Scale and local modeling: new perspectives on the modifiable areal unit problem and Simpson’s paradox

Scale and local modeling: new perspectives on the modifiable areal unit problem and Simpson’s paradox
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尺度和局部建模:可修改面积单位问题和辛普森悖论的新视角

DOI:
10.1007/s10109-021-00371-5
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发表时间:
2022
影响因子:
2.9
通讯作者:
Sachdeva, M.
Sachdeva, M.
中科院分区:
地球科学3区
文献类型:
--
作者:
Fotheringham, A. Stewart;Sachdeva, M.

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“空间尺度”或简称“尺度”的概念隐含在任何关于全球与局部模型的讨论中。局部模型的理论基础是,全球尺度(这里的“全球”仅指预定义的感兴趣区域内的所有位置)可能是进行空间过程分析的不正确尺度;替代方案是局部尺度(这里的“局部”指单个位置)。在这里,我们将探讨两个著名的规模问题的背景下,当地的建模:可修改的面积单位问题(MAUP)和辛普森悖论。在这样做的时候,我们强调,规模效应发挥两个非常不同的作用,在任何考虑本地与全球建模。首先,我们研究的敏感性的全球和本地模型的MAUP和显示如何在全球模型中的MAUP的影响是一个函数的过程在空间上变化的程度。这对MAUP产生了新的见解:它源于进程的属性而不是数据的属性。然后,我们强调的极端差异,可以导致校准全球和本地模型,以及如何辛普森悖论可以在这种情况下出现。在对MAUP的研究中,规模被视为衡量数据在任何形式的建模之前被聚合的程度;在辛普森悖论的研究中,规模是指模型被校准的地理实体。
The concept of ‘spatial scale’, or simply ‘scale’ is implicit in any discussion of global versus local models. Theraison d’etreof local models is that a global scale (where here ‘global’ simply refers to all locations within a predefined area of interest) might be the incorrect scale at which to undertake any analysis of spatial processes; the alternative being a local scale (where here ‘local’ refers to individual locations). Here we explore two well-known scale issues in the context of local modeling: the modifiable areal unit problem (MAUP) and Simpson’s paradox. In doing so, we highlight that scale effects play two very different roles in any consideration of local versus global modeling. First, we examine the sensitivity of global and local models to the MAUP and show how the effects of the MAUP in global models are a function of the degree to which processes vary over space. This generates a new insight into the MAUP: it results from the properties ofprocessesrather than the properties ofdata. Then we highlight the extreme differences that can result when calibrating global and local models and how Simpson’s paradox can arise in this context. In the examination of the MAUP, scale is treated as a measure of the degree to which data are aggregated prior to any form of modeling; in the study of Simpson’s paradox, scale refers to the geographical entity for which a model is calibrated.
DOI: 10.1080/01621459.2018.1529595
发表时间: 2019-04-10
影响因子: 3.7
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DOI: --
发表时间: 1981
期刊:
影响因子: --
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DOI: 10.1080/24694452.2019.1704680
发表时间: 2020-02-11
影响因子: 3.9
作者:
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DOI: 10.1080/13658816.2020.1720692
发表时间: 2020-02-08
影响因子: 5.7
作者:
Li, Ziqi;Fotheringham, A. Stewart
通讯作者: Fotheringham, A. Stewart
DOI: 10.1136/bmj.292.6524.879
发表时间: 1986-03-29
影响因子: 105.7
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