The Study Of Urban-ruarl Land Use Smatr Growth Based On BP Neural Networks

With rapid development of urbanization and industrialization,the land resource become more urgent,Limited land resources not only to meet the needs of social and economic development,but also to meet the needs of cultivated land protection,ecological environment protection and people’s quality of life.How to explore the potential of development using smart growth is one of the problems to be solved in the process of urban development.This work focus on Cenxi city in Guangxi province,constructed land use smart growth evaluation index system,Criterion level include Spatial pattern of land,Land utilization and social benefit, ecological environment protection;Index level has19factors.Using method of lattice,we produce357lattice units based on GIS.Finally,the land use smart growth level is measured by BP Artificial Neural Networks, proposed land use smart growth mode for Cenxi city.This work main research results are the following aspects:First,combined with spatial pattern of land,Land utilization and social benefit and ecological environment protection, constructing land use smart growth evaluation index system,combining with the results of various scholars before, finally determine the19evaluation indexes.Second, based on the BP artificial neural networks evaluation method, and calculated output land use smart growth level, include the high smart growth degree,smart growth degree,spread degree,high spread degree.Third, the high smart growth degree of land use is mainly concentrated in Anping, Cencheng, Botang, Nuodong; smart growth degree of land use is mainly concentrated in Shuiwen, Dalong, Malu, Sanbao, Daye;spread degree of land use is mainly concentrated in the Jingzhu, Guiyi;high spread degree of land use mainly in the Nandu, Chengjian, Limu.Fourth, using the evaluation results proposed land use smart growth mode for Cenxi city. Including the urban construction and the surrounding agricultural compact use model;the traffic guides the villages and ecological agriculture model; protect ecological conservation in the open space model.