ABSTRACT
The processing and analysis methods for Light Detection and Ranging (LiDAR) data are usually application-specific, and many new methods are being proposed. Unlike optical or radar imagery, airborne LiDAR data do not continuously measure or map the earth's surface. Each laser pulse and its returns are essentially samples of the environment, even at very high point density. This chapter introduces filtering, classification of non-ground returns, and spatial interpolation, respectively. It presents two ArcGIS projects to create a digital terrain model (DTM), a digital surface model (DSM), and a digital height model (DHM) for an area in Indianapolis, IN (USA), and to create a terrain dataset for an area in St. Albans, VT (USA). Filtering is used to remove non-ground LiDAR points so that bare-earth digital elevation models can be created from the remaining ground LiDAR points. Triangulated irregular network (TIN) is a vector-based data structure for representing continuous surface. TIN is well suited for constructing terrain surface from LiDAR points.
