Disaster Management

Abstract

The study deals with semi automatic extraction of urban risk related base data and their different generic aspects. Emphasis is given to the building footprint map which is a major base data. The main objective of the study is to extract Building Footprints from High Resolution Imagery using a semi automated approach. In this context the research mainly focuses on developing an integrated extraction to generate the risk related base data in an urban area from high resolution remote sensing images. A multi scale object oriented fuzzy classification of various urban settings was carried out. The method was applied in Dehradun, Uttaranchal, India. The city lies in the high seismic risk zone, also experiencing rapid urbanization due to its newly attained status of a state capital. The extracted base data maps were empirically evaluated by comparing them with visually interpreted reference maps. The evaluation of the extracted base data was carried out by both the quantitative and quality assessment techniques. It was observed that the building footprints extracted from fused Ikonos (PAN+XS) image gave acceptable accuracy for providing better management and better preparedness for any future disasters. Though there are compound problems associated with extraction of information from high resolution images, it is demonstrated from the study that such extraction techniques can be used and improved upo