 26. A diagonal crosshatch pattern marks states that gave no response to this question—Hawaii, Michigan, Montana, North Carolina, and Rhode Island—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and external consultants by U S state, using six distinct fill patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Iowa, Indiana, and Wyoming—accounting for 5.9 percent, with sample size N equal to 3. A diagonal line pattern marks states that reported sharing data rarely or upon request—Alabama, California, Colorado, Mississippi, Minnesota, New Hampshire, New Mexico, New York, Pennsylvania, Texas, Nevada, Virginia, Vermont, and West Virginia—accounting for 27.5 percent, with N equal to 14. An open horizontal line pattern marks states that reported sharing data regularly—Connecticut, Idaho, Illinois, Louisiana, Kansas, New Jersey, Maryland, Massachusetts, Maine, North Dakota, Oklahoma, Ohio, Oregon, South Carolina, South Dakota, Utah, Wisconsin, and Washington—accounting for 35.2 percent, with N equal to 18. A dotted fill pattern marks states that reported sharing data routinely—Alaska, Arkansas, Florida, Missouri, Kentucky, and Tennessee—accounting for 11.8 percent, with N equal to 6. A diagonal crosshatch pattern marks states that gave no response to this question—the District of Columbia, Hawaii, Michigan, Montana, North Carolina, and Rhode Island—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and academic research institutions, using six patterns. A tight horizontal line pattern marks states that reported never sharing Lidar data—Wyoming, South Dakota, Minnesota, Wisconsin, Oklahoma, Indiana, West Virginia, South Carolina, New York, and Vermont—accounting for 19.6 percent, with sample size N equal to 10. A diagonal line pattern marks states that reported sharing data rarely or upon request—California, Oregon, Washington, Nevada, Idaho, North Dakota, New Mexico, Colorado, Texas, Iowa, Missouri, Kansas, Arkansas, Louisiana, Mississippi, Alabama, Florida, Virginia, Ohio, Pennsylvania, New Jersey, Maryland, Connecticut, New Hampshire, and Maine—accounting for 49.1 percent, with N equal to 25. An open horizontal line pattern marks states that reported sharing data regularly—Utah and Massachusetts—accounting for 3.9 percent, with N equal to 2. A dotted pattern marks states that reported sharing data routinely—Alaska, Illinois, Kentucky, Tennessee, and the District of Columbia—accounting for 9.8 percent, with N equal to 5. A diagonal crosshatch pattern marks states that gave no response to this question—Montana, Michigan, Hawaii, North Carolina, and Rhode Island—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map shows the frequency of sharing and utilization of Lidar data between D O Ts and other departments using four patterns. A diagonal line pattern marks Hawaii, the single state that report sharing data rarely or upon request, accounting for 2 percent. A dotted pattern marks states that reported sharing data routinely—Wisconsin, Tennessee, and North Carolina—accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. A diagonal crosshatch pattern marks the remaining 43 states, which gave no response to the question, accounting for 84.3 percent. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Colorado Typically share photogrammetry not LiDAR
Hawaii On a project-by-project need
North Carolina NCDOT considers their LiDAR data public data. NCDOT focus is on sharing with all NCDOT. Another state agency focuses on sharing with the public.
Rhode Island Consultants
Tennessee We make the 3DEP lidar available for free download.
Wisconsin Design/Construction

Quality assurance practices

  1. Approximately what level of accuracy does your DOT expect or require from each lidar platform?

The hexagon map displays how departments of transportation reported expected accuracy standards for airborne Lidar platforms using seven patterns. An open diagonal crosshatch pattern marks states with accuracy standards to the centimeter (0.05 feet)—Utah, Texas, North Dakota, Wisconsin, Missouri, Kentucky, West Virginia, North Carolina, South Carolina, Ohio, Pennsylvania, and Maryland—accounting for 23.5 percent, with sample size N equal to 12. A diagonal line pattern marks states with accuracy standards to the decimeter (0.5 feet)—Washington, Oregon, Nevada, Idaho, Wyoming, South Dakota, New Mexico, Oklahoma, Kansas, Arkansas, Louisiana, Illinois, Indiana, Virginia, Alabama, Florida, New York, Connecticut, and Maine—accounting for 37.3 percent, with N equal to 19. A horizontal line pattern marks California, the single state with accuracy standards to the meter (5 feet), accounting for 2 percent. An open crosshatch pattern marks the District of Columbia, the single state with accuracy standards to several meters (more than 10 feet), accounting for 2 percent. A tight crosshatch pattern marks states that responded that they were not sure—Alaska, Hawaii, Colorado, Iowa, Tennessee, New Jersey, Hew Hampshire, Massachusetts, and Vermont—accounting for 17.6 percent, with N equal to 9. A tight diagonal crosshatch pattern marks states that did not respond to the question—Minnesota, Michigan, Montana, Mississippi, and Rhode Island—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map displays how departments of transportation reported expected accuracy standards for helicopter-based Lidar platforms using five patterns. A diagonal line pattern marks states with accuracy standards to the centimeter (0.05 feet)—Texas, Wisconsin, Missouri, Kentucky, Arkansas, West Virginia, Ohio, Florida, South Carolina, Alabama, and Maryland—accounting for 21.6 percent, with N equal to 11. A horizontal line pattern marks states with accuracy standards to the decimeter (0.5 feet)—Washington, Oregon, California, New Mexico, Oklahoma, Illinois, and Maine, reporting decimeter-equals 0.5 feet, accounting for 13.7 percent, with N equal to 7. A tight crosshatch pattern marks states that responded that they were not sure—Alaska, Hawaii, Nevada, Idaho, Utah, Colorado, North Dakota, South Dakota, Iowa, Kansas, Louisiana, Tennessee, Indiana, Virginia, Pennsylvania, New Jersey, New York, Connecticut, Massachusetts, Vermont, and New Hampshire—accounting for 41.2 percent, with N equal to 21. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, Wyoming, Minnesota, Mississippi, Michigan, the District of Columbia, Rhode Island, and North Carolina—accounting for 15.7 percent, with N equal to 8. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays how departments of transportation reported expected accuracy standards for terrestrial tripod Lidar platforms using six patterns. A horizontal line pattern marks states with accuracy standards to the centimeter (0.05 feet)—California, Oregon, Idaho, Wyoming, New Mexico, Colorado, South Dakota, North Dakota, Minnesota, Wisconsin, Illinois, Missouri, Kansas, Arkansas, Kentucky, Indiana, Michigan, North Carolina, South Carolina, Virginia, Maryland, Vermont, and Maine—accounting for 45.1 percent, with sample size N equal to 23. A crosshatch pattern marks Oklahoma, the single state with accuracy standards to the decimeter (0.5 feet), accounting for 2.0 percent. A diagonal line pattern marks states with accuracy standards to the millimeter (0.005 feet)—Alaska, Hawaii, Washington, Nevada, Utah, Texas, Louisiana, Alabama, Florida, West Virginia, Ohio, Pennsylvania, New York, and Connecticut—accounting for 27.5 percent, with N equal to 14. A tight crosshatch pattern marks states that responded that they were not sure—Iowa, Tennessee, New Jersey, New Hampshire, and Massachusetts—accounting for 9.8 percent, with N equal to 5. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, Mississippi, the District of Columbia, and Rhode Island—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays how departments of transportation reported expected accuracy standards for vehicle-mounted mobile Lidar platforms using seven patterns. A diagonal stripe pattern marks states with accuracy standards to the centimeter (0.05 feet)—California, Nevada, Oregon, Idaho, Utah, Wyoming, North Dakota, South Dakota, Colorado, New Mexico, Texas, Iowa, Wisconsin, Illinois, Missouri, Kansas, Louisiana, Arkansas, Kentucky, Michigan, Ohio, West Virginia, Tennessee, Alabama, Florida, North Carolina, South Carolina, Virginia, Pennsylvania, New York, Connecticut, Maine, and Maryland—accounting for 64.7 percent, with sample size N equal to 33. An open crosshatch pattern marks Oklahoma, the single state with accuracy standards to the decimeter (0.5 feet), accounting for 2.0 percent. A horizontal line pattern marks Minnesota, the single state with accuracy standards to the meter (5 feet), also accounting for 2.0 percent. An open diagonal crosshatch pattern marks Washington, the single state with accuracy standards to the millimeter (0.005 feet), also accounting for 2.0 percent. A tight crosshatch pattern marks states that responded that they were not sure—Alaska, Hawaii, Indiana, New Jersey, Massachusetts, Vermont, and New Hampshire—accounting for 13.7 percent, with N equal to 7. A tight diagonal crosshatch pattern marks states that did not respond to the question—Montana, Mississippi, the District of Columbia, and Rhode Island—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map displays how departments of transportation reportrd expected accuracy standards for U A S-mounted Lidar platforms using six patterns. A diagonal line pattern marks states with accuracy standards to the centimeter (0.05 feet)—Alaska, California, Utah, Colorado, New Mexico, Texas, North Dakota, South Dakota, Kansas, Louisiana, Arkansas, Kentucky, Indiana, Michigan, West Virginia, North Carolina, South Carolina, Virginia, Pennsylvania, Maryland, Connecticut, and New Hampshire—accounting for 43.2 percent, with sample size N equal to 22. An open crosshatch pattern marks states with accuracy standards to the decimeter (0.5 feet)—Washington, Oregon, Idaho, Nevada, Oklahoma, Missouri, Illinois, Ohio, Florida, and Maine—accounting for 19.6 percent, with N equal to 10. A horizontal line pattern marks the District of Columbia, the single state with accuracy standards to the meter (5 feet), accounting for 2 percent. A tight crosshatch pattern marks states that responded that they were not sure—Iowa, Wisconsin, Tennessee, Alabama, Hawaii, Vermont, New York, New Jersey, and Massachusetts—accounting for 17.6 percent, with N equal to 9. A tight diagonal crosshatch pattern marks states that did not respond to the question—Montana, Minnesota, Wyoming, Mississippi, and Rhode Island—accounting for 9.8 percent, with N equal to 5. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays how departments of transportation reported expected accuracy standards for pocket Lidar platforms using seven patterns. A diagonal line pattern marks states with accuracy standards to the centimeter (0.05 feet)—Alaska, Pennsylvania, Virginia, and Texas—accounting for 7.8 percent, with sample size N equal to 4. A horizontal line pattern marks states with accuracy standards to the decimeter (0.5 feet)—Utah, Ohio, and Connecticut—accounting for 5.9 percent, with N equal to 3. An open crosshatch pattern marks states with accuracy standards to the meter (5 feet)—New Mexico and Florida—accounting for 3.9 percent, with N equal to 2. An open diagonal crosshatch pattern marks states with accuracy standards to several meters (more than 10 feet)—North Dakota and Illinois—also accounting for 3.9 percent, with N equal to 2. A tight crosshatch pattern marks states that responded that they were not sure—Washington, California, Nevada, Oregon, Idaho, South Dakota, South Carolina, Alabama, Kansas, Oklahoma, Missouri, Iowa, Wisconsin, Colorado, Indiana, Kentucky, Tennessee, West Virginia, Hawaii, Louisiana, New Jersey, New York, Vermont, New Hampshire, Massachusetts, and Maine—accounting for 51.1 percent, with N equal to 26. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, Michigan, Minnesota, Wyoming, Mississippi, Arkansas, North Carolina, District of Columbia, Maryland, and Rhode Island—accounting for 19.6 percent, with N equal to 10. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays how departments of transportation reported expected accuracy standards for other Lidar systems using four fill patterns. A diagonal line pattern marks Idaho, the single state with accuracy standards to the centimeter (0.05 feet), accounting for 2.0 percent. A tight crosshatch pattern marks states that responded that they were not sure—Hawaii, Nevada, Wisconsin, Iowa, New Jersey, and Massachusetts—accounting for 11.8 percent, with N equal to 6. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. A diagonal crosshatch pattern marks the remaining 40 states, which did not respond to the question, accounting for 78.4 percent. The legend defines each pattern with its expected accuracy reporting category, percentage, and sample size, where N refers to the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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State DOT Other Text
Hawaii To Survey grade
Idaho Salt Shed inventory
South Carolina Aerial (Airborne, Helicopter, UAS) RMSEz = 0.10’, Mobile/Terrestrial RMSEz = 0.05’ or 0.025’. See SCDOT survey manual at scdot.org/business/preconstruction surveys.
Wisconsin Airborne (both fixed wing and aerial) WisDOT requires 0.1ft or less. Mobile WisDOT requires 0.08’ or less. UAS we have only done pilot projects and do not have a specific accuracy requirement.
  1. How does your DOT typically ensure the accuracy of your lidar data?
State DOT In-house validation protocols Third-party validation Utilizing tools in manufacturer’s software Following industry standards such as ASPRS, ASTM, and others Not sure
Alabama X - X X -
Alaska X - X X -
Arizona
Arkansas X - - X -
California X - X - -
Colorado X - - X -
Connecticut X X - - -
Delaware
District of Columbia - - - X -
Florida - - X X -
Georgia
Hawaii - - X - -
Idaho X X - X -
Illinois X X X X -
Indiana X - X - -
Iowa X - - - -
Kansas X - - - -
Kentucky X - - - -
Louisiana X X X X -
Maine X X X X -
Maryland X - X X -
Massachusetts - - - - X
Michigan - - - X -
Minnesota - - X - -
Mississippi - - - - -
Missouri X - - - -
Montana X - - X -
Nebraska
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Nevada X - - - -
New Hampshire - - X - -
New Jersey - - X X -
New Mexico X - - - -
New York X - - - -
North Dakota X - X X -
North Carolina X - - X -
Ohio X - - - -
Oklahoma X - X - -
Oregon X - X - -
Pennsylvania - - - X -
Rhode Island - - - - X
South Carolina X - X X -
South Dakota - X - - -
Tennessee - - - X -
Texas X X - X -
Utah X X - - -
Vermont X - - - -
Virginia - - X X -
Washington X X X X -
West Virginia X X X - -
Wisconsin X - X X -
Wyoming X - - - -
  1. How does your DOT typically manage and maintain lidar data documentation and metadata?
State DOT Automated documentation processes Standardized metadata templates Periodic manual updates Detailed reports Document data requirements and data standards Links to data standards from each entity No metadata are tracked. Other (please specify) Not sure
Alabama - - - - - - - X -
Alaska X X - X X X - - -
Arizona
Arkansas X X X - - - - - -
California - - X X X - - - -
Colorado - - X - X - - - -
Connecticut X - X X - - - - -
Delaware
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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District of Columbia - - - - - - X - -
Florida - X - X - - - - -
Georgia
Hawaii - - - - - - - - X
Idaho - - - X - - X - -
Illinois - X - - X - - - -
Indiana X - - - - - - - -
Iowa - - - - - - X - -
Kansas - X - - - - - - -
Kentucky - - - - - - X - -
Louisiana - - - X - - - - -
Maine - X - - X - - - -
Maryland - - X X X - - - -
Massachusetts - - - - - - X - -
Michigan - - - - - - - - X
Minnesota - - - - - - X - -
Mississippi - - - - - - - - -
Missouri - - - X X - - - -
Montana - X X - - - - - X
Nebraska
Nevada - X - - - - - - -
New Hampshire - - - - - - - - -
New Jersey - - - - - - - - X
New Mexico - - - X X - - - -
New York - - X - X - - - -
North Carolina - - - - - - - X -
North Dakota - - - X - - X - -
Ohio - - - X X - - - -
Oklahoma - - - - X - - - -
Oregon - - - X X - - - -
Pennsylvania - X - X - - - - -
Rhode Island - - - - - - - X X
South Carolina - - - X X - - - -
South Dakota - - - - - - X - -
Tennessee - - - - - - - X -
Texas - - - X X - - - -
Utah - - X - - - - - -
Vermont - - X X - - - - -
Virginia - - - - - X - - -
Washington - - - - X - - X -
West Virginia - X X X - - - - -
Wisconsin - - - X X - - - -
Wyoming - - X - - - - - -
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State DOT Other Text
Alabama Varies depending on what type LIDAR maintained
North Carolina Reliance on the header of the .las file
Rhode Island Consultants
Tennessee Third party vendor maintains documentation and metadata
Washington Currently exploring methods with network collection
  1. What were the methods used to establish data requirements?

The hexagon map displays the methods state departments of transportation used to establish Lidar data requirements, using six patterns. A horizontal line pattern marks states that indicated the use of agency-wide data standards—North Dakota, Nevada, Texas, Oklahoma, Kansas, Arkansas, Tennessee, Missouri, Kentucky, West Virginia, Florida, the District of Columbia, New Hampshire, Maine, and Michigan—accounting for 29.4 percent, with sample size N equal to 15. A crosshatch pattern marks states that follow business unit or office-specific data standards—Oregon, Idaho, Wyoming, Utah, New Mexico, Minnesota, Wisconsin, Indiana, Illinois, Iowa, Ohio, Virginia, Maryland, Pennsylvania, New Jersey, New York, Vermont, and Massachusetts—accounting for 35.4 percent, with N equal to 18. A diagonal line pattern marks states that reported the use of statewide data standards—Alaska, California, South Dakota, Louisiana, and North Carolina—accounting for 9.8 percent, with N equal to 5. An dotted pattern marks states that chose the response “Other—Hawaii, Washington, Colorado, Alabama, South Carolina, Connecticut, and Rhode Island—accounting for 13.7 percent, with N equal to 7. A diagonal crosshatch pattern marks states that did not respond to the question—Mississippi and Montana—accounting for 3.9 percent, with N equal to 2. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Alabama Airborne - USGS. Mobile - varies
Colorado Statewide standards in progress
Connecticut Working on updating agency standards
Hawaii Project by project
Rhode Island Consultants
South Carolina National Standards used for accuracy
Washington National standards for airborne and static. Agency-wide standards for Enterprise Mobile LiDAR to support design requirements and exceed national standards

DOT Policies and Standards

  1. What role do standards play in your DOT’s lidar data practices?
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The hexagon map displays the role of standards in D O Ts’ Lidar data practices using seven patterns. An open diagonal crosshatch pattern marks states that reported ad hoc procedures in place—Idaho, Iowa, Minnesota, New Hampshire, Connecticut, Vermont, and Massachusetts—accounting for 13.7 percent, with sample size N equal to 7. A diagonal line pattern marks states that adhere to national standards such as T R B Mobile Lidar guidelines, A S P R S, and A S T M—Alaska, Tennessee, Alabama, North Carolina, South Carolina, Virginia, Pennsylvania, New Jersey, and Maine—accounting for 19.6 percent, with N equal to 9. A horizontal line pattern marks states that reported using a combination of internal and national standards—Washington, Oregon, Nevada, Utah, New Mexico, Texas, Colorado, North Dakota, Kansas, Arkansas, Louisiana, Kentucky, Illinois, Wisconsin, Indiana, Michigan, Ohio, Florida, and the District of Columbia—accounting for 37.4 percent, with N equal to 19. An open crosshatch pattern marks states that indicated the development of internal standards—California, Wyoming, Oklahoma, Missouri, West Virginia, Maryland, and New York—accounting for 13.7 percent, with N equal to 7. An dotted pattern marks states that selected the response “Other”—Hawaii, and Rhode Island—accounting for 3.9 percent, with N equal to 2. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, South Dakota, and Mississippi—accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

State DOT Other Text
Hawaii Project by project
Rhode Island Consultants

The following files were shared with the research team by respondents.

State DOT Resource Link
California Chapter 15 Survey Manual (2018) https://dot.ca.gov/programs/right-of-way/surveys-manual-and-interim-guidelines
Colorado Chapter 4 Aerial Surveys 2021 https://www.codot.gov/business/manuals/survey
Illinois Survey Manual https://idot.illinois.gov/content/dam/soi/en/web/idot/documents/doing-business/manuals-guides-and-handbooks/highways/design-and-environment/survey-manual.pdf
Kansas Lidar Project Home Page https://www.ksdot.gov/bureaus/burTransPlan/Lidar/home.asp
Ohio Surveying and Mapping Specifications https://www.transportation.ohio.gov/working/engineering/cadd-mapping/survey-mapping-specs
South Carolina Preconstruction Survey Manual (2023)
Texas Surveyor Toolkit https://www.txdot.gov/business/resources/surveyor-toolkit.html
Vermont Lidar operations manual
Wisconsin Best Uses for Static and Mobile Lidar (2023)
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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  1. What methods do personnel in your DOT typically use to stay informed about the latest advancements in lidar technology? (Check all that apply)
State DOT Regular training Internal, ad hoc training / mentorship Membership in lidar-related organizations Collaboration with educational / research Subscriptions to industry magazines and journals Continuing education opportunities Tradeshows and national conferences such as GeoWeek Professional certifications Other (please specify)
Alabama X X - - - X X - X
Alaska - X X X - - X X -
Arizona
Arkansas - X - - - - - - -
California X X - X X - X X -
Colorado - X - - X X X - X
Connecticut X X - X - - X - -
Delaware
District of Columbia - - - - - - X - -
Florida - - X X - - - - -
Georgia
Hawaii - - - - X X X X -
Idaho - - - - - - - - X
Illinois - X - - - - - - -
Indiana - - - - X X - - -
Iowa - X - X X X - - -
Kansas - - X X - - - - -
Kentucky - - - X - X - - -
Louisiana X X - - - X X X -
Maine X X - - - X - X -
Maryland X X - - - X - - -
Massachusetts - - - X - - - - -
Michigan - - - X - X X X -
Minnesota - - - - - - X - -
Mississippi
Missouri - - - - X X X - -
Montana - X - - - X X - -
Nebraska
Nevada - X - X - X - - -
New Hampshire - - - - - X X - -
New Jersey X - - - - - - - -
New Mexico - X - - - - - - -
New York X - - - X - X - -
North Carolina - X - - - X X - -
North Dakota - - - - X - X - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Ohio - X X - - - X - -
Oklahoma - - - - - - X - -
Oregon - X - - X - X - -
Pennsylvania - - - - X X X X -
Rhode Island - - - - - - - - X
South Carolina - - - - - X - - X
South Dakota - - - - - - - - -
Tennessee - - X - - - X - -
Texas X X - X X X X - -
Utah - X - - - - - - -
Vermont - X - - - - - - -
Virginia - - X - X X X - -
Washington X X - - - - - - X
West Virginia - - - X - X X - -
Wisconsin - - - - X X X - -
Wyoming X - - - X X X - -
State DOT Other Text
Alabama Contractors/Vendors
Colorado Vendor notice of updates and training
Idaho Unknown
Rhode Island Self-learning
South Carolina Self-study
Washington This will grow as we expand on the business units involved.

Future needs.

  1. How does your DOT assess the return on investment (ROI) in lidar data projects?

The hexagon map displays whether departments of transportation considered cost saving as an assessment criterion for return on investment in Lidar data projects using six patterns. A pattern of red diagonal lines marks states that responded “No”—Idaho, Wyoming, Colorado, Oklahoma, Kansas, Louisiana, Michigan, Indiana, North Carolina, Vermont, and Connecticut—accounting for 21.6 percent, with sample size N equal to 11. An open pattern of green diagonal lines marks states that reported that R O I is not assessed—Oregon, Utah, and the District of Columbia—accounting for 5.9 percent, with N equal to 3. A tight pattern of green diagonal lines marks states that responded “Yes”—Alaska, Nevada, Washington, California, New Mexico, Texas, North Dakota, Minnesota, Wisconsin, Iowa, Illinois, Missouri, Arkansas, Tennessee, Kentucky, Alabama, Florida, South Carolina, Virginia, West Virginia, Ohio, Pennsylvania, New Jersey, New York, Maryland, New Hampshire, and Maine—accounting for 52.9 percent, with N equal to 27. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—South Dakota, Montana, and Mississippi—also accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map displays whether departments of transportation considered improved decision-making savings as an assessment criterion for return on investment in Lidar data projects, using six patterns. A pattern of red diagonal lines marks states that responded “No”—California, Wyoming, North Dakota, New Mexico, Oklahoma, Missouri, Iowa, Arkansas, Louisiana, Indiana, Michigan, Ohio, Kentucky, South Carolina, Virginia, West Virginia, Pennsylvania, New Jersey, Maryland, Maine, Florida, and Vermont—accounting for 43.1 percent, with sample size N equal to 22. An open pattern of green diagonal lines marks states that reported that R O I is not assessed—Oregon, Utah, and the District of Columbia—accounting for 5.9 percent, with N equal to 3. A tight pattern of green diagonal lines marks states that responded “Yes”—Alaska, Idaho, Nevada, Colorado, Minnesota, Wisconsin, Texas, Kansas, Illinois, Tennessee, North Carolina, Alabama, Connecticut, New York, New Hampshire, and Washington—accounting for 31.4 percent, with N equal to 16. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—South Dakota, Montana, and Mississippi—also accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. A hexagon map displays whether departments of transportation consider time efficiency savings as an assessment criterion for return on investment in Lidar data projects, using six patterns. A pattern of red diagonal lines marks states that responded “No”—Vermont, Kansas, and Virginia—accounting for 5.9 percent, with sample size N equal to 3. An open pattern of green diagonal lines marks states that reported that R O I is not assessed—Oregon, Utah, and the District of Columbia, that reported R O I is not assessed, accounting for 5.9 percent, with N equal to 3. A tight pattern of green diagonal lines marks states that responded “Yes”—Alaska, California, Nevada, New Mexico, Texas, Idaho, Wyoming, North Dakota, Colorado, Oklahoma, Missouri, Arkansas, Louisiana, Alabama, Florida, South Carolina, North Carolina, Kentucky, Tennessee, Indiana, Michigan, Ohio, Pennsylvania, New Jersey, Maryland, Connecticut, Minnesota, New York, Maine, New Hampshire, Illinois, Iowa, Wisconsin, West Virginia, and Washington—accounting for 68.6 percent, with N equal to 35. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, South Dakota, and Mississippi—also totaling 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays whether departments of transportation consider savings from enhanced project outcomes as an assessment criterion for return on investment in Lidar data projects, using six patterns. A pattern of red diagonal lines marks states that responded “No”—Idaho, North Dakota, Wyoming, Colorado, New Mexico, Oklahoma, Kansas, Arkansas, Iowa, Illinois, Indiana, Wisconsin, Kentucky, Missouri, Ohio, Michigan, New Jersey, Vermont, Florida, and New Hampshire—accounting for 39.3 percent, with a sample size N equal to 20. An open pattern of green diagonal lines marks states that reported that R O I is not assessed—Oregon, Utah, and District of Columbia—accounting for 5.9 percent, with N equal to 3. A tight pattern of green diagonal lines marks states that responded “Yes”—Alaska, Washington, California, Texas, Nevada, Minnesota, South Carolina, North Carolina, Maryland, Connecticut, West Virginia, Virginia, Alabama, Tennessee, Maine, New York, and Pennsylvania—accounting for 33.3 percent, with N equal to 17. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—South Dakota, Montana, Mississippi, and Louisiana—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map displays whether departments of transportation consider safety savings as a criterion for return on investment in Lidar projects, using six patterns. A pattern of red diagonal lines marks states that responded “No”—New Jersey and Kansas—accounting for 3.9 percent, with sample size N equal to 2. An open pattern of green diagonal lines marks states that reported that R O I is not assessed—Oregon, Utah, and the District of Columbia—accounting for 5.9 percent, with N equal to 3. A tight pattern of green diagonal lines marks states that responded “Yes”—Alaska, Washington, California, Nevada, North Dakota, Idaho, New Mexico, Minnesota, Texas, Oklahoma, Missouri, Colorado, Iowa, Arkansas, Louisiana, Alabama, Florida, South Carolina, North Carolina, Virginia, West Virginia, Kentucky, Tennessee, Indiana, Michigan, Ohio, Pennsylvania, New York, Maryland, Connecticut, Vermont, New Hampshire, Maine, Illinois, Wyoming, and Wisconsin—accounting for 70.6 percent, with a sample size N equal to 36. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, South Dakota, and Mississippi—also totaling 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map displays other assessment criteria for return on investment in Lidar data projects by departments of transportation, using eight patterns. A pattern of red diagonal lines marks states that responded “No”—Alaska, California, Washington, Oregon, Nevada, North Dakota, Minnesota, Idaho, Wyoming, Colorado, New Mexico, Texas, Oklahoma, Kansas, Missouri, Arkansas, Wisconsin, Illinois, Indiana, Michigan, Ohio, Kentucky, Tennessee, Florida, Vermont, New Hampshire, Maine, North Carolina, Virginia, West Virginia, Maryland, Pennsylvania, New Jersey, Connecticut, and New York—accounting for 68.6 percent, with sample size N equal to 35. A pattern of green diagonal stripes marks Alabama, the single state that responded that no formal R O I documents were developed, accounting for 2.0 percent. A horizonal line pattern marks states that reported that R O I is not assessed—Utah and the District of Columbia—accounting for 3.9 percent, with N equal to 2. An open diagonal crosshatch pattern marks South Carolina, the single state that indicated that R O I was not formally assessed and that benefits were seen empirically over time, accounting for 2.0 percent. An open crosshatch pattern marks Iowa, which indicated that, to clarify, the selections above were noted but no formal R O I analysis had been completed, that they were aware of, accounting for 2.0 percent, with N equal to 1. A tight crosshatch pattern marks states that responded that they were not sure—Massachusetts, Rhode Island, and Hawaii—accounting for 5.9 percent, with N equal to 3. A diagonal crosshatch pattern marks states that did not respond to the question—South Dakota, Montana, Louisiana, and Mississippi—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group. The hexagon map shows assessment criteria for return on investment in Lidar data projects by departments of transportation—Other—using five patterns. An open pattern of diagonal lines marks Alabama, the single state that indicated that no formal R O I documents were developed, accounting for 2.0 percent. An open crosshatch pattern marks South Carolina, the single state that indicated that R O I was not formally assessed and that benefits were seen empirically over time, accounting for 2.0 percent. A horizontal line pattern marks Iowa, which indicated that, to clarify, the selections above were noted but no formal R O I analysis had been completed, that they were aware of, accounting for 2.0 percent, with N equal to 1. A diagonal crosshatch pattern marks states that did not respond to the question—Alaska, Arkansas, California, Colorado, Connecticut, the District of Columbia, Florida, Hawaii, Idaho, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming—accounting for 86.2 percent, with N equal to 44. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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  1. Regarding costs for lidar programs, what specific cost components are prioritized or considered essential in terms of improving ROI?

The hexagon map displays D O Ts’ key cost components for improving return on investment in Lidar programs, using 11 patterns. An open diagonal crosshatch pattern marks states that emphasized processing costs—Oregon, California, North Dakota, Missouri, Louisiana, Virginia, Massachusetts, and Pennsylvania—accounting for 15.7 percent, with sample size N equal to 8. A pattern of circles marks Colorado, which indicated that it emphasized processing costs, other, accounting for 2.0 percent, with N equal to 1. A loose dotted pattern marks states Kentucky, Florida, and Connecticut, that emphasize processing costs with significant attention to storage costs—accounting for 5.9 percent, with N equal to 3. An open crosshatch pattern marks states that indicated high focus on collection costs—Idaho, Wyoming, Utah, Nevada, Texas, Oklahoma, Kansas, Arkansas, New York, New Jersey, New Hampshire, and Maine—accounting for 23.5 percent, with N equal to 12. An open pattern of green diagonal lines marks states that indicated high focus on collection costs and emphasis on processing costs—New Mexico, Wisconsin, West Virginia, North Carolina, and Alabama—accounting for 9.8 percent, with N equal to 5. A horizontal line pattern marks states that indicated high focus on collection costs, emphasis on processing costs, and significant attention to storage costs—Alaska, Washington, Iowa, and Tennessee—accounting for 7.8 percent, with N equal to 4. An pattern of yellow diagonal stripes marks Michigan, which indicated high focus on collection costs and significant attention to storage costs, accounting for 2.0 percent, with N equal to 1. A pattern of stars marks states that give significant attention to storage costs—Illinois, Indiana, and Maryland—accounting for 5.9 percent, with N equal to 3. A tight dotted pattern marks states that responded “Other”—Hawaii, Ohio, Rhode Island, South Carolina, and Minnesota that selected other, accounting for 9.8 percent, with N equal to 5. A tight diagonal crosshatch pattern marks states that did not respond to the question—Montana, Vermont, the District of Columbia, and South Dakota—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

State DOT High focus on collection costs Emphasis on processing costs Significant attention to storage costs Other (please specify)
Alabama X X - -
Alaska X X X -
Arizona
Arkansas X - - -
California - X - -
Colorado - X - X
Connecticut - X X -
Delaware
District of Columbia - - - -
Florida - X X -
Georgia
Hawaii - - - X
Idaho X - - -
Illinois - - X -
Indiana - - X -
Iowa X X X -
Kansas X - - -
Kentucky - X X -
Louisiana - X - -
Maine X - - -
Maryland - - X -
Massachusetts - X - -
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Michigan X - X -
Minnesota - - - X
Mississippi
Missouri - X - -
Montana X - X -
Nebraska
Nevada X - - -
New Hampshire X - - -
New Jersey X - - -
New Mexico X X - -
New York X - - -
North Carolina X X - -
North Dakota - X - -
Ohio - - - X
Oklahoma X - - -
Oregon - X - -
Pennsylvania - X - -
Rhode Island - - - X
South Carolina - - - X
South Dakota - - - -
Tennessee X X X -
Texas X - - -
Utah X - - -
Vermont - - - -
Virginia - X - -
Washington X X X -
West Virginia X X - -
Wisconsin X X - -
Wyoming X - - -
Agency Other Text
Colorado Equipment cost and maintenance
Hawaii Not sure
Minnesota Based on projects
Ohio We do not prioritize costs in this manner.
Rhode Island Consultants
South Carolina Lidar is considered a mapping tool. Consultants provide 99% of lidar mapping and cost is negotiated as part of the preconstruction contract.
  1. If your DOT assesses ROI for lidar technology, what is the approximate level of return seen in recent years?
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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The hexagon map shows recent trends in return on investment for Lidar technology in D O Ts, using six fill patterns. An open crosshatch pattern marks states that reported average R O I—Nevada, West Virginia, Virginia, Florida, New York, Connecticut, and Maine—accounting for 13.7 percent, with sample size N equal to 7. An open diagonal crosshatch pattern marks states whose departments do not assess R O I for Lidar technology—Oregon, Idaho, Utah, North Dakota, Iowa, Illinois, Michigan, Missouri, Texas, Kansas, Oklahoma, Pennsylvania, North Carolina, South Carolina, Maryland, and Rhode Island—accounting for 31.5 percent, with N equal to 16. A pattern of circles, representing poor R O I, is not shown for any state, accounting for 0.0 percent, with N equal to 0. A horizontal line pattern marks states that reported substantial positive R O I—Alaska, California, Washington, Wyoming, Colorado, New Mexico, Minnesota, Louisiana, Arkansas, Kentucky, Ohio, and New Jersey accounting for 23.5 percent, with N equal to 12. A diagonal line pattern marks states in which the R O I trend is unclear—Hawaii, Wisconsin, Indiana, Tennessee, Alabama, New Hampshire, Vermont, and Massachusetts—accounting for 15.7 percent, with N equal to 8. A diagonal crosshatch pattern marks states that did not respond to this question—Montana, South Dakota, Mississippi, and the District of Columbia—accounting for 7.8 percent, with N equal to 4. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

Innovative and Interesting Case Examples

As part of this synthesis, we will be including case study examples with at least 5 DOTs to highlight lidar data usage including benefits and challenges. We are looking for case studies that reflect a wide range of technology usage levels.

  1. We would like to interview selected DOT respondents for use in developing case examples. Case examples will be included in the final synthesis report. The case example DOTs will be identified, but the interviewees will remain anonymous. DOTs will have the opportunity to review their case examples for accuracy. Case example interviews typically last for one hour. Are you willing to participate in a case study interview?

The hexagon map shows the willingness of departments of transportation to contribute case examples on Lidar data usage by United States using four patterns. An open pattern of diagonal lines marks states states that responded “No”—Alaska, Hawaii, Nevada, North Dakota, Wyoming, Utah, Iowa, Illinois, New Mexico, Indiana, Ohio, Kentucky, West Virginia, Virginia, the District of Columbia, Maryland, Pennsylvania, New Jersey, Connecticut, Louisiana, Alabama, Michigan, Missouri, New York, Maine, Vermont, Rhode Island, and New Hampshire—accounting for 54.9 percent, with sample size N equal to 28. A tight pattern of diagonal lines marks states that responded “Yes”—Washington, Texas, Oregon, California, Idaho, Colorado, Kansas, Oklahoma, Arkansas, Massachusetts, Minnesota, Wisconsin, Tennessee, South Carolina, North Carolina, and Florida—accounting for 31.4 percent, with N equal to 16. A diagonal crosshatch pattern marks states that did not respond to the question—Montana, South Dakota, and Mississippi—accounting for 5.9 percent, with N equal to 3. A blank fill marks states that reported no Lidar usage—Arizona, Delaware, Georgia, and Nebraska—accounting for 7.8 percent, with N equal to 4. The legend defines each pattern by category, percentage, and sample size, where N is the number of states in each group.

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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Suggested Citation: "Appendix B: Detailed Questionnaire Results." National Academies of Sciences, Engineering, and Medicine. 2025. Practices for Collecting, Managing, and Using Light Detection and Ranging Data. Washington, DC: The National Academies Press. doi: 10.17226/29042.
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Next Chapter: Appendix C: Case Example Interview Questions
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