Rural land use spatial allocation in the semiarid loess hilly area in China:Using a Particle Swarm Optimization model equipped with multi-objective optimization techniques  

作　　者：LIU YaoLin LIU DianFeng LIU YanFang HE JianHua JIAO LiMin CHEN YiYun HONG XiaoFeng 

机构地区：[1]School of Resource and Environment Science,Wuhan University,Wuhan 430079,China [2]Ministry of Education Key Laboratory of Geographic Information System,Wuhan University,Wuhan 430079,China

出　　处：《Science China Earth Sciences》2012年第7期1166-1177,共12页中国科学（地球科学英文版）

基　　金：supported in part by the National High-Tech Research & Development Program of China (Grant No.2011AA120304);National Key Technology R&D Program of China(Grant Nos. 2011BAB01B06 and 2006BAB05B06)

摘　　要：Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion,cultivated land conservation,soil erosion and water shortage,and require land use allocation to reconcile these environmental conflicts.We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization (PSO) model in conjunction with multi-objective optimization techniques.Our study focuses on Yuzhong County of Gangsu Province in China,a typical catchment on the Loess Plateau,and proposes a land use spatial optimization model.The model maximizes land use suitability and spatial compactness based on a variety of constraints,e.g.optimal land use structure and restrictive areas,and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation (DWA) method to obtain the optimized land use spatial pattern.The results suggest that (1) approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area;(2) the major reshuffling is slope farmland and newly added construction and cultivated land,whereas the unchanged areas are largely forests and basic farmland;and (3) the PSO is capable of optimizing rural land use allocation,and the determinant initialization method and DWA can improve the performance of the PSO.Semiarid loess hilly areas in China are enduring a series of environmental conflicts between urban expansion, cultivated land conservation, soil erosion and water shortage, and require land use allocation to reconcile these environmental conflicts. We argue that the optimized spatial allocation of rural land use can be achieved by a Particle Swarm Optimization （PSO） model in conjunction with multi-objective optimization techniques. Our study focuses on Yuzhong County of Gangsu Province in China, a typical catchment on the Loess Plateau, and proposes a land use spatial optimization model. The model maximizes land use suitability and spatial compactness based on a variety of constraints, e.g. optimal land use structure and restrictive areas, and employs an improved PSO algorithm equipped with a determinant initialization method and a dynamic weighted aggregation （DWA） method to obtain the optimized land use spatial pattern. The results suggest that （1） approximately 4% of land use should be reallocated and these changes would alleviate the environmental conflicts in the study area; （2） the major reshuffling is slope farmland and newly added construction and cultivated land, whereas the unchanged areas are largely forests and basic farmland; and （3） the PSO is capable of optimizing rural land use allocation, and the determinant initialization method and DWA can improve the performance of the PSO.

关 键 词：spatial allocation rural land use particle swarm optimization multi-objective optimization Loess Plateau 

分 类 号：S793.6[农业科学—林木遗传育种] S157[农业科学—林学]