[Assessment of urban location factors from remote sensing]

Abstract

Highly-dynamic, explosively and unmanageably growing megacities arise throughout the world. This rapid alteration within the urban environment often results in a lack of reasonable information for city planning, risk management or site selection. In urban areas conventional techniques for data collection through field work or census are too time-consuming and cost-intensive. Remote sensing of urban areas with a high spatial resolution has the potential to deliver up-to-date area-wide information about the urban morphology and to infer indirectly additional socio-economic parameters. This paper presents the workflow, from the original IKONOS imagery to a land cover classification and to a structuring of homogeneous zones within the city, based on similar urban morphology. Results show a 3-D perspective of alignments, structures and densities of urban areas. Supported by field work data the allocation of homogeneous zones serves for an area-wide computation of the population density distribution as an example for the inference of a socio-economic parameter. GIS-Layer of the built-up areas as well as census data are the basis for an accuracy assessment of the classification result and the population density. The collation of diverse location factors derived from remote sensing eventually leads to an assessment of a location at the test-site Üsküdar, a quarter on the Anatolian side of Istanbul, Turkey.