Abstract
Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM). High resolution ground-based Light Detecting and Ranging (LiDAR) technology can be used to collect detailed topographic and land cover characteristic data. In this study, a method was developed to remove vegetation from ground-based LiDAR data to create high resolution DEMs. Research was conducted on intensively studied rainfall–runoff plots on the USDA-ARS Walnut Gulch Experimental Watershed in Southeast Arizona. LiDAR data were used to generate 1 cm resolution digital surface models (DSM) for 5 plots. DSMs created directly from LiDAR data contain non-surface objects such as vegetation cover. A vegetation removal method was developed which used a slope threshold and a focal mean filter method to remove vegetation and create bare earth DEMs. The method was validated on a synthetic plot, where rocks and vegetation were added incrementally. Results of the validation showed a vertical error of ±7.5 mm in the final DEM.
Highlights
Distributed process based hydrologic and erosion models use digital elevation models (DEMs) to discretize watersheds into contributing areas and route surface water across the terrain using overland flow planes and channels [1]
The difference map comparing the digital surface models (DSM) with the final DEM for the validation plot is shown in indicates areas where there is negligible change in elevation values in both DEMs
High resolution DEMs are used to generate accurate channels and planes needed for hydrologic and erosion simulation models
Summary
Distributed process based hydrologic and erosion models use digital elevation models (DEMs) to discretize watersheds into contributing areas and route surface water across the terrain using overland flow planes and channels [1]. Radar) and airborne LiDAR (Light Detecting and Ranging) have been used to scan the earth surface to develop digital elevation models (DEMs) used in hydrologic modeling, urban planning and forestry [2,3]. The captured data from airborne LiDAR often contain vegetation and other non-surface objects along with the surface topographic data. Various algorithms and methods have been developed to remove the vegetation and non-surface objects from the data and develop bare earth DEMs from DSM (digital surface model) [5,6,7]
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