Applying co-operative operators for urban-area detection using SPOT imagery

The study of urban area is an important problem in image interpretation. It is interesting to be able to analyze town development on satellite images or to mask urban areas. The objective of this study is to extract urban areas from remote sensing images and to make a classification of these areas. The detection algorithm combines different types of operators in order to improve the final detection. We separate urban areas from the other type of regions (vegetation, rivers . . .). Then the urban areas are classified into various under-classes (dense urban areas, suburbs . . .). This study has been performed by IRIT in the frame of the CNES program on studies and research on automatic analysis and interpretation of SPOT images.