Impact of Lidar Nominal Post-spacing on DEM Accuracy and Flood Zone Delineation

Lidar data have become a major source of digital terrain information for use in many applications including hydraulic modeling and flood plane mapping. Based on established relationships between sampling intensity and error, nominal post-spacing likely contributes significantly to the error budget. Post-spacing is also a major cost factor during lidar data collection. This research presents methods for establishing a relationship between nominal post-spacing and its effects on hydraulic modeling for flood zone delineation. Lidar data collected at a low post-spacing (approximately 1 to 2 m) over a piedmont study area in North Carolina was systematically decimated to simulate datasets with sequentially higher post-spacing values. Using extensive first-order ground survey information, the accuracy of each DEM derived from these lidar datasets was assessed and reported. Hydraulic analyses were performed utilizing standard engineering practices and modeling software (HEC-RAS). All input variables were held constant in each model run except for the topographic information from the decimated lidar datasets. The results were compared to a hydraulic analysis performed on the un-decimated reference dataset. The sensitivity of the primary model outputs to the variation in nominal post-spacing is reported. The results indicate that base flood elevation does not statistically change over the post-spacing values tested. Conversely, flood zone boundary mapping was found to be sensitive to variations in post-spacing. Introduction Airborne light detection and ranging (lidar) remote sensing has become a widely-used method for acquiring elevation data for trees, shrubs, buildings, and Earth’s terrain. Data Impact of Lidar Nominal Post-spacing on DEM Accuracy and Flood Zone Delineation George T. Raber, John R. Jensen, Michael E. Hodgson, Jason A. Tullis, Bruce A. Davis, and Judith Berglund users and vendors commonly referred to these data products as digital surface models (DSMs). The lidar data can be further processed to create bare-earth digital elevation models or DEMs (Jensen, 2000). DEMs are utilized in a variety of geographic applications (Cowen et al., 2000) including hydraulic modeling for flood zone mapping (e.g., Kenward et al., 2000; Marks and Bates, 2000; Manson et al., 2002; Omer et al., 2003). As the DEM is a primary input to this process, it is reasonable to suggest that the accuracy of the DEM surface has an effect on the output of the models and thus the modeled flood extent (often referred to as the flood zone). In 1997, FEMA identified a need to update their database of approximately 100,000 flood insurance rate maps (FIRMs) and therefore initiated the Map Modernization Program (FEMA, 2002 and 2003). As a response to this effort and to the flood damage sustained during the 2000 hurricane season, the State of North Carolina with the support of FEMA undertook a massive project called the North Carolina Floodplain Mapping program to update the FIRMs for the entire state (NCFMP, 2002 and 2003). Many factors are known to contribute to the accuracy of a DEM derived from lidar data. The nominal post-spacing (or average ground spacing between lidar postings) is believed to be a significant contributor to the overall vertical error prevalent in the lidar-derived DEM (Hodgson et al., 2004). However, unlike other factors that contribute to the overall error budget such as terrain variability and land-cover, postspacing represents a significant portion of overall project costs. A lower post-spacing generally requires a more sophisticated sensor system with a higher pulse rate, a lower altitude over-flight, a narrower scan angle, or a combination of these variables that results in the need for more flightlines. In addition, significantly more personnel time and computing resources (processor speed, RAM, mass storage, etc.) are required to process lower post-spacing lidar data. The goal of this research was to establish an empirical relationship between lidar post-spacing and DEM accuracy within the study area in the piedmont of North Carolina. Further, this research investigated the nature of this relationship on flood zone mapping. This research focused on using established methods and models for statewide mapping efforts currently planned and underway in the United States. Namely, this included the usage of the United States Army Corps of Engineers HEC-RAS and HEC-GEORAS hydraulic model, and the triangulated irregular network (TIN) as the PHOTOGRAMMETRIC ENGINEER ING & REMOTE SENS ING J u l y 2007 793 George T. Raber is with the Department of Geography and Geology, School of Ocean and Earth Sciences, University of Southern Mississippi, 118 College Drive, #5051, Hattiesburg, MS 39406 ([email protected]). John R. Jensen and Michael E. Hodgson are with the Department of Geography, University of South Carolina, Columbia, South Carolina 29208. Jason A. Tullis is with the Department of Geosciences and The Center for Advanced Spatial Technologies at the University of Arkansas. Bruce A. Davis is with the Interagency Modeling and Atmospheric Assessment Center, EP&R Portfolio, Science and Technology Directorate, Department of Homeland Security. Judith Berglund is with Science Systems and Applications, Inc. (SSAI), John C. Stennis Space Center, MS 39529. Photogrammetric Engineering & Remote Sensing Vol. 73, No. 7, July 2007, pp. 793–804. 0099-1112/07/7307–0793/$3.00/0 © 2007 American Society for Photogrammetry and Remote Sensing 05-058 6/11/07 9:37 AM Page 793