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模拟探索聚合和分解中可修改的面积单位问题的“沙盒”。

A simulated 'sandbox' for exploring the modifiable areal unit problem in aggregation and disaggregation.

机构信息

University of Glasgow, School of Geographical & Earth Sciences, Glasgow, UK.

University of Louisville, Dept. of Geographic and Environmental Sciences, Louisville, USA.

出版信息

Sci Data. 2024 Feb 24;11(1):239. doi: 10.1038/s41597-024-03061-1.

Abstract

We present a spatial testbed of simulated boundary data based on a set of very high-resolution census-based areal units surrounding Guadalajara, Mexico. From these input areal units, we simulated 10 levels of spatial resolutions, ranging from levels with 5,515-52,388 units and 100 simulated zonal configurations for each level - totalling 1,000 simulated sets of areal units. These data facilitate interrogating various realizations of the data and the effects of the spatial coarseness and zonal configurations, the Modifiable Areal Unit Problem (MAUP), on applications such as model training, model prediction, disaggregation, and aggregation processes. Further, these data can facilitate the production of spatially explicit, non-parametric estimates of confidence intervals via bootstrapping. We provide a pre-processed version of these 1,000 simulated sets of areal units, meta- and summary data to assist in their use, and a code notebook with the means to alter and/or reproduce these data.

摘要

我们提供了一个基于墨西哥瓜达拉哈拉周边一系列非常高分辨率的基于普查的面元数据集的模拟边界数据的空间测试平台。从这些输入的面元数据中,我们模拟了 10 个空间分辨率级别,每个级别有 5515-52388 个单元和 100 个模拟的区域配置,总计 1000 组模拟的面元数据集。这些数据可以方便地对不同的数据实现和空间粗糙度以及区域配置(可修改区域单位问题,MAUP)的影响进行查询,这些影响可应用于模型训练、模型预测、离散化和聚合过程。此外,这些数据还可以通过自举法方便地生成空间显式的、非参数置信区间估计。我们提供了这些 1000 组模拟面元数据集的预处理版本、元数据和摘要数据,以协助使用,还提供了一个代码笔记本,其中包含更改和/或重现这些数据的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c725/10894218/b8aafd329940/41597_2024_3061_Fig1_HTML.jpg

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