Spatial econometrics in an age of CyberGIScience
Spatial econometrics in an age of CyberGIScience
复制标题
DOI：
10.1080/13658816.2012.664276
复制
发表时间：
2012-01-01
影响因子：
5.7
通讯作者：
Rey, Sergio J.
中科院分区：
文献类型：
--
作者：
Anselin, Luc;Rey, Sergio J.
在这篇文章中，我们专注于技术的演变，这是将空间计量经济学方法应用到软件工具中的基础。我们审查不断变化的方法的重点和它们的影响，所需的数据结构和计算基础设施的估计和推断。我们回顾了软件解决方案的演变，从SpaceStat和GeoDa开始，然后转向空间分析函数的PySAL开源库（Rey和Anselin 2010，PySAL：空间分析方法的Python库。在：M。M. Fischer和A. Getis，eds.应用空间分析手册。柏林：施普林格，175-193.）。我们将这些方法与其他软件解决方案进行比较，例如R空间分析例程和最近发布的Stata空间计量经济学功能。我们遵循的审查与讨论的要求和遇到的挑战时，这些软件工具移动到一个CyberGIScience框架。我们专注于高效的数据结构，元数据和出处跟踪的需要，以及高性能计算的要求。最后，我们概述了“空间计量经济学工作台”作为GIScience网络基础设施的核心组成部分的愿景。
In this article, we focus on the evolution of the technology that lies at the basis of implementing spatial econometric methods into software tools. We review the changing methodological emphases and their implications for data structures and computational infrastructure required for estimation and inference. We review the evolution of software solutions, starting with SpaceStat and GeoDa and moving on to the PySAL open source library of spatial analytical functions (Rey and Anselin 2010, PySAL: a Python library of spatial analytical methods. In: M. M. Fischer and A. Getis, eds. Handbook of applied spatial analysis. Berlin: Springer, 175-193.). We compare these approaches with other software solutions, such as the R spatial analytical routines and recently released Stata functionality for spatial econometrics. We follow the review with a discussion of requirements and challenges encountered when moving these software tools into a CyberGIScience framework. We focus on the efficient data structures, the need for metadata and provenance tracking, as well as high-performance computing requirements. We close with the outline of a vision for a 'spatial econometrics workbench' as a core component of cyberinfrastructure for GIScience.