{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:34:43Z","timestamp":1773189283060,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T00:00:00Z","timestamp":1759968000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Chengdu University of Technology"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Mountainous urban areas like Guiyang face unique fire safety challenges due to rugged terrain and complex road networks, which hinder fire station accessibility. This study proposes a GIS-based framework that integrates nighttime light (NPP\/VIIRS) and point of interest (POI) data to assess fire risk and accessibility. Kernel density estimation quantified POI distributions across four risk categories, and the Spatial Appraisal and Valuation of Environment and Ecosystems (SAVEE) model combined these with NPP\/VIIRS data to generate a composite fire risk map. Accessibility was evaluated using the enhanced two-step floating catchment area (E2SFCA) method with road network travel times; 80.13% of demand units were covered within the five-minute threshold, while 53.25% of all units exhibited low accessibility. Spatial autocorrelation analysis (Moran\u2019s I) revealed clustered high risk in central basins and service gaps on surrounding hills, reflecting the dominant influence of terrain alongside protected forests and farmlands. The results indicate that targeted road upgrades and station relocations can improve fire service coverage. The approach is scalable and supports more equitable emergency response in mountainous settings.<\/jats:p>","DOI":"10.3390\/ijgi14100393","type":"journal-article","created":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:54:31Z","timestamp":1760028871000},"page":"393","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Assessing Fire Station Accessibility in Guiyang, a Mountainous City, with Nighttime Light and POI Data: An Application of the Enhanced 2SFCA Approach"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0749-0500","authenticated-orcid":false,"given":"Xindong","family":"He","sequence":"first","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Research Center for Human Geography of Tibetan Plateau and Its Eastern Slope (Chengdu University of Technology), Chengdu 610059, China"}]},{"given":"Boqing","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Guoqiang","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Regional and City Planning, College of Architecture and Civil Engineering, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Qianqian","family":"Lyu","sequence":"additional","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Grace","family":"Ofori","sequence":"additional","affiliation":[{"name":"College of Geography and Planning, Chengdu University of Technology, Chengdu 610059, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1071\/WF09119","article-title":"Wildland fire spread modelling using cellular automata: Evolution in large-scale spatially heterogeneous environments under fire suppression tactics","volume":"20","author":"Alexandridis","year":"2011","journal-title":"Int. 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