| Summary: | 碩士 === 臺灣大學 === 生物環境系統工程學研究所 === 98 === The objectives of spatial analysis are to identify areas of locally increased risk and of factors resulting in spatial interaction which can be used in future forecasting. Two data model, raster and vector, are used in the extraction and expression of spatial data. The vector data model is suitable for spatial objects with definite boundary such as buildings, road network, and administrative boundary, while the raster data model is good at describing spatially continuous phenomenon such as rainfall and terrain. Most of the spatial decisions in regional planning involve both kinds of data, and the integration of raster and vector data for data analysis becomes a concern. The objective of this study is to establish a data framework based on raster data model to integrate the natural resources and socioeconomic data for more efficient and effective data analysis and decision in regional planning.
The raster data framework proposed in this study covers both natural resources which is traditionally expressed in raster format, and socioeconomic data that in general is more suitable modeled by vector data form. Techniques such as gravity model, density analysis and spatial interpolation were used to transform the vector data into raster format. Two case studies were presented for demonstration the usability of this proposed data framework.
The proposed raster data framework is proved to be useful in integrating data needed in regional planning decisions. The easy of use and simplicity of raster data model may help to increase the efficiency of spatial data analysis in regional planning.
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