{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T14:03:24Z","timestamp":1764943404921,"version":"3.46.0"},"reference-count":67,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T00:00:00Z","timestamp":1764892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute for the Humanities and Social Sciences scholarship","award":["NIHSS SDS17\/1130"],"award-info":[{"award-number":["NIHSS SDS17\/1130"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Persistent forest fire refugia are areas within fire-prone landscapes that remain fire-free over long periods of time and are crucial for ecosystem resilience. Modelling to develop maps of these refugia is key to informing fire and land use management. We predict persistent forest fire refugia using variables linked to the fire triangle (aspect, slope, elevation, topographic wetness, convergence and roughness, solar irradiation, temperature, surface wind direction, and speed) in machine learning algorithms (Random Forest, XGBoost; two ensemble models) and K-Nearest Neighbour. All models were run with and without ADASYN over-sampling and grid search hyperparameterisation. Six iterations were run per algorithm to assess the impact of omitting variables. Aspect is twice as influential as any other variable across all models. Solar radiation and surface wind direction are also highlighted, although the order of importance differs between algorithms. The predominant importance of aspect relates to solar radiation received by sun-facing slopes and resultant heat and moisture balances and, in this study area, the predominant fire wind direction. Ensemble models consistently produced the most accurate results. The findings highlight the importance of topographic and microclimatic variables in persistent forest fire refugia prediction, with ensemble machine learning providing reliable forecasting frameworks.<\/jats:p>","DOI":"10.3390\/ijgi14120480","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T13:17:07Z","timestamp":1764940627000},"page":"480","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Persistent Forest Fire Refugia Using Machine Learning Models with Topographic, Microclimate, and Surface Wind Variables"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4711-6193","authenticated-orcid":false,"given":"Sven","family":"Christ","sequence":"first","affiliation":[{"name":"Department of Geography and Environmental Studies, Stellenbosch University, P. Bag X1, Stellenbosch 7602, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8891-2869","authenticated-orcid":false,"given":"Tineke","family":"Kraaij","sequence":"additional","affiliation":[{"name":"Natural Resource Science and Management, Science Faculty, Nelson Mandela University, George Campus, George 6530, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3593-5247","authenticated-orcid":false,"given":"Coert J.","family":"Geldenhuys","sequence":"additional","affiliation":[{"name":"Forest Science Program, Department of Plant and Soil Sciences, University of Pretoria, c\/o Forestwood cc, 35 Grace Avenue, Murrayfield, Pretoria 0184, South Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1628-352X","authenticated-orcid":false,"given":"Helen M.","family":"de Klerk","sequence":"additional","affiliation":[{"name":"Department of Geography and Environmental Studies, Stellenbosch University, P. Bag X1, Stellenbosch 7602, South Africa"},{"name":"Centre for Geospatial and Computing Technologies, Faculty of Environment, Society and Design|Te W\u0101haka ki te Taiao, te H\u0101pori Wh\u0101nui me k\u0101 Mahi Hoahoa, Lincoln University, Forbes Building, Ellesmere Junction Road, Lincoln 7608, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"ref_1","first-page":"944","article-title":"Fire Refugia: What Are They, and Why Do They Matter for Global Change?","volume":"68","author":"Meddens","year":"2018","journal-title":"BioScience"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.foreco.2009.03.041","article-title":"Factors influencing the formation of unburned forest islands within the perimeter of a large forest fire","volume":"258","author":"Gracia","year":"2009","journal-title":"For. Ecol. 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