As a key element for land use cover change research, change detection technique is of urgent demands and has great
potential in scientific applications. Conflation is the process of combining the information from two (or more) geodata
sets to make a master data set that is superior to either source data set in either spatial or attribute aspect. The objectives
of conflation include increasing spatial accuracy and consistency, and updating or adding new spatial features into data
sets. Based on the analysis and summarizations of researched home and aboard, the paper focused on Land Use/Cover
Change detection using feature database of basic types based on vector-image data conflation, that is : Combining of
Land use map and RS image, features(grey feature, texture feature and shape feature) are extracted. This methodology
belongs to "Feature class" of LUCC. It should be pointed out that the researches must be focused on the land use span
other then traditional methods of the pixels. Each spans of T2 will be classified according to the minimum Euclidean
distance to the T2 sample span accepted, and the corresponding land use type will be assigned to the current patch,
Change information are extraction automatically based on Boolean operations. The method is tested on the Quick Bird
images of a district in Wuhan and the precision of the results is high as 92.6% (in urbanization).The experimental results
demonstrate that the proposed method can cut down the computational costs and improve the accuracy.
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