Valeriepieris Circles for Spatial Data Analysis

IF 3.3 3区 地球科学 Q1 GEOGRAPHY
Rudy Arthur
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引用次数: 0

Abstract

The Valeriepieris (VP) circle is the smallest circle containing half of the world's population. The Valeriepieris circle acts as a spatial median, splitting spatial data into two halves in a unique way. In this article the idea of the VP circle is generalized and a fast algorithm to compute it is described. This algorithm has been implemented in Python and is available for download and use. The VP circle is compared to other measures of center and dispersion for population distributions and is shown to reflect expected differences between countries and changes over time. By studying the VP circle as a function of the included population fraction, a new way of representing population distributions is constructed, as well as a mathematical model of its expected behavior. Finally a measure of population “centralization” is constructed which measures the tendency of a territory to be dominated by a single population center or to have a more even distribution of population. Thus, VP circles unify measures of population center, dispersion and centralization while also being useful for more detailed modeling efforts.

Abstract Image

用于空间数据分析的 Valeriepieris 圆圈
Valeriepieris (VP)圈是包含世界一半人口的最小的圈。Valeriepieris圆作为空间中位数,以一种独特的方式将空间数据分成两半。本文推广了VP圆的思想,并给出了计算VP圆的一种快速算法。该算法已在Python中实现,并可下载和使用。VP圈与人口分布的中心和分散的其他度量相比较,显示出国家之间的预期差异和随时间的变化。通过研究VP圆作为包含的总体分数的函数,构建了一种新的表示总体分布的方法,并建立了其期望行为的数学模型。最后,构建了一个人口“集中化”的度量,它衡量一个地区由单一人口中心主导或人口分布更均匀的趋势。因此,VP圈统一了人口中心、分散和集中的度量,同时也有助于更详细的建模工作。
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来源期刊
CiteScore
8.70
自引率
5.60%
发文量
40
期刊介绍: First in its specialty area and one of the most frequently cited publications in geography, Geographical Analysis has, since 1969, presented significant advances in geographical theory, model building, and quantitative methods to geographers and scholars in a wide spectrum of related fields. Traditionally, mathematical and nonmathematical articulations of geographical theory, and statements and discussions of the analytic paradigm are published in the journal. Spatial data analyses and spatial econometrics and statistics are strongly represented.
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