2017/12/12 by Pinliang Dong, Qi Chen · 1 citation
Environmental Science · Earth and Planetary Sciences · #Remote Sensing and LiDAR Applications #3D Surveying and Cultural Heritage #Remote Sensing in Agriculture
paper · doi:10.4324/9781351233354-3
openalex publication_date 2017/12/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
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;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.