LOCAL INDICATORS OF SPATIAL ASSOCIATION - LISA
LOCAL INDICATORS OF SPATIAL ASSOCIATION - LISA
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DOI：
10.1111/j.1538-4632.1995.tb00338.x
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发表时间：
1995-04-01
影响因子：
3.6
通讯作者：
ANSELIN, L
中科院分区：
文献类型：
--
作者：
ANSELIN, L
地理信息系统（GIS）中的可视化、快速数据检索和操作能力，产生了对探索性数据分析新技术的需求，这些技术侧重于数据的“空间”方面。在这方面，确定空间联系的地方模式是一个重要问题。在本文中，我概述了一个新的一般类的地方指标的空间关联（丽莎），并显示它们如何允许分解的全球指标，如莫兰的我，到每个观察的贡献丽莎统计服务于两个目的。一方面，它们可以被解释为局部非平稳性区域或热点的指标，类似于GI和G（i）*; Getis和Ord（1992）的统计数据。另一方面，它们可以用来评估单个位置对全局统计量大小的影响，并识别“离群值”，如Anselin的Moran散点图（1993 a）。的丽莎统计的属性进行了初步评价，为当地的莫兰，这是适用于非洲国家的冲突的空间格局的研究，并在一些蒙特卡洛模拟。
The capabilities for visualization, rapid data retrieval, and manipulation in geographic information systems (GIS) have created the need for new techniques of exploratory data analysis that focus on the ''spatial'' aspects of the data. The identification of local patterns of spatial association is an important concern in this respect. In this paper, I outline a new general class of local indicators of spatial association (LISA) and show how they allow for the decomposition of global indicators, such as Moran's I, into the contribution of each observation The LISA statistics serve two purposes. On one hand, they may be interpreted as indicators of local pockets of nonstationarity, or hot spots, similar to the Gi and G(i)*; statistics of Getis and Ord (1992). On the other hand, they may be used to assess the influence of individual locations on the magnitude of the global statistic and to identify ''outliers,'' as in Anselin's Moran scatterplot (1993a). An initial evaluation of the properties of a LISA statistic is carried out for the local Moran, which is applied in a study of the spatial pattern of conflict for African countries and in a number of Monte Carlo simulations.