Data mining for geo-information of urban land utility:the case of Shanghai
城市土地利用演变信息的数据挖掘——以上海市为例

This paper focuses on GIScience-techniques with the involvement of two technques of data mining,the Markov Chain method and Artificial Neural Network(ANN)method.The results were used to the strategic planning and development of the city of Shanghai.In order to estimate state transtation matrix,firstly the city was divided into 5 zones based on GIS,remote sensing images and electronic maps,and then the total amount of land use in Shanghai in 2002 and 2005 was estimated by Markov Chain method. Secondly,changes in land use types in core areas of Shanghai were forecasted with ANN method which shows the ANN Model 2 (Fig.3)is better than Model 1(Fig.1).This indicates that each one has its strong point,for the ANN method can be better used to forecast directional aspect of land use,and the Markov Chain method can be better used to forecast changes of land use within the zones.Here Markov Chain method was found that is wreath to take the inside variety, ANN considered fit the land that make use in class direction is good.It is further found out that merely for the converted land use types,the standard ANN-BP method gives greater error.This can be explained as the transform process of land use types of Shanghai city is directional,a general ANN-BP arithmetic gives each land type conversion with the same weight function.Although it is self-contradictory in directionality of the transformation,the modified model can still overcome this difficulty.