2026-07-22T01:18:03Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:18942 2024-03-06T11:03:01Z ddc:004 open_access

Investigating MAUP Effects on Census Data Using Approximately Equal-Population Aggregations (Short Paper) Lin, Yue Xiao, Ningchuan Census heuristics modifiable areal unit problem spatial aggregation spatial autocorrelation The modifiable areal unit problem (MAUP) can significantly impact the use of census data as different choices in aggregating geographic zones can lead to varying outcomes. Previous research studied the effects using random aggregations, which, however, may lead to the use of impractical and unrealistic zones that deviate from recommended census geography criteria (e.g., equal population). To address this issue, this study proposes the use of approximately equal-population aggregations (AEPAs) for exploring MAUP effects on various statistical properties of census data, including Moran coefficients, correlation coefficients, and regression statistics. A multistart and recombination algorithm (MSRA) is used to generate multiple sets of high-quality AEPAs for testing MAUP effects. The results of our computational experiments highlight the need for more well-defined census geographies and realistic alternative zones to fully understand MAUP effects on census data. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Yue Lin and Ningchuan Xiao 2023 Is Part Of LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.GIScience.2023.47 urn:nbn:de:0030-drops-189428 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.47 eng https://creativecommons.org/licenses/by/4.0/legalcode