k-最近邻算法
地理
背景(考古学)
地图学
分布(数学)
空间语境意识
空间色散
空间生态学
计算机科学
数据挖掘
人工智能
数学
生态学
遥感
物理
数学分析
光学
考古
生物
出处
期刊:CRC Press eBooks
[Informa]
日期:2023-02-06
卷期号:: 53-76
标识
DOI:10.1201/9781003304395-4
摘要
Patterns of distribution of geographic phenomena, such as plants and animal populations, are the basis for researchers to understand the dynamics of geographical objects or events (henceforth geographic events) in the context of environmental influences. Nearest neighborhood index (NNI) is one of the earliest and easiest indices to describe a spatial distribution of geographic events. It uses the average nearest neighbor distance between events to assess how, and to what degree, the distribution of events or objects is clustered or dispersed in space. Such assessment of the degree of clustered or dispersion of a spatial pattern is then inferred and used to understand the mechanisms behind the spatial relationships among geographic events and their interactions with the surrounding environment.
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