Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This ...Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.展开更多
Based on the exploratory spatial data analysis （ESDA） technique and geographic information system （GIS） platform, with statistic data of counties in 2005, this paper confirms that there is a large population densi...Based on the exploratory spatial data analysis （ESDA） technique and geographic information system （GIS） platform, with statistic data of counties in 2005, this paper confirms that there is a large population density gap between counties in 2005 because the Gini coefficient is 0.55. Population distribution does not change a lot during the past decades, and the southeast China is still much more densely populated than the northwest China. The global spa- tial autoeorrelation of population distribution is obvious because Moran＇s I scores 0.42 and local spatial autocorrelation is partly significant. Climate and elevation are still the main natural influ- encing factors. Meanwhile industrial structure and transportation significantly influence population distribution. Different combinations of natural factors have different effects on population distribution. For a long term, climate and terrain factor stability affect population distribution. But its influence will be weakened by progress of technology. Economic development is the main factor that changes population distribution for a short term.展开更多
The gap between SDA(Spatial Data Analysis)and GIS(Geographical Information Systems )existed for a long time.Presently this problem still remains in spite of a lot of theore tical and practical studies which tr y to fi...The gap between SDA(Spatial Data Analysis)and GIS(Geographical Information Systems )existed for a long time.Presently this problem still remains in spite of a lot of theore tical and practical studies which tr y to find the solu-tion for it.The research background and current situation about how to in tegrate SDA and GIS are introduced at first.The main idea of this article is to make su re what is the best scheme to bridge th e gap between SDA and GIS and how to design it.There are a lot of factors to influ ence the standards to assess such a sc heme,for instance,the attitude of users and GIS developers,the framework and related functions of current available GI S software in the market and so on.But the two most important ones of them are effic iency and flexibility of the scheme i tself.Efficiency can be measured by the conve-nient extent and temporal length when it is used for carrying out SDA.Flex ibility means users can define their own SDA methods.The best integration schem e should satisfy the two standards at the same time.A group of functions,which can be combined to implement any SDA meth od,are defined in order to design such an integration scheme.The functio ns are divided into five classes according to their properties.展开更多
基金ProjectsupportedbytheNationalScienceFoundationofSurveyingandMappingofChina (No .990 1 3) .
文摘Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.
基金supported by the National Natural Science Foundation of China(Key Program,Grant No. 40830741)the National Natural Science Foundation of China (Grant No.41101138)
文摘Based on the exploratory spatial data analysis （ESDA） technique and geographic information system （GIS） platform, with statistic data of counties in 2005, this paper confirms that there is a large population density gap between counties in 2005 because the Gini coefficient is 0.55. Population distribution does not change a lot during the past decades, and the southeast China is still much more densely populated than the northwest China. The global spa- tial autoeorrelation of population distribution is obvious because Moran＇s I scores 0.42 and local spatial autocorrelation is partly significant. Climate and elevation are still the main natural influ- encing factors. Meanwhile industrial structure and transportation significantly influence population distribution. Different combinations of natural factors have different effects on population distribution. For a long term, climate and terrain factor stability affect population distribution. But its influence will be weakened by progress of technology. Economic development is the main factor that changes population distribution for a short term.
文摘The gap between SDA(Spatial Data Analysis)and GIS(Geographical Information Systems )existed for a long time.Presently this problem still remains in spite of a lot of theore tical and practical studies which tr y to find the solu-tion for it.The research background and current situation about how to in tegrate SDA and GIS are introduced at first.The main idea of this article is to make su re what is the best scheme to bridge th e gap between SDA and GIS and how to design it.There are a lot of factors to influ ence the standards to assess such a sc heme,for instance,the attitude of users and GIS developers,the framework and related functions of current available GI S software in the market and so on.But the two most important ones of them are effic iency and flexibility of the scheme i tself.Efficiency can be measured by the conve-nient extent and temporal length when it is used for carrying out SDA.Flex ibility means users can define their own SDA methods.The best integration schem e should satisfy the two standards at the same time.A group of functions,which can be combined to implement any SDA meth od,are defined in order to design such an integration scheme.The functio ns are divided into five classes according to their properties.
