• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.609-611
• /
• 2003

In the past, it has always been time -consuming and labor intensive to extract and update Digital Elevation Model (DEM). How to extract highly accurate DEM with efficiently and the most economical method has always been a cutting-edge topic in the remote sensing filed. This paper discusses using PCI Geomatica OrthoEngine software to extract DEM automatically from ASTER stereo satellite images (15 m resolution). For the study, DEMs were extracted for two sites in Taiwan, and the resulting DEMs were found to have RMS errors between 10 and 16 meters in both flat and mountainous areas.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.259-261
• /
• 2008

GIS-based spatial data integration tasks have used exhaustive thematic maps generated from sparsely sampled data or satellite-based exhaustive data. Due to a simplification of reality and error in mapping procedures, such spatial data are usually imperfect and of different accuracy. The objective of this study is to carry out a sensitivity analysis in connection with input topographic data for landslide hazard mapping. Two different types of elevation estimates, elevation spot heights and a DEM from ASTER stereo images are considered. The geostatistical framework of kriging is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. The effects of different accuracy arising from different terrain-related maps on the prediction performance of landslide hazard are illustrated from a case study of Boeun, Korea.