Abstract

Integrating advanced algorithms, LiDAR and soil data in ArcGIS
Track: Water Resources
Authors: Peder Bøcher, Lars Arge, Jens-Christian Svenning, Mogens Greve

One main challenge with LiDAR technology is that it readily generates tens or hundreds of gigabytes of data (Arge et al. 2003). Despite this, several applications including erosion modeling, landslide risk assessment, stream mapping, and hydrologic modeling can in theory benefit from the high resolution data as the spatial resolution of these approaches the scale at which these processes take place.
The massive data challenges are at the moment being dealt with by means of innovative I/O-efficient algorithms. These algorithms have until now increased the speed with which surface hydrological parameters for example are being computed by factors above 1000 (Danner et al., 2007).
Here we present the latest methods for computing surface hydrological parameters from terrain data and combined with airborne imagery and fine resolution soil data obtained by proximal sensors (EM-38). Everything is combined through the unique facilities in ArcGIS to integrating algorithms and data.