Automated micro-landform classification by combination of satellite images and SRTM DEM

Abstract

The objective of this study is to produce an automated micro-landform map of an alluvial plain by combining land surface parameters (LSPs) from Shuttle Radar Topographic Mission Digital Elevation Model (SRTM DEM) and land cover characteristics from satellite images (Landsat and ASTER) for further flood hazard assessment. Local relief and average elevation from SRTM DEM are designated as LSPs. In addition, channel network is extracted by using multiple Landsat images and r.param.scale function. Modified Normalized Difference Water Index (MNDWI) by Landsat in rainy season can help to separate non-water areas from water and moist surface by determining thresholds. Land cover features are obtained by unsupervised classification by the ISODATA method. Micro-landform units of automated micro-landform map are also classified based on relative position of objects. A case study is conducted in the alluvial plain of the Thu Bon - Vu Gia river, central Vietnam.