Assessment the Quality of Life in Karachi City through the Integration of Space and Spatial Technologies

Abstract

This study is an attempt to map and measure the quality of life in the urban area of Karachi, Pakistan, by using Landsat-7 sensor, Enhanced Thematic Mapper (ETM+) combined with Census data through the state-of-the-art Geographic Information System (GIS). For this purpose, the physical environment of the city is determined by the variables of Normalized Difference Vegetation Index (NDVI), surface temperature and land cover/use. These are extracted from the satellite image data through various techniques of remote sensing. On the other hand, the socioeconomic variables were obtained from the 2000 Karachi District Census Reports, to represent the living environment of the city. Finally, the integration of the physical variables with the socioeconomic variables was conducted in a GIS framework using an aggregated Z Sum score approach, in order to derive the quality of life scores for the city of Karachi on the basis of Administrative-Spatial Units called Union Councils (UCs). The results effectively demonstrated the efficiency of the Index raster techniques to evaluate and map the quality of life over the study area. In addition, the GIS techniques also isolated the contributing variables that may be responsible for the spatial variability in the quality of life.

A Critical Review of High and Very High-Resolution Remote Sensing Approaches for Detecting and Mapping Slums: Trends, Challenges and Emerging Opportunities

“…Studies by Lo and Faber [167] and Afsar et al [168] have also made attempts to fuse both remote sensing and socioeconomic data by incorporating land cover data. However, such land cover data is often only available at a coarser classification granularity than what is required for the study of slums.…”