1Comparison of Surface Models Derived by Manual, LIDAR, and Softcopy

Techniques

UW-Madison NCRST-I Research Team

Frank Scarpace, Alan Vonderohe, Teresa Adams (Investigators)

Nick Koncz (Project Manager)

Hongwei Zhu, Amar Padmanabhan, Jisang Park (Research Assistants)

2Comparison of Surface Models Derived by Manual, LIDAR, and Softcopy

Techniques

Objectives

Determine Differences among Results from the Various Techniques

Seek Methods for Improving Accuracies by Technology Integration

Seek Methods for Reducing Required Editing Time for Raw Softcopy Data

Test Site: Highway Corridor Near Solon, IA

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Manual, LIDAR, and Softcopy Data Sets

Manual Photogrammetry Data Set Provided by Iowa DOT and CTRE:

Breaklines and Mass Points (~20-Meter Spacing)

Compiled on Analytical Stereoplotters from 1:4800 (nominal scale) photos

Expected Accuracy: 0.07-0.10m RMS

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Breaklines and Mass Points

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1-Meter DEM Generatedfrom Manual Photogrammetry Data Set

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Manual, LIDAR, and Softcopy Data Sets

Softcopy Photogrammetry Data Set:

Same Photography as Manual Method Same Camera Calibration Same External Orientation Parameters

Film Diapositives Scanned at 15 Micrometers

38 Photos in 3 Strips – 35 Stereo Models

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Manual, LIDAR, and Softcopy Data Sets

Softcopy Photogrammetry Data Set: In-House Software

Resampled Epipolar Images

1:32 Image Pyramids

Cross-Correlation

Least Squares Matching

Generates Irregular 1-Meter Spacing of Elevations

Correlation Coefficients from a Single Model

Red = 0.5-0.7

Yellow = 0.7-0.9

Green = > 0.9

DEM by Softcopy Photogrammetry

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Manual, LIDAR, and Softcopy Data Sets

LIDAR Data Set: Irregular 2-Meter Spacing of Elevations

Expected Accuracy: 0.15m RMS

Raw Data Were Edited, But Some Vegetation (e.g., Crops) Were Not Removed

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Part of the LIDAR Data Set

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Parts of the Three Data Sets

Sample Comparisons and Results

Comparison Methodology

TINs

Manual PhotogrammetryMass Points and Breaklines

20m spacing (irregular)

LIDAR2 m spacing (irregular)

DigitalPhotogrammetry

1 m spacing (irregular)

POINTS

DEMs

DEMComparisons

POINT To TINComparisons

Sample Comparisons and Results

DifferenceType

Mean RMS Mean RMS(m) (m) (m) (m)

Sub-Area 1: Farmland DEM 0.29 0.39 0.33 0.35Without crops PT-TIN 0.21 0.37 0.31 0.37

Sub-Area 2: Farms/Road DEM 0.29 0.33 -0.11 0.27Without crops PT-TIN -0.37 0.43 -0.21 0.33

Sub-Area 3: Mixed Use DEM -0.13 0.39 0.17 0.21Without Hwy PT-TIN -0.14 0.69 0.12 0.21

AVERAGE DEM 0.15 0.37 0.13 0.28PT-TIN -0.10 0.50 0.07 0.30

Location 1: Drainage Ditch DEM 0.14 0.59 0.09 0.31PT-TIN 0.22 0.57 0.11 0.41

Location 2: Gully DEM 0.00 0.43 0.09 0.26PT-TIN 0.23 0.64 0.13 0.35

Location 3: Bridge DEM -0.25 0.33 0.14 0.19Without bridge deck PT-TIN -0.17 0.39 0.14 0.24

AVERAGE DEM -0.04 0.45 0.11 0.25PT-TIN 0.09 0.53 0.13 0.33

Softcopy

Area+ 2 m Tolerance

with 1st Approx.

ExtractionLIDAR

Preliminary Results Indicate that Softcopy Data are at Least as Good as LIDAR when Compared to Manually-Extracted Data.

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Sample Comparisons and Results

Mixed Land Use

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Sample Comparisons and Results

Drainage Ditch

18Softcopy / LIDAR Integration Project StatusSoftcopy Extraction w/LIDAR (Initial Comparison)

Model 127 PT-To-TIN Comparison Area #Points Min Max Mean StdDev RMS

Auto Match/ Manualw/o 1st approximation Whole DEM 3,615 -2.13 1.67 0.17 0.21 0.27

2m tolerance 3,615 -0.72 5.43 0.86 1.22 1.49

w/o 1st approximation W/O Road 1,202 -0.97 1.04 0.13 0.17 0.222m tolerance 1,202 -0.36 2.10 0.12 0.17 0.21

w/ LiDAR approximation + 1 m tolerance2.5M Spacing Whole DEM 3,615 -0.88 1.00 0.14 0.14 0.20

W/O Road 1,202 -0.74 1.00 0.10 0.15 0.18

5M Spacing Whole DEM 3,615 -0.87 0.97 0.14 0.13 0.19W/O Road 1,202 -0.63 0.97 0.08 0.14 0.16

10M Spacing Whole DEM 3,615 -1.19 0.75 0.13 0.14 0.19W/O Road 1,202 -0.63 0.71 0.08 0.14 0.16

LiDAR/ Manual Whole DEM 3,615 -1.59 2.89 -0.15 0.48 0.50W/O Road 1,202 -1.45 2.89 -0.14 0.68 0.69

LiDAR/ Auto Matchw/o 1st approximation Whole DEM 163,190 -5.55 2.99 -0.32 0.40 0.52

2m tolerance 134,705 -6.00 2.91 -0.33 0.40 0.52

w/o 1st approximation W/O Road 109,640 -2.67 2.99 -0.31 0.39 0.502m tolerance 104,124 -2.00 2.91 -0.31 0.34 0.46

19Softcopy / LIDAR Integration Project Status

Softcopy Extraction w/LIDAR (Initial Comparison)

Drainage Ditch PT-To-TIN #Points Min Max Mean StdDev RMS

Auto Match/ Manual 215w/o 1st approximation -0.23 0.79 0.17 0.17 0.24

2m tolerance -3.36 1.04 0.11 0.39 0.41

w/ LiDAR approximation + 1 m tolerance2.5 m Spacing -0.55 0.90 0.18 0.18 0.25

5 m spacing -0.68 1.23 0.19 0.20 0.2810 m spacing -0.45 1.12 0.20 0.19 0.28

LiDAR/ Manual 215 -0.71 1.66 0.22 0.53 0.57

LiDAR/ Auto Matchw/o 1st approximation 14611 -1.45 1.93 -0.10 0.58 0.59

2m tolerance 93104 -1.91 4.23 -0.06 0.58 0.58

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Softcopy Editing Tools

Automated Slope Filter (Spikes and Holes)

Manual (Stereo Viewing) Point-by-Point

Polygon Constant Elevation

Polygon Planar Fit

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Manual Editing Tool Menu

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Manual Editing Polygon Selection Tool

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Manual Editing Set-to-Constant Elevation Tool

One of the Stereo Pairs

Raw Softcopy Data

After Slope Filter

After Slope Filter

After Manual Editing

After Manual Editing

Effects of Slope Filter(Crop area was excluded)

Model: 4-1-125

Difference DEM Area #Points Min Max Mean StdDev RMS

Auto Match/ Manualw/ USGS approximation

Whole DEM 5044 -3.88 1.66 -0.19 0.5 0.54

W/O Road 3793 -3.88 1.66 -0.16 0.5 0.52

w/ LiDAR approximationWhole DEM 5044 -2.23 3.61 -0.11 0.46 0.47(without filter)W/O Road 3793 -2.23 3.61 -0.07 0.46 0.47(without filter)Whole DEM 5044 -2.16 1.84 -0.11 0.41 0.43(with filter)W/O Road 3793 -2.16 1.84 -0.1 0.41 0.43(with filter)

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ConclusionsWhen Differenced with Manually-Derived Data, Softcopy Results (0.2-0.4m RMS) are Slightly Better than LIDAR (0.3-0.5m RMS).When LIDAR is Used as First Approximation for Softcopy, Results are Mixed with Improvements of 20% (to 0.16m RMS) in Some Cases.Slope Filter Improves Raw Softcopy Data by 10%.Comparisons with Manually-Edited Softcopy Remain to be Done.