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Interpolating SRTM Elevation Data to Higher Resolution to Improve Hydrologic Analysis
Authors:Younggu Her  Conrad D Heatwole  Moon S Kang
Institution:1. Blackland Research & Extension Center, Texas A&M University, Temple, Texas;2. Department of Biological Systems Engineering, Virginia Tech, Blacksburg, Virginia;3. Department of Rural Systems Engineering, Research Institute for Agriculture and Like Sciences, Seoul National University, Seoul, Korea
Abstract:The Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) has been a valuable resource for hydrological analysis, providing elevation data at a consistent resolution on a near‐global scale. However, its resolution (three arc‐second or 90 m) is sometimes too low to obtain the desired level of accuracy and precision for hydrologic analysis. We evaluated the performance of several methods for interpolating SRTM three arc‐second data to a 30‐m resolution grid to better represent topography and derive terrain characteristics of the landscape. STRM data were interpolated to 30‐m DEMs on a common grid using spline, inverse distance weighting (IDW), kriging (KR), natural neighbor methods, and cubic convolution (CC) resampling. Accuracy of the methods was assessed by comparing interpolated and resampled 30‐m grids with the reference data. Slope, aspect, sinks, and stream networks were derived for the 30‐m grids and compared on a cell‐by‐cell basis to evaluate their performance in reproducing the derivatives. The comparisons identify spline and KR as the most accurate interpolation methods, of which spline is preferred because of its relative simplicity. IDW provided the greatest bias in all methods with artifacts evident in slope and aspect maps. The performance of CC projection directly to a 30‐m resolution was comparable to spline interpolation, thus is recommended as the most convenient method for interpolating SRTM to a higher resolution.
Keywords:geospatial analysis  Shuttle Radar Topography Mission digital elevation model  interpolation  elevation  slope  sink  stream network  geostatistics
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