Surface Mapping, Data Handling, and 3D Data Visualizations for Mountainous Terrains with LIDAR-derived DEM

Aileen Buckley, Ph.D.
Department of Geography
University of Oregon
Eugene, OR 97403-1251
Voice: (541) 346-4160
Fax: (541) 346-2067

Mike Renslow
Spencer B. Gross, Inc.
13545 NW Science Park Drive
Portland, OR 97229
Voice: (503) 646-1733
Fax: (503) 626-4818


Accurate depiction of the earth’s surface has been advanced dramatically through the use of rich LIDAR (Light Detection and Ranging) data sets. LIDAR data are acquired from laser pulses directed towards the earth; since the speed of light is a constant, the time from pulse emission to pulse return can be accurately calculated. The time required to record the "return" allows the distance to the terrain surface to be mathematically determined resulting in accurate data recording of multiple returns about the first surface (such as vegetation canopy or building roofs), additional surfaces (such as understory), and the bare ground. Advantages of using these data for earth surface mapping include expeditious data delivery, easy integration with geographic information systems, and, in most cases, acquisition of LIDAR data at reduced costs when compared to traditional photogrammetric mapping. Additional advantages for mapping mountainous environments include LIDAR's increased ability to determine surface elevations in difficult areas and LIDAR's ability to capture data in normally obscured areas (such as in shadows and ravines).

In this paper, we describe the details relating to the use of LIDAR for mapping mountainous surfaces, including description of the use of LIDAR to generate high performance digital elevations models (DEMs), data handling techniques for using LIDAR data with GIS, and methods for making terrain maps and 3D visualizations from the LIDAR-derived DEMs. For this study, we focus on the Coast Range of northern California, with its highly dissected landscape, moderate ranges in relief, and dense vegetation cover. We provide a detailed description of the process used to map this area using multiple-return LIDAR data. We describe the generation of shaded relief models generated from the LIDAR-derived DEMs, along with methods for defining various layer tinting options and their appropriateness given landscape characteristics of the region. We then demonstrate these techniques in various graphic landscape representations of the area. We conclude with a 3D fly-through generated using the LIDAR-derived ground and vegetation data. In this presentation, we aim to demonstrate that LIDAR-derived data sets are emerging as a legitimate alternate for mapping mountainous terrain and vegetation surfaces.