A simulated ‘sandbox’ for exploring the modifiable areal unit problem in aggregation and disaggregation

• Published in: Scientific data Vol. 11; no. 1; p. 239
• Main Authors: Nieves, Jeremiah J., Gaughan, Andrea E., Stevens, Forrest R., Yetman, Greg, Gros, Andreas
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 24.02.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 706/2808; 706/648/697; 706/689/680; Censuses; Data Descriptor; Decision making; Disaggregation; Geography; Humanities and Social Sciences; Machine learning; Mexico; multidisciplinary; Population; Science; Science (multidisciplinary); Mexico
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-024-03061-1

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.