Fusing landscape accuracy-dependent SRTM elevation data with NGDC and LiDAR data for the Florida coastline

Abstract

Extended coverage digital elevation models (DEMs) including topographic and bathymetric area at moderate resolution are needed for regional-scale hazard modelling. Shuttle Radar Topography Mission (SRTM) provides important intermediate-scale information between coarse resolution data sets of wide area and high-resolution data sets of limited area. Although there are many anthropogenic structures that cause errors in the height of SRTM data, the measurement error is given as a single value for the entire area. The filter residuals in an adaptive multi-scale fusion algorithm were used to evaluate the landscape-dependent accuracy of SRTM elevations over the Florida coastal urban area. With accuracy and employing a stochastic framework to optimally fuse National Geophysical Data Center (NGDC) data, SRTM data and high-resolution light detection and ranging data, single seamless fused DEMs at multiple scales were derived for the coastal area and improved DEM quality at 30 m scale for coastal flood prediction was demonstrated.