{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T01:04:20Z","timestamp":1772759060583,"version":"3.50.1"},"reference-count":66,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T00:00:00Z","timestamp":1753747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangxi Science and Technology Major Program","award":["AA23062039-2"],"award-info":[{"award-number":["AA23062039-2"]}]},{"name":"Major Talent Project in Guangxi Province","award":["AA23062039-2"],"award-info":[{"award-number":["AA23062039-2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Spatial association analysis is essential for understanding interdependencies, spatial proximity, and distribution patterns within spatial data. The spatial scale is a key factor that significantly affects the result of spatial association mining. Traditional methods often rely on a fixed distance threshold (bandwidth) to define the scale effect, which can lead to scale sensitivity and discontinuity results. To address these limitations, this study introduces the Fuzzy Geographically Weighted Colocation Quotient (FGWCLQ) method. By integrating fuzzy theory, FGWCLQ replaces binary distance cutoffs with continuous membership functions, providing a more flexible and stable approach to spatial association mining. Using Point of Interest (POI) data from the Beijing urban area, FGWCLQ was applied to explore both intra- and inter-category spatial association patterns among star hotels, transportation facilities, and tourist attractions at different fuzzy neighborhoods. The results indicate that FGWCLQ can reliably discover global prevalent spatial associations among diverse facility types and visualize the spatial heterogeneity at various spatial scales. Compared to the deterministic GWCLQ method, FGWCLQ delivers more stable and robust results across varying spatial scales and generates more continuous association surfaces, which enable clear visualization of hierarchical clustering. Empirical findings provide valuable insights for optimizing the location of star hotels and supporting decision-making in urban planning. The method is available as an open-source Matlab package, providing a practical tool for diverse spatial association investigations.<\/jats:p>","DOI":"10.3390\/ijgi14080296","type":"journal-article","created":{"date-parts":[[2025,7,29]],"date-time":"2025-07-29T12:39:29Z","timestamp":1753792769000},"page":"296","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the Spatial Association Between Spatial Categorical Data Using a Fuzzy Geographically Weighted Colocation Quotient Method"],"prefix":"10.3390","volume":"14","author":[{"given":"Ling","family":"Li","sequence":"first","affiliation":[{"name":"Key Laboratory of Environment Change and Resources Use in Beibu, Nanning Normal University, Nanning 530000, China"},{"name":"School of Natural Resources and Surveying, Nanning Normal University, Nanning 530000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6006-9259","authenticated-orcid":false,"given":"Lian","family":"Duan","sequence":"additional","affiliation":[{"name":"School of Natural Resources and Surveying, Nanning Normal University, Nanning 530000, China"},{"name":"Joint Centre for Urban Health and Security Intelligent Data Analytics, Nanning Normal University, Nanning 530000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meiyi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Nanning Normal University, Nanning 530000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiongfa","family":"Mai","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Nanning Normal University, Nanning 530000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Deng, Y., Liu, J., Liu, Y., and Luo, A. 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