unmanned aerial systems (uas) data quality and accuracy realities

Copyright © 2013 Merrick & Company - All rights reserved.

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Matt Bethel, GISP

Director of Technology for Merrick & Company


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Stephen Keen geoResource Technologies, Inc. Northeast Arc User Group (NEARC)Spring Spatial Technologies Conference Monday, May 11, 2015


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UAS vs. Direct Georeferencing

GPS seeds the processing No post processing GPS (no AGPS base station required) No rigorous IMU processing Photo identifiable points are still required Exterior orientation is calculated with little to no GPS/IMU information

Camera model is automatically refined throughout the process Interior is adjusted, typically per image This allows for the use of non-metric cameras

Movement towards more streamlined / black box process Less human time, more computer time (until processes are improved)

1. Relative 3D model is built using computer vision processes

2. Adjusted to ground with control using traditional AT procedures

3. Strengthened and densified using new photogrammetric processes


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UAS Processing Workflow

Flight Planning AcquisitionPre-Processing

• Image reformatting• AGPS reformatting• Processing block selection

Triangulation• Feature detection• Feature matching• Initial 3D model / point cloud built using

Structure from Motion (SfM)• Models each scene• Creates a rough surface for image scaling

during point measurement• Interior orientation calibration

Control Point Measurement

Bundle Adjustment• Adjusts model to control point

measurements• Recalibrates interior and exterior

orientations

Full Processing• Uses multi-ray photogrammetry /SGM• Undistorts images• Creates dense point clouds

Orthophoto Generation• Creates grid• Creates mesh (to fill in holes)• Generates individual orthophotos• Mosaicing, radiometric and color

balancing, and automatic seamline placement

• Mosaic tiling

Image Textured 3D Models


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Influences on UAS Product Accuracies

Camera CCD / pixel size and quality Lens quality Lens field of view Camera triggering / frame rate and image

write speed Shutter speed / motion blur ISO, aperture, and focus (infinity) Image compression and acquisition storage

file format (raw vs. jpg) Orientation (portrait vs. landscape)

UAV Flight line geometry, especially cross flight

lines Image endlap and sidelap Flight management system Stability / wind conditions Above ground level

Environmental Lighting conditions Land cover Dust, haze, humidity, smog, etc.

GNSS Surprisingly, rarely AGPS quality Quality and feature placement of photo id

control points Photo id control points distribution Quantity of photo id control points Use of an inertial measurement system

Software Computer resources (can limit products) Features Settings Robustness Versions


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Test Area

2,105 nadir RGB images2 UAS missions300 m AGL24 MP non-metric digital

camera75% endlap / 50% sidelap4.5 cm nominal pixel res2.6 square miles31 GPS surveyed points

5 Control points 26 Check points

UAS data overlaps existing fixed wing LiDAR


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Horizontal Orthophoto Accuracy

Reno Stead Airport AOI 0.5 square mile 10 cm acquisition / orthophoto

resolution 31 surveyed photo id points

15 used for control 16 used for check

15 control points = 5.5 cm RMSE

16 check points = 4.9 cm RMSE

Typically 1 -1.5 pixel resolutionGuadalajara AOI yielded 5 cm RMSE from 4.5 cm resolutionSome lower resolution, small area collects can yield better than 1:1


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3D Product Accuracy Results

Dense Point Cloud Gridded Elevation Model0

5

10

15

20

25

30

6.15.2

7.9

9.7

24.2

20.1

15.1

11.2

Fixed Wing LiDAR

UAS Software 1

UAS Software 2

UAS Software 3

Vert

ical

Acc

urac

y R

MSE

z (c

m)


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Volumetric Accuracy Results

Dense Point Cloud Gridded Elevation Model0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

2.50%

0.78%

0.21%

0.04%

1.10%

1.42%

UAS Software 1

UAS Software 2

UAS Software 3

Volu

met

ric D

iffer

ence

Com

pare

d to

LiD

AR


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3D Model Regional Deformation

Vertical separation raster of UAS DPC compared to the all returns LiDAR

The vertical RMSEz measured to PID control for each SW package are: UAS Software 1 – 7.9 cm UAS Software 2 – 24.2 cm UAS Software 3 – 15.1 cm

Meters


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Summary of Realistic UAS Accuracies

Best possible horizontal (absolute) accuracy in non-obstructed land cover is 0.5 to 1.5 times the captured pixel resolution (RMSE)

Best possible vertical (absolute) accuracy in non-obstructed land cover is 2 to 3 times the captured pixel resolution (RMSE)


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Phoenix Aerial Systems LiDAR UAS Vertical Accuracy


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Phoenix Aerial Systems LiDAR UAS Horizontal Accuracy


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LiDAR UAS


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Contact Info

Matt BethelDirector of Technology

Merrick & Companywww.merrick.com

[email protected](303) 353-3662

http://www.merrick.com/

mailto:[email protected]