Unsupervised Geo-Demographic Classification of City-Area Using Multimodal Multimedia Data

Geo-demographical segmentation of a city area is of interest in many social as well business contexts. In this paper, we present a new method for demographic segmentation of a city by analyzing satellite imagery and other forms of neighborhood data. We explore the feature-set that can be used for effective geo-demographic segmentation of satellite imagery. In particular, we study the effectiveness of a few color and texture features for the purpose. Our method essentially involves analysis of large volume of image data, for which we have devised a two-step process and approximate clustering methods. We have experimented with satellite images of two major cities to illustrate the results. We have integrated telecom data that signify human activity with satellite imagery to achieve enhanced segmentation of the demographic regions.