Abstract
Abstract. Global digital elevation models (DEM) are considered a source of vital spatial information and find wide use in several applications. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (GDEM) and Shuttle Radar Topographic Mission (SRTM) DEM offer almost global coverage and provide elevation data for geospatial analysis. However, GDEM and SRTM still contain some height errors that affect the quality of elevation data significantly. This study aims to examine methods to improve the resolution as well as accuracy of available free DEMs by data fusion techniques and evaluating the results with a high-quality reference DEM. The DEM fusion method is based on the accuracy assessment of each global DEM and geomorphological characteristics of the study area. Land cover units were also considered to correct the elevation of GDEM and SRTM with respect to the bare-earth surface. The weighted averaging method was used to fuse the input DEMs based on a landform classification map. According to the landform types, the different weights were used for GDEM and SRTM. Finally, a denoising algorithm (Sun et al., 2007) was applied to filter the output-fused DEM. This fused DEM shows excellent correlation to the reference DEM, having a correlation coefficient R2 = 0.9986, and the accuracy was also improved from a root mean square error (RMSE) of 14.9 m in GDEM and 14.8 m in SRTM to 11.6 m in the fused DEM. The results of terrain-related parameters extracted from this fused DEM such as slope, curvature, terrain roughness index and normal vector of topographic surface are also very comparable to reference data.
Highlights
A digital elevation model (DEM) is a digital model representing a surface which is presently used in many applications such as hydrology, geomorphology, geology and disaster risk mitigation
This study proposes a geomorphological approach for DEM fusion based on evaluation of the accuracy of Global DEM (GDEM) and Shuttle Radar Topographic Mission (SRTM) in mountain slopes, valleys and flat areas
The mean of absolute error (MAE) and root mean square error (RMSE) of the fused DEM were much improved compared to the available global DEMs
Summary
A digital elevation model (DEM) is a digital model representing a surface which is presently used in many applications such as hydrology, geomorphology, geology and disaster risk mitigation. It is one of the essential inputs in modeling or simulating landscapes as well as dynamic natural phenomena such as flooding, soil erosion and landslides. Aerial photos, high-resolution satellite data or field-surveyed spot height and light detection and ranging (lidar) data are used as inputs to generate high-resolution/high-quality DEMs. Surveying data collections is time consuming and expensive. Even though a good number of aerial photos, highresolution synthetic aperture radar (SAR) and optical remotesensing data are available, it is not always easy and affordable to generate a DEM over large areas
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