The Majority Theorem for the Single ( p = 1) Median Problem and Local Spatial Autocorrelation
The Majority Theorem for the Single ( p = 1) Median Problem and Local Spatial Autocorrelation
复制标题
单 ( p = 1) 中值问题的多数定理和局部空间自相关
DOI：
10.1111/gean.12321
复制
发表时间：
2022
影响因子：
3.6
通讯作者：
Kim, Hyun
中科院分区：
文献类型：
--
作者：
Griffith, Daniel A.;Chun, Yongwan;Kim, Hyun
除了大约六篇论文（几乎全部由格里菲斯（共同）撰写）之外，现有文献缺乏关于空间优化（一种流行的地理分析形式）和空间自相关（地理参考数据的基本属性）之间的接口的内容。流行的p中值位置分配问题凸显了这种情况：需求的经验地理分布实际上总是表现出正的空间自相关。当地理空间数据的这一属性实际上与解决方案相关时，它为解决此类空间优化问题提供了额外的被忽视的信息。本文以概念验证的视角，阐明了著名的 1 中值极小和问题的多数定理与局部空间自相关指数之间的联系； LISA 统计似乎是这些后来的统计中更有用的，因为它们更好地包含负空间自相关。这里概述的关系表述导致提出一个称为平等主义定理的新命题。
Except for about a half dozen papers, virtually all (co)authored by Griffith, the existing literature lacks much content about the interface between spatial optimization, a popular form of geographic analysis, and spatial autocorrelation, a fundamental property of georeferenced data. The popularp‐median location‐allocation problem highlights this situation: the empirical geographic distribution of demand virtually always exhibits positive spatial autocorrelation. This property of geospatial data offers additional overlooked information for solving such spatial optimization problems when it actually relates to their solutions. With a proof‐of‐concept outlook, this paper articulates connections between the well‐known Majority Theorem of the 1‐median minisum problem and local indices of spatial autocorrelation; the LISA statistics appear to be the more useful of these later statistics because they better embrace negative spatial autocorrelation. The relationship articulation outlined here results in the positing of a new proposition labeled the egalitarian theorem.