A series researches have been made on how to extract road features from satellite data. The main Methods include edge detection and line finding

line filtering and using spatial relationships to extract road features. Another approach to the extraction of road networks involves the use of GIS and rule and knowledge based algorithms. Several workers have examined mathematical morphology as a means of extracting linear features from satellite data. However

many problems are still remained to solve. In this paper

algorithms of mathematical morphology and analysis of road networks are applied to extract road networks digitally from classified imagery to update digital databases and map. The first step involves road image two valued

removes noise data

break line connection

thin and raster convert to vector. The second is analysis the vector networks

connection and selection and eliminate the road arcs. Finally

the Douglas Peuker algorism is used to smooth the road networks. The test area is Nanjing Jiangning County. The satellite data is SPOT multi spectral image. IKONOS high resolution image is tested too. The comparison is made between the results of the extracted road networks and visual interpretation from location accuracy and extraction accuracy. The results described here show that the technique appears to be most effective in areas of recent road development. It is very useful for land managing and planning and is an effective method to update GIS and map.