Spatial Data Mining And Urban Land Grading

Modern spatial data acquisition technology and computer network technology is developing rapidly,making GIS spatial data in the rapid expansion.Although these spatial data meets the human's potential demand for study of Earth's resources and environment,and broadens the sources of information available,the complexity and size of the data of general affairs is far from the spatial data.Currently,space data processing means is relatively straggly,so it makes spatial data contained in the wealth of knowledge resources to be shelved.In order to meet the growing demand of high-level information for spatial data,spatial data mining theory and the technology has come into being.Spatial Data Mining is a research branch of data mining,and the spatial clustering analysis is an important area of research of spatial data mining.Spatial clustering algorithm has been a very active research topic on spatial Data Mining Research field,and has been widely studied for many years. However,the scope of the study mainly concentrated in the cluster analysis based on distance.In this paper,a systematic study of traditional clustering algorithms of spatial data is made,such as hierarchical clustering algorithm,and we conclude that this clustering algorithm is summed up easily into local optimum.In the process of realization does not take into account the overall situation of target groups to maintain distribution,and is more sensitive to the isolated information.Because of these deficiencies,it greatly limits the clustering algorithm in the field of GIS Application.Meanwhile,genetic algorithms mimic biological evolution process of natural selection and evolution mechanism,and it is a global optimization algorithm based on a random group.So we can be considered the use of genetic algorithms to solve the problem of spatial clustering.Considering the relationships between party and entirety of Clustering object's feature,we came out of a method of combining the genetic algorithm and the conventional clustering,to design a spatial clustering algorithm based on genetic algorithm.After the specific theoretical analysis and simulation test,found that the method is feasible,and indeed reached a theoretical requirements in the course of specific test.Finally,we analysis the status of distinction of grading of the land,and concludes that artificial subjective factors is a dominated factor.using improved of spatial clustering algorithm,as the basic premium for the sample area,we do the work of Land Classification,and get the fairly satisfactory results.Although there are some fields not to be studied,this will be the important research area for the future.