Distance is an important and basic concept in geography. Many theories, methods, and applications involve distance explicitly or implicitly. While measuring the distance between two locations is a straightforward task, many geographical processes involve areal units, where the distance measurement can be complicated. This research investigates distance measurement between a location (point) and an area (polygon). We find that traditional polygon‐to‐point distance measurements, which involve abstracting a polygon into a central or representative point, could be problematic and may lead to biased estimates in regression analysis. To solve this issue, we propose a new polygon‐to‐point distance metric along with two algorithms to compute the new distance metric. Simulation analysis shows the effectiveness of the new distance metric in providing unbiased estimates in linear regression.

中文翻译：

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空间分析中的距离：测量，偏差和替代方法

距离是地理学中一个重要的基本概念。许多理论，方法和应用都明确或隐含地涉及距离。尽管测量两个位置之间的距离是一项简单的任务，但是许多地理过程都涉及面积单位，而距离测量可能会很复杂。这项研究调查了位置（点）和区域（多边形）之间的距离测量。我们发现，传统的多边形到点的距离测量涉及将多边形抽象为中心点或代表点，这可能会带来问题，并且可能导致回归分析中的估计偏差。为解决此问题，我们提出了一种新的多边形到点的距离度量以及两种算法来计算新的距离度量。