The optimization of land-use spatio-structure is one of the most important areas of land use management;constructing a spatial optimization model that is based on the micro spatial unit in a bottom-up mode plays an important role in coupling the quan-tity structure and spatial structure effectively.The objective of this research is to develop a land use spatial optimization model based on particle swarm optimization to make spatial decision in land use management.The model is implemented using real data-sets to emulate the process of spatial structure optimization in order to get the best landscape pattern under the control of decision environments.Simulation results revealed that the particle swarm optimization model has the ability to utilize the quantity and spa-tial structure.Furthermore,the result demonstrated that it can be used to stimulate the landscape pattern in designing the appropriate optimization environment,which could land quantity target to the basic spatial units effectively and provide appropriate spa-tio-structure for regional land use space layout decision making.
The indetermination of direction relation is a hot topic for fuzzy GIS researchers. The existing models only study the effects of indetermination of spatial objects,but ignore the uncertainty of direction reference framework. In this paper,first a for-malized representation model of indeterminate spatial objects is designed based on quadruple (x,y,A,μ),then a fuzzy direction reference framework is constructed by revising the cone method,in which the partitions of direction tiles are smooth and continuous,and two neighboring sections are overlapped in the transitional zones with fuzzy method. Grounded on these,a fuzzy description model for indeterminate direction relation is proposed in which the uncertainty of all three parts (source object,reference object and reference frame) is taken into account simultaneously. In the end,case studies are implemented to test the rationality and validity of the model.
LIU YaoLin1,HE JianHua1,YU Yan2 & TANG XinMing3 1 School of Resource and Environment Science,Wuhan University,Wuhan 430079,China
