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
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
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
NC STATE UNIVERSITY Elevation 400 m 422 m
NC STATE UNIVERSITY Terrain Attributes Ø Slope gradient Ø Slope aspect Ø Upslope contributing area Ø Slope curvature – Profile curvature – Contour curvature – Total curvature
NC STATE UNIVERSITY Slope Gradient 0%17%
NC STATE UNIVERSITY Upslope Contributing Area
NC STATE UNIVERSITY Profile Curvature
NC STATE UNIVERSITY Topsoil Thickness 0 m2 m
NC STATE UNIVERSITY DEM Resolution 0%17% 0%15% 10 m DEM 30 m DEM
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
NC STATE UNIVERSITY DEM Horizontal Resolution
NC STATE UNIVERSITY DEM Resolution 0%17% 0%15% 10 m DEM 30 m DEM
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
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
NC STATE UNIVERSITY LIDAR Data Density
NC STATE UNIVERSITY LIDAR Data Density
NC STATE UNIVERSITY Data Reduction LIDAR tile 50% Test 50% Validation 25% Test 10% Test 5% Test 5% Test 1% Test 1% Test
NC STATE UNIVERSITY Data Reduction } } 10 cm IDW vs. OK
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
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
NC STATE UNIVERSITY Study Site
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
NC STATE UNIVERSITY Data Reduction 100% 50% 25% 10% 5% 1%
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
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
NC STATE UNIVERSITY Data Reduction and Point Density
NC STATE UNIVERSITY Elevation Differences
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
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
NC STATE UNIVERSITY Data Density
NC STATE UNIVERSITY Data Density Requirements DEM horizontal resolution (m) LIDAR (points ha -1 ) Excessive data density Threshold data density Insufficient data density
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
NC STATE UNIVERSITY
DEM Precision 0%17% 0%20% 0.1 m precision 1.0 m precision
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
NC STATE UNIVERSITY DEM Vertical Precision
NC STATE UNIVERSITY DEM Precision 0%17% 0%20% 0.1 m precision 1.0 m precision
NC STATE UNIVERSITY Study Site
NC STATE UNIVERSITY
LIDAR Data Density Ø Collected as point files Ø Linear interpolation techniques are needed for improved use of LIDAR (Lloyd and Atkinson, 2002)
NC STATE UNIVERSITY Profile Curvature
NC STATE UNIVERSITY Data Reduction 100% 1%