環境資源及社經資料網格地理資料庫之建置

Abstract

空間分析之目的不外乎由空間型態尋求資料趨勢以提升資料可用性、探討空間分析結果之原因及建立模式已達到預測研究事件未來發展等。一般空間分析所使用的資料模型分為向量式(Vector)及網格式(Raster)等兩大類，兩種資料格式各有其優缺點及其適用對象，網格式資料適合用來記錄具有連續變化特性的空間資料；而向量式資料較適於表示非連續且有確切空間邊界或位置的空間資料。因空間決策常會同時涉及自然資源與社會經濟資料，為更有效的結合這兩類資料，本研究嘗試以網格資料模型作整合建立自然環境與人文環境的地理資料庫，以提升區域及資源規劃管理相關決策之目的。 研究中建置之網格式資料庫架構涵蓋區域規劃所需的自然環境(氣象、地形、地表覆蓋)及人文環境資料(土地利用、交通路網、公共設施)，因原始資料包含網格式及向量式資料結構，研究中乃以重力模型(gravity model)、密度圖(density maps)及空間內差等方式將原以點、線、面的形式儲存的向量式資料轉換為網格資料，以網格資料模型整合與區域規劃決策相關的各類資料建立環境資源相關資料及人文環境資訊之網格空間資料庫架構，研究中並以兩案例研討所建立之資料庫架構之可用性。 本研究所建置之網格式資料庫架構，改善向量式及網格式資料結構已往在空間合併使用上的困擾，使其透過單一網格式資料概念，運用於區域全面性規劃及相關決策，達到提升空間資料及空間資訊可用性。

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.