以曲率為基礎的多邊形縮編技術

Shape-Based Generalization Technique for Polygon GIS Data

陳敏新(Min-Hsin Chen) ； 陳繼藩(Chi-Farn Chen)

《航測及遙測學刊》 11卷4期 (2006/12) Pp. 417-426

https://doi.org/10.6574/JPRS.2006.11(4).5

摘要

地圖縮編在地理資訊系統的資料前處理中是一個重要的工具，其中多邊形圖形的縮編是較為複雜的。由於大部分的多邊形縮編方法，是將多邊形簡化成多邊線後，利用線性的縮編方法進行縮編；此時，將多邊形簡化為多邊線的起始點的決定，將會影響縮編後的結果。本研究主要是利用曲率的特性，來進行多邊形圖形的縮編。首先先計算多邊形上每個節點的曲率值，利用曲率即可找出多邊形上較明顯的特徵節點。透過特徵點，就可以將一個封閉的多邊形分割為數個彎曲的線段，此時再對各個線段進行縮編。在本研究中是利用縮編前後面積的變化率，來調整縮編的程度；其中較低的面積變化容忍率，將會保留較多的節點。最後本研究與Douglas-Peucker的縮編結果進行比較，實驗的結果顯示，所提出的方法在使用相近的節點數下，縮編後的圖形相較於原始圖形具有較少的變形。

關鍵字

地圖縮編 ； 多邊形 ； 曲率

並列摘要

Cartographic generalization represents the process of simplifying a graphic object by reducing the number of its data points. The graphic reduction technique is capable of removing points on a smooth-curve segment, while retaining sharp turning points. Therefore, a good generalization algorithm is not only capable of simplifying data points, but it also retains the similarity of the generalized curve to the original one as close as possible. Among many generalization procedures, polygon shape generalization is considered the most complicated. Since most polygon generalization methods simplify the polygon as poly-lines, therefore the generalized result is significantly affected by the decision of the starting point, which is required in initiating the poly-line generalization algorithm. The purpose of this study is to develop a curvature-based generalization approach for polygon GIS data. Because the curvature can be used to quantitatively measure the shape of a curve, therefore, this approach uses curvature as a generalization index. According to the curvature property, this study classifies the data point of polygon into two types: the critical points and the secondary points. The critical points are the points with relatively large curvature (often with sharp angles) and can be detected automatically by using a curvature threshold. Then the critical points will be used to divide the closed polygon into the curve segments, which can be employed to extract the secondary points. The extraction of the secondary points is performed by ranking the significance of the data points on the curve segments. The significance of the data point will be decided by the curvature and its relative positions to other data points. The data points with larger curvatures and longer distances to neighbor points will have higher chance to be selected as the secondary points, because after simplification, they will not change the shape of the polygon largely. An experiment is performed to compare the proposed method with the Douglas-Peucker method. The test shows that the generalization results of the proposed method have fewer shape distortions, and it can be used to provide an efficient and automatic tool for polygon GIS data generalization.

並列關鍵字

Generalization ； Polygon ； GIS Data