基于陕西省粮食产量数据的空间自相关分析

Hui Kong, Liangyan Yang
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引用次数: 0

摘要

本文从地理信息系统技术的空间分析出发,将粮食产量数据抽象为GIS中的平面数据形式,通过利用地质数据模型来分析空间中粮食单产的相关性。空间自相关主要以空间自相关系数为特征,主要分为全局空间自相关和局部空间自相关两大类,利用全局和局部Morans的I分析方法和Morans散点图分析陕西省单产变化趋势的具体统计标准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Autocorrelation Analysis based on Grain Yield Data in Shaanxi Province
This article embarks from the spatial analysis of geographic information system technology, the yield of grain yield data abstraction into planar data form in the GIS, by using geological data model to analyze the space of per unit area yield of grain production since the correlation. Spatial autocorrelation is mainly characterized by spatial autocorrelation coefficient, mainly divided into the global spatial autocorrelation and local spatial autocorrelation two categories, the use of global and local Morans' I analysis method and Morans scatter diagram to analyze the specific statistical standard per unit area yield of grain yield change trend of Shaanxi province.
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