LiDAR QAQC

04/10/2023 MN GIS/LIS Spring Workshop Series

LiDAR Quality Control

Validating LiDAR Data

Tim Loesch

Minnesota Department of Natural ResourcesGIS Section

04/10/2023 MN GIS/LIS Fall Workshops

LiDAR QA/QC – Did I get what I paid for?

LiDAR = Massive quantities of dataLiDAR = Expensive acquisition costsLiDAR = File upon file upon file…LiDAR = Very accurate informationLiDAR = Lots of room for error

Client QA/QC is an critical part of the process



QA/QC ElementsValidating file(s) existence

LiDAR is delivered in tiles

Validation of data Schema Valid elevation values Visual exam for data defects Vertical accuracy verification

Based on Contractual Obligations



Tightly defined data delivery structureProvides a basis for comparisonDevelopment of automated validation routines



Step by Step ChecklistHelps with consistencyAllows for distribution of effortEnsures consistency of validationProvides record of work



Initial File Check-inAutomated routine checks for:

File existence (GDB, LAS, DEM, etc) Valid values Field validation

Produces table of results



DEM MosaicMosaic all DEMs to single rasterGenerate shaded relief

Provides excellent product for visual examinationDisplay techniques can reveal small irregularitiesWe visually inspect every tile!



Generate derived products2’ ContoursBuilding Polygons

Can highlight problems that you cannot see

Classification errorsOverlap errors

04/10/2023 Minnesota Department of Natural Resources


Vertical Accuracy AssessmentValidation Points

Level ground away from breaks in topography Open, visible sky

Five cover classes – 20 points per class (30 preferred) L1O – Open terrain L2T – Tall Grass L3B – Brush L4F – Forested L5U - Urban


Types of AccuracyFundamental Accuracy = Best Case Scenario

Open terrain tested to 95% accuracy

Supplemental Accuracy Accuracy for Cover Classes other than Open terrain

Consolidated Accuracy All Cover Class Accuracies Combined



371.93

LiDAR pointsInterpolated Value372.115



Winona County Validation Points



RMSE CalculationsRMSE(z) = Sqrt(sum(Zdata(i) – ZCheck(i))2 / n)

NSSDA Vertical Accuracy 95% Rate = 1.96 * RMSE2



--------- Report Summary ---------

Error Mean: -0.116Error Range: [-0.435,0.143]Skew: -0.305RMSE(z): 0.161NMAS/VMAS Accuracy(z) (90% CI): ±0.265ASPRS/NSSDA Accuracy(z) (95% CI): ±0.315

176 control points included in summary out of 176- 0 control points turned off- 0 control points returned no-data

--------- Control Points ---------

Name Control X Control Y Control Z Surface Z Error L1O0 604760.340 4878787.629 201.217 201.389 -0.172 L5U1 608921.294 4878065.350 201.488 201.806 -0.318 L1O2 610991.353 4876621.369 200.214 200.397 -0.183 L1O3 607292.402 4874401.804 233.428 233.606 -0.178 L1O4 622397.772 4873262.387 207.292 207.356 -0.064 L1O5 626922.206 4869248.810 202.936 202.969 -0.033 L1O6 631669.497 4863815.331 200.254 200.333 -0.079 L1O7 635439.901 4857649.190 375.011 375.070 -0.059 L1O8 625518.897 4864620.423 385.756 385.722 0.034 L2T9 621174.012 4864494.226 388.359 388.470 -0.111 L2T10 620283.975 4857065.579 386.810 387.048 -0.238



Winona County Validation Report

RMSE across cover Types

RMSE0.000

0.050

0.100

0.150

0.200

0.250

0.127

0.166

0.196

0.172

0.136

0.161

L1OL2TL3BL4FL5UOverall



Winona County Validation Report

175 225 275 325 375 425-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

Vertical Error Distribution

L1OL2TL3BL4FL5U



Then…..If the data does not meet spec Vendor is notified and delivered QA/QC Checklist

Some issues are clear and some are not

If the data is deemed to meet or exceed spec Packaging and Publishing Metadata, Services, etc…..



National Accuracy Standards Specifications

USGS Base LiDAR Specifications V13

NDEP Guidelines For Digital Elevation Data


http://lidar.cr.usgs.gov/USGS-NGP%20Lidar%20Guidelines%20and%20Base%20Specification%20v13(ILMF).pdf

http://www.ndep.gov/TechSubComm.html

http://www.ndep.gov/TechSubComm.html

Documents

LiDAR QAQC