Identification / Mapping of Slum Environment using IKONOS Satellite Data: A Case Study of Dehradun, India  Ujjwal Sur Officer Trainee (M.Tech.), Human Settlement Analysis Group, Indian Institute of Remote Sensing (NRSA), Dehradun, India.  Sadhana Jain Scientist, Human Settlement Analysis Group, Indian Institute of Remote Sensing (NRSA), Dehradun, India. B. S. Sokhi Scientist and Head, Human Settlement Analysis Group, Indian Institute of Remote Sensing (NRSA), Dehradun, India. Introduction In the developing countries like India, the acute problem of slum formation is found not only in the big cities but also in medium and small cities and towns. Due to rapid urbanization and consequent haphazard growth, most of these cities have become congested and unhygienic. It is clear that rapid processes of accretion as a result of incessant flows of immigrants caused the present changes in aerial size of slum. In most of the municipal bodies proper up-to-date maps of slums along with proper database and genesis of its growth are not available which create problem in developmental process. Thus, it is important to analyze the slum formation, slum morphology and impact on surroundings to improve quality of life of slum dwellers. Under these circumstances, remote sensing plays a leading role by virtue of its repetitive and synoptic coverage that may become a base map for many government and semi government organization in a very rapidly growing urban area. Objectives of the Study The aim of the study was to locate slums and identify the physical characteristics of the slum areas that could be interpreted through high-resolution Ikonos satellite imagery. To present a comprehensive picture of the slums, two aspects, i.e. spatial distribution and growth, and physical infrastructural services related to slums had been taken into account. High-resolution satellite imagery (Ikonos satellite Data acquired April 2000 was used to detect, identify and delineate the slums in Dehradun to detect the changes that has taken place in terms of new slum development and to map condition of slum environment. GIS was used to identify the slum areas that had fallen under flood vulnerability.
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