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Jim Thompson, Eric Anderson, & Rob Austin NC State University, Department of Soil Science Jim Thompson, Eric Anderson, & Rob Austin NC State University,

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Presentation on theme: "Jim Thompson, Eric Anderson, & Rob Austin NC State University, Department of Soil Science Jim Thompson, Eric Anderson, & Rob Austin NC State University,"— Presentation transcript:

1 Jim Thompson, Eric Anderson, & Rob Austin NC State University, Department of Soil Science Jim Thompson, Eric Anderson, & Rob Austin NC State University, Department of Soil Science NC STATE UNIVERSITY DEPARTMENT OF SOIL SCIENCE Horizontal Resolution and Data Density Effects on LIDAR-based DEM

2 NC STATE UNIVERSITY Outline Ø Digital elevation models (DEM) – Terrain attributes calculated from DEM – Horizontal resolution effects – Data density issues Ø LIDAR Data Density vs. DEM Quality – Methods – Results – Conclusions

3 NC STATE UNIVERSITY Outline Ø Digital elevation models (DEM) – Terrain attributes calculated from DEM – Horizontal resolution effects – Data density issues Ø LIDAR Data Density vs. DEM Quality – Methods – Results – Conclusions

4 NC STATE UNIVERSITY Elevation 400 m 422 m

5 NC STATE UNIVERSITY Terrain Attributes Ø Slope gradient Ø Slope aspect Ø Upslope contributing area Ø Slope curvature – Profile curvature – Contour curvature – Total curvature

6 NC STATE UNIVERSITY Slope Gradient 0%17%

7 NC STATE UNIVERSITY Upslope Contributing Area

8 NC STATE UNIVERSITY Profile Curvature

9 NC STATE UNIVERSITY Topsoil Thickness 0 m2 m

10 NC STATE UNIVERSITY DEM Resolution 0%17% 0%15% 10 m DEM 30 m DEM

11 NC STATE UNIVERSITY Horizontal Resolution Effects Ø Decreasing the horizontal resolution produces (Thompson and Bell, 2001): – lower slope gradients on steeper slopes – steeper slope gradients on flatter slopes – narrower ranges in curvatures – larger catchment areas in upper landscape positions – lower catchment areas in lower landscape positions Ø and leads to the loss of small-scale features

12 NC STATE UNIVERSITY DEM Horizontal Resolution

13 NC STATE UNIVERSITY DEM Resolution 0%17% 0%15% 10 m DEM 30 m DEM

14 NC STATE UNIVERSITY LIDAR-Based DEM Ø Interpolation of spot elevation data Ø Vertical precision of 0.1 m Ø Horizontal resolution – Best possible for any given application Ø NC Floodplain Mapping Program LIDAR Data – Bare earth mass data – 20 ft (~6 m) gridded DEM – 50 ft (~15 m) gridded DEM

15 NC STATE UNIVERSITY LIDAR Data Density Ø ,000 laser pulses per second Ø 2-7 returns collected for each laser pulse Ø 25,000 points per square mile ABUNDANCE OF DATA

16 NC STATE UNIVERSITY LIDAR Data Density

17 NC STATE UNIVERSITY LIDAR Data Density

18 NC STATE UNIVERSITY Data Reduction LIDAR tile 50% Test 50% Validation 25% Test 10% Test 5% Test 5% Test 1% Test 1% Test

19 NC STATE UNIVERSITY Data Reduction } } 10 cm IDW vs. OK

20 NC STATE UNIVERSITY Objectives Ø Produce a series of DEM at different horizontal resolutions at multiple LIDAR data densities Ø Compare each of these DEM to a DEM produced from 100% of the LIDAR data Ø Determine the optimum LIDAR point density suitable for producing a DEM at a given horizontal resolution Evaluate the effects of LIDAR data density on the production of DEM at different resolutions

21 NC STATE UNIVERSITY Outline Ø Digital elevation models (DEM) – Terrain attributes calculated from DEM – Horizontal resolution effects – Data density issues Ø LIDAR Data Density vs. DEM Quality – Methods – Results – Conclusions

22 NC STATE UNIVERSITY Study Site

23 NC STATE UNIVERSITY Study Site Ø Hofmann Forest – 32,500 ha forest ecosystem – Lower Coastal Plain – >90% forested – 12 to 20 m above MSL Ø LIDAR Data – NC Floodplain Mapping Program – 61 LIDAR tiles – 9,000,000 LIDAR points

24 NC STATE UNIVERSITY Data Reduction 100% 50% 25% 10% 5% 1%

25 NC STATE UNIVERSITY DEM5 50 DEM10 50 Data Reduction and Comparison Data Reduction DEM30 50 Compare Elevations DEM5 100 DEM DEM Generate DEM (ANUDEM) 100% LIDAR Data Set 100% LIDAR Data Set Generate DEM (ANUDEM) 50% LIDAR Data Set 50% LIDAR Data Set 25% LIDAR Data Set 25% LIDAR Data Set DEM30 25 DEM10 25 DEM % LIDAR Data Set 10% LIDAR Data Set DEM30 10 DEM10 10 DEM5 10 5% LIDAR Data Set 5% LIDAR Data Set DEM30 5 DEM10 5 DEM5 5 1% LIDAR Data Set 1% LIDAR Data Set DEM30 1 DEM10 1 DEM5 1

26 NC STATE UNIVERSITY DEM Comparisons Ø Evaluate the effects of data density at each horizontal resolution Ø Cell-by-cell comparison – Assumed DEM created from the complete LIDAR data set were the best DEM – Comparisons always made back to DEM created using the total original data set Ø Elevation values compared using paired t-tests Ø Differences regressed against data density

27 NC STATE UNIVERSITY Data Reduction and Point Density

28 NC STATE UNIVERSITY Elevation Differences

29 NC STATE UNIVERSITY Elevation Differences Ø All reduced density DEM overestimated elevations for all horizontal resolutions Ø As data density decreased, the elevation difference increased Ø As mean points per grid cell decreased, the elevation difference increased

30 NC STATE UNIVERSITY Elevation Differences Mean points per grid cell Mean difference (m) 5 m Mean points per grid cell Mean difference (m) 10 m Mean points per grid cell Mean difference (m) 30 m

31 NC STATE UNIVERSITY Data Density

32 NC STATE UNIVERSITY Data Density Requirements DEM horizontal resolution (m) LIDAR (points ha -1 ) Excessive data density Threshold data density Insufficient data density

33 NC STATE UNIVERSITY Conclusions Ø Target resolution of DEM determines the level of acceptable LIDAR data reduction Ø Higher density LIDAR data needed to model higher resolution topographic features Ø Results are a function of landscape morphology and land use

34 NC STATE UNIVERSITY

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37 DEM Precision 0%17% 0%20% 0.1 m precision 1.0 m precision

38 NC STATE UNIVERSITY Vertical Precision Effects Ø Decreasing the vertical precision of the DEM produces (Thompson and Bell, 2001): – more flat cells (slope gradient = 0 and curvature = 0) – more steep cells – a wider distribution in curvatures – discretization of elevation values, which leads to discretization of other terrain attributes and reduced similarity of data sets

39 NC STATE UNIVERSITY DEM Vertical Precision

40 NC STATE UNIVERSITY DEM Precision 0%17% 0%20% 0.1 m precision 1.0 m precision

41 NC STATE UNIVERSITY Study Site

42 NC STATE UNIVERSITY

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44 LIDAR Data Density Ø Collected as point files Ø Linear interpolation techniques are needed for improved use of LIDAR (Lloyd and Atkinson, 2002)

45 NC STATE UNIVERSITY Profile Curvature

46 NC STATE UNIVERSITY Data Reduction 100% 1%


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