Extraction and classification of urban areas on SPOT images

The study of urban area is an important problem in image interpretation. It is interesting to be able to analyse town development, to make streets maps automatically or just, to mask urban areas in satellite images. The objective of this study is to extract urban areas from remote sensing images and to make a classification of these areas. The proposed method combines different types of operators in order to improve the final detection. At first, the authors separate urban areas from the other type of regions (vegetation, rivers...). Then these urban areas are segmented according to the thoroughfares to obtain urban districts. Finally, the authors define a measure of urban density. This study is performed by IRIT and has been partially funded by CNES agency in the frame of the CNES program on studies and research on automatic analysis and interpretation of SPOT images