title: Irregular tessellated surface model map algebras to define flow directions and delineate catchments using LiDAR bare earth sample points
Creators: name: Gabrisch, Gerald B.
Publisher: name: Western Washington University
Year: 2011

description: <p>Flow directions and catchment algorithms have historically utilized raster-based data models. A significant body of literature focuses on raster-based interpolation errors, and the subsequent surface reconditioning to compensate for those errors, that together degrade the accuracy of the derived flow directions and catchments. This research seeks to improve upon the raster-based approach by developing and evaluating a vector-based approach to generating flow directions and delineating catchments that preserves the accuracy of the input point data through the use of irregular tessellated surface models. Specifically, the Python computer programming language was used in conjunction with a geographic information system (GIS) to develop ITSMHydro, a custom toolset that creates a Delaunay triangulated irregular network (TIN) from LiDAR bare-earth sample point data, and subsequently generates flow directions, delineates basins, and processes spurious sink catchments. Surface model accuracy, and area, shape, and overlap of the resulting catchments were compared with catchments delineated using industry-standard raster-based digital terrain models. The vector-based approach implemented through ITSMHydro was limited to file sizes less than approximately 120,000 LiDAR strikes that processed in approximately 30 hours, whereas the industry-standard raster-based approach transformed 111,000,000 LiDAR strikes across the study area into a 3-feet pixel surface model and generated catchment boundaries in approximately 36 hours. A root mean square analysis of surface models indicates that surface model quality is more heavily degraded when LiDAR sample points are interpolated to raster grids as opposed to surface models relying on Delaunay TIN interpolation, suggesting that the vector-based approach maintains the quality and precision of the LiDAR input data. For the four test areas in which the two approaches were compared, ITSMHydro generated catchments that were generally smaller (percent difference in areas ranged from -83.97% to 9.39%) and with more complex boundaries (i.e. lower isoperimetric quotient in 3 out of 4 test areas) than the associated raster-based catchments. Coefficient of areal correspondence (CAC), a measure of overlap between catchments generated by the two methods where a value of 1 indicates perfect overlap, ranged from 0.28 to 0.80 in the four test areas. Given the lower relative accuracy of raster-based surface models evident in the study area, these differences suggest use of the raster-based approach may compromise accuracy in area, shape, and location of the resulting catchments. A vector-based approach that preserves the accuracy of the input data is preferred, especially in areas of low topographic relief. The file size constraints limit application of the approach developed herein, however, at least until technological advances and/or code revisions improve computer processing speed and file size capacity.</p>