Detection of Urban Housing Development Using Multisensor Satellite Data and Maps

Detection of land-cover / land-use changes is an important process in monitoring and managing urban development and natural resources, because it provides quantitative analysis of the spatial distribution in the population of interest. A large number of change-detection techniques have been developed, but little has been done to detect detailed changes, such as urban housing development, using satellite data. In this study a new attempt was carried out to extract urban housing changes from satellite data. For this purpose Landsat TM, SPOT pan and map data were used in the extraction. The two satellite data were merged. A cooccurrence-matrix-based filtering algorithm was developed for the accuracy improvement of the classified houses. An axis-oriented linking method and some logical segmentation methods were developed to complete the classified water areas. Mathematical morphology was used to increase the accuracy of the classified green areas. By integrating the housing information extracted from satellite data and that of a former map, the newly developed houses were highlighted. The new attempt was tested in the urban area of Shanghai, China. The average accuracy of the house extraction was 86 %.