空间数据科学的开源软件

IF 3.3 3区 地球科学 Q1 GEOGRAPHY Geographical Analysis Pub Date : 2022-06-28 DOI:10.1111/gean.12339
Luc Anselin, Sergio J. Rey
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引用次数: 7

摘要

自2006年专门讨论“社会科学空间分析软件的最新进展”的《地理分析》特刊问世以来,空间分析软件工具的开发取得了很大进展(Rey and Anselin 2006)。自该问题出版以来的15年左右的时间里,空间分析软件领域发生了重大变化。可以说,推动这些变化的三个重要且有些相关的现象可以区分开来:空间分析嵌入到空间数据科学中;在实证工作中越来越多地认识到开放科学/开源原则;以及越来越多地采用识字编程的观点。
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Open Source Software for Spatial Data Science

Much progress has been made in the development of software tools for spatial analysis since the special issue of Geographical Analysis appeared in 2006, devoted to “Recent advances in software for spatial analysis in the social sciences” (Rey and Anselin 2006). The 15 some years since the publication of the issue have been marked by major changes in the spatial analytical software landscape. Arguably, three important and somewhat related phenomena can be distinguished that drove these changes: the embedding of spatial analysis into spatial data science; the growing recognition of open science/open source principles in empirical work; and the increasing adoption of a literate programming perspective.

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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.
期刊最新文献
Issue Information The Multiple Gradual Maximal Covering Location Problem Correction to “A hybrid approach for mass valuation of residential properties through geographic information systems and machine learning integration” Plausible Reasoning and Spatial‐Statistical Theory: A Critique of Recent Writings on “Spatial Confounding” The Regionalization and Aggregation of In‐App Location Data to Maximize Information and Minimize Data Disclosure
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