The Effect of Lidar Posting Density on Dem Accuracy and Flood Extent Delineation a Gis-simulation Approach

Recently a number of local communities and a few statewide agencies have undertaken efforts to acquire more accurate digital elevation surfaces for various applications including flood hazard mapping. The technology most widely adopted for this purpose has been LIDAR remote sensing. The acquisition of a spatially dense set of elevation postings representing the " bare " ground may be the greatest factor in deriving an accurate elevation surface. Creating such a dense elevation dataset using LIDAR remote sensing requires two elements – a high raw posting density during the collection phase and rigorous post-processing to identify the " ground " returns. A higher posting density generally requires significantly higher cost associated with the LIDAR sensor and the addition technical personnel time and computing resources (processor speed, RAM, storage space, etc.) that are required to process higher posting densities to produce digital elevation models (DEMs) of the bare ground. The goal of this research is to develop a relationship between LIDAR posting density and DEM accuracy. Specifications for data collection/processing in future mapping efforts could use this empirical relationship to match target accuracy requirements with data collection/processing parameters. For this research, a simple GIS simulation was developed in order to create a LIDAR data collection over two GIS generated surfaces. The vertical and surface form accuracy of the resulting DEMs are compared to the posting density in order to establish the relationship between these variables. The research further investigates the sensitivity of horizontal accuracy (for flood extent delineation) using the generated DEMs. The results indicate that these relationships exist and validate the need for an empirical study to explore the patterns further.