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A Spatial Analysis of Landuse Change and Influencing Factors in Taoyuan Area
Spatial Lag Model
Geographically Weighted Reg
A large amount of immigration attracted by the development of industrial areas and transportation construction causes Taoyuan County to develop rapidly, and leads landuse changes. Influenced by historical and political context, it shows dual developmental traits of Taoyuan City in the north and Chungli City in the south. However, most research on the landuse changes in the past neglects spatial traits of phenomena of geographical distribution, which causes bias against derivation of patterns. The innovation in ways of the spatial statistics helps to handle such problem of spatial effects. The purpose of this research is to help everyone understand the distribution patterns and the influencing factors of the changes of the build-up areas in Taoyuan district, and examine the influence the spatial effects have. This study used spatial autocorrelation index to detect the distribution of the build-up areas and the changes of the spatial patterns; furthermore, we used Spatial Lag Model and Geographically Weighted Regression to probe into the influencing factors of the changes of the build-up areas, and the effectiveness of spatial lag dependence and spatial heterogeneity. The result of the research shows that the build-up areas increased dramatically in Taoyuan area from 1995 to 2006, and the agricultural land of the counterparts eroded fast. Taoyuan City and Chungli City are the cores of the distribution of the build-up areas, and in recent years the districts have developed fastest in peri-urban areas of Chulgli-Pingzhen as well as in peri-urban areas of Taoyuan City, and Gongsi, Guishan. Overall, the villages listed below have stronger possibility of developing the build-up areas: villages of the build-up areas developing faster neighbour villages, of population and employee growth of business, in peri-urban areas, near interchanges, and in urban planning areas or industrial areas; villages of smaller proportion of industrial land; villages of more vacant land and agricultural land. In the spatial effects, the spatial lag dependence and spatial heterogeneity exist in multiple linear regressions, which can effectively correct the derivative bias in pattern respectively with the Spatial Lag Models and Semiparametric Geographically Weighted Regression, and elevate goodness of fit of models. We can know from local regression coefficient of Semiparametric Geographically Weighted Regression that, the changes of population density and growth of employees of tertiary sector in such areas as the northern part of Taoyuan City, Luzhu Township, Guishan Township, Dayuan Township, have higher impact to the changes of built-up area; effects of growth of employees of secondary sector are confined to coastal districts; the proportion of negative effects is the largest in original industrial land of Taoyuan City and Bade City; the changes of build-up areas have higher impact on the distance from interchanges—only around specific interchanges, such as Linkou, Chungli, Neili, Danan—; the distance form train stations, the proportion of original agricultural land, and the proportion of original vacant land, these three in such core areas as Taoyuan City, Bade City, Chulgli-Pingzhen City, are key to the changes of the build-up areas. In totality, the factors of the changes of build-up areas in Taoyuan area show great differences between the north and south, as well as urban and rural. Keywords: Taoyuan, landuse change, spatial effects, Spatila Lag Model, Geographically Weighted Regression
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