LiDAR QA/QC Presentation

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LiDAR Calibration Errors & QA/QC

September 16th, 2009

GIS in The RockiesPresented By: Brandon Tilley



What is Calibration?

• Calibration varies by

vendor

• Four different lines

collected

• 3 perpendicular

• 1 parallel

• All used to calibrate a

single mission




• This calibration is flown before

and after the flight/mission

• Flown over a flat surface

• Enables user to account for the

attitude of the aircraft

• Yaw, pitch, and roll are primarily

adjusted using opposing lines

• Calibration settings apply to entire

mission




• Roll accounted

• Pitch accounted

• Settings applied throughout

mission strips

• Similar calibration settings

for each flight

• Accurate calibration =

Accurate Dataset

Roll Error

Corrected Roll

Pitch Error

Corrected Pitch



Calibration Errors

Roll

• Can potentially be seen in

entire project

• Can greatly effect the

horizontal and vertical

accuracy of your data

• Create sharp elevation shifts

between each swath

• Cutting overlap usually helps

with roll errors

Pitch

• Can decrease the quality of the

building and structure by shape

• Decreases accuracy of

classifications, i.e. ground and

building classes

• Greatly reduces the accuracy of

the horizontal and vertical planes

• If widespread throughout project,

will create inaccurate geo-

referenced data



Relative Accuracy - CalibrationErrors – Roll



Relative Accuracy - CalibrationRoll Error Corrected



Relative Accuracy - CalibrationRoll Error- Example 2



Relative Accuracy - Calibration

Pitch Error



Relative Accuracy - CalibrationPitch Error Corrected



Filtering

• Cutting over edge or overlap?

• No? Increases chances for less accurate data (off nadir) but provides more

bare earth points per sq. m.

• Yes? Eliminates chances for less accurate data, less ground

• Removing (classifying) outliers?

• Ground filter: Does it classify too much? Not enough?

• All filter steps are necessary for an accurate BE model



Filtering- Under Filtering



Filtering- Over Filtering



Filtering- Ground

• Under Filtering

• Produces an inaccurate bare earth model

• Within the BE surface, can be vegetation, swath noise, buildings and bridges

• Increases manual QC TPT

• Over Filtering

• Also creates inaccurate bare earth model

• Cuts off mountains, hills, and other terrain features

• Increases manual QC TPT



Final QC Techniques

• What should your bare earth

surface contain?

• Structures removed

• Artifacts/Vegetation removed

• Noise removed

• Very minimal calibration

errors (if any)

• Common Sense• Anything not man made



Artifact Removal – Bridges/Overpasses



Artifact Removal – Buildings/Structures



Artifact Removal – Vegetation



Clients’ Specifications

Standard LIDAR 1.4m

• Automated process yields 89% of Artifacts removed

• Automated process yields 90% of all outliers removed

• Automated process yields 90% of all vegetation removed

• Automated process yields 93% of all Building removed

FEMA Compliant LIDAR• Automated process yields 90% of Artifacts or as required by FEMA lead

• Outliers removed per the FEMA lead provisions for a limited percentage of outliers

• Automated process yields 95% of all vegetation removed and as per FEMA lead provisions

• Automated process yields 98% of all Building removed and as per FEMA lead provisions

High Density LIDAR 0.7m

• Automated and manual processes yields 95% of Artifacts removed

• Automated process yields 98% of all outliers removed

• Automated process yields 97% of all vegetation removed

• Automated process yields 99% of all Building removed



Efficiency

• Tiled datasets

• Fast read/write

• Multitasking

• Data tracking

• Easy to use tools for

classifying points


Distribution or copying prohibited unless approved in writing.

Thank You!

Graphics provided by Leica

Technology

LiDAR QA/QC Presentation