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- W2012495850 abstract "Study of spatial scale effect on regional land-use pattern analysis for construction of spatial model of regional land-use change entails consideration of regional land-use classification system selected and data source used. The effect characteristics of spatial scale on the results of regional land-use pattern analysis was investigated for two different classification systems and different data sources in terms of spatial autocorrelation by empirical study in the Fujian province of China. Fujian province and Longhai County, are selected representing two hierarchical management levels. At County level, two different data sources are used: the 1: 100,000 land use map interpreted from Landsat TM of 2000 and 1:10,000 land use surveying map of 2000. Results showed that all land uses in our study area shows strong positive spatial autocorrelation and VMI of most land uses are scale-dependent. VMI of most land uses decrease with increasing grain size except in Fujian province and VMI of regional land use from more coarse scale land use map decreases more sharply with increasing grain size. Characteristics of fractal dimension are similar to that of spatial autocorrelation in both Counties to a certain extent. When two or three land uses are combined into one, the fractal dimension of it is comparatively larger than the original ones but No general laws in terms of VMI were seen. There may be more variation of VMI of land uses in more detailed classification system. Reducing number of land-use for one classification system may diminish the loss of information of land use area across the range of scale and the effect of spatial scale on regional land-use analysis in certain extent." @default.
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- W2012495850 date "2009-08-01" @default.
- W2012495850 modified "2023-09-24" @default.
- W2012495850 title "Effect of spatial scale on regional land-use pattern analysis in different classification system and data sources" @default.
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- W2012495850 doi "https://doi.org/10.1109/geoinformatics.2009.5293204" @default.
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