Digital Elevation Models (DEMs) play an important role in terrain-related GIS applications. Chief among the many factors that affect the accuracy of DEMs, is the accuracy, type, and resolution of the source data. Photogrammetric DEMs derived from stereo imagery can deliver highly accurate terrain data, but can be time consuming and difficult to create in dense urban cores or heavily forested areas. Light Detection and Ranging (LiDAR) offers high density data capture that provides the opportunity to make high-quality elevation models of two distinct types: DSMs that include tree canopy and/or building surfaces, or bare-earth DEMs.
Join experts from PCI Geomatics and DAT/EM Systems International as we demonstrate a workflow that leverages DAT/EM’s Landscape software to ingest raw LiDAR data and generate 3D point clouds. Learn how these point clouds can be easily ingested into Geomatica using Python scripting for accurate DEM creation, and how using Geomatica’s Smart GeoFill technology will allow you to merge DEMs from multiple sources at varying accuracies and resolutions into one homogeneous product.