Abstract
Performance and sensitivity of freely available equal resolution space borne digital elevation model derivatives in landslide susceptibility analysis were carried out in a selected part of the Western Ghats, India. ASTER and SRTM digital elevation models having 30m resolution were used to derive the terrain variables such as slope, aspect, relative relief, slope length and steepness, curvature, landform and stream networks. Most of the variables shown spatial variability in distribution pattern, which affects the results of geo-environmental processes analyzed. Sensitivity and performance of each variable derived from the digital elevation models were assessed by preparing a landslide susceptibility index (LSI) maps using the Information Value (InfoVal) technique and was validated through receiver operator characteristics (ROC) curve analysis. LSI maps generated point towards the capability of the SRTM digital elevation model, to correctly generate the terrain variables than the ASTER elevation surface, by giving the accuracy of LSI maps greater than those produced using the ASTER derived parameters (0.77 and 0.72 for SRTM; 0.67 and 0.65 for ASTER). The results of the present study suggest, the SRTM digital elevation data is more sensitive and suitable for terrain analysis and earth surface process modelling than the ASTER elevation data sets, though both possess equal resolutions .DOI: http://dx.doi.org/10.5755/j01.erem.73.2.16385
Highlights
The research related to the earth surface process heavily depends on digital elevation models (DEM) from various sources and resolutions
The results of the present study suggest that the shuttle radar topography mission (SRTM) digital elevation data are more sensitive and suitable for terrain analysis and earth surface process modelling than the ASTER elevation data sets, both possess equal resolutions
The suitability of each elevation dataset in the study area was analysed by comparing the elevation points extracted from the SoI toposheets, ASTER and SRTM through the linear regression analysis
Summary
The research related to the earth surface process heavily depends on digital elevation models (DEM) from various sources and resolutions. The accuracy of the derived elevation surfaces depends on the capacity and expertise of the analyst, who converts the contour lines into the digital format using geographical information systems, which seems to be time consuming and contains non-rectifiable errors. This has been overcome by the increased availability of moderate to high resolution and real near time digital elevation models available from space-borne sources. In the latest version of SRTM data, most of the voids are filled with the available ASTER elevation datasets This has made the SRTM 30-m data a unique, high resolution, errorless digital elevation model, which is ready to use in any application
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