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Measuring Land Development in Urban Regions using Graph Theoretical Features

Inferring land use from satellite images is studied extensively. In previous studies, the focus was on classifying large regions due to the resolution of available satellite images. Nowadays, very high resolution satellite imagery (Ikonos and Quickbird) allow researchers to focus on more complex land use problems such as monitoring development in urban regions. Solutions to these complex problems may improve life standards of city residents. To this end, we focus on automatically monitoring construction zones using their very high resolution panchromatic satellite images through time. To monitor land development, we obtain sequential images of a selected region. Then, we extract features from each image in the sequence. Comparing values of these features, we expect to measure the degree of land development through time. Here, we introduce four new graph theoretical features to the existing ones. We test all our existing and new features to measure land development in 19 different urban construction zones. Our test set consists of Ikonos satellite images of these regions imaged in separate times.