Suitability of Aster and SRTM dems, and satellite imagery in detailed geomorphological mapping in Dzanani Area of Makhado Local Municipality, Limpopo Province, Republic of South Africa

• Main Author: Motene, Sylvia
• Other Authors: Odhiambo, B. O. O.
• Format: Others
• Language: en
• Published: 2018
• Subjects: Geomorphological mapping; Satellite imagery; GIS; Linear spectral unmixing; 910.2850968257; Remote-sensing images > South Africa > Limpopo; Satellites > South Africa > Limpopo; Geomorphological mapping > South Africa > Limpopo; Geomorhology > Maps > South Africa > Limpopo; Geographic information systems > South Africa > Limpopo
• Online Access: Motene, Sylvia (2018) Suitability of Aster and SRTM Dems, and satellite imagery in detailed geomorphological mapping in Dzanani Area, Limpopo Province, Republic of South Africa, University of Venda, Thohoyandou, South Africa,<http://hdl.handle.net/11602/1227>; http://hdl.handle.net/11602/1227

MENVSC (Geography) === Department of Geography and Geo - Information Sciences === Detailed geomorphological mapping is important for monitoring environmental phenomena, it is therefore crucial that the methods employed for mapping are accurate. The basis of remote sensing for geomorphological work is moving from the consideration of whether satellite data are accurate for landform mapping to how surfaces of interest can be defined from remote sensing data, since earlier approaches of mapping are deemed costly and tedious. The aim of this study is to assess the suitability of ASTER and SRTM DEMs, and satellite imagery in detailed geomorphological mapping. Field survey and aerial photo interpretation were used to prepare a reference geomorphological map for comparisons. A similar approach of demarcating landform boundaries from aerial photographs was implemented to segment the DEMs into landform classes. The software packages that were used for processing the satellite data to create detailed geomorphological maps are QGIS with GRASS and SAGA plugins, and ENVI. The resultant geomorphological units’ maps from the DEMs when compared with the reference geomorphological map, show that the automated classification technique has advantages in terms of its efficiency and reproducibility. Nevertheless, distinct limitations of the technique are apparent and the technique is not suitable for detailed geomorphological mapping in the proposed study area. === NRF