{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T07:31:34Z","timestamp":1774078294590,"version":"3.50.1"},"reference-count":113,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100016811","name":"National Institute of Forest Science","doi-asserted-by":"publisher","award":["FE0500-2025-02-2025"],"award-info":[{"award-number":["FE0500-2025-02-2025"]}],"id":[{"id":"10.13039\/100016811","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Ecological Informatics"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.ecoinf.2026.103640","type":"journal-article","created":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T23:40:44Z","timestamp":1771198844000},"page":"103640","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Predicting wildfires triggered by human-caused ignition: A spatial framework integrating AI models"],"prefix":"10.1016","volume":"94","author":[{"given":"Sujung","family":"Heo","sequence":"first","affiliation":[]},{"given":"Sujung","family":"Ahn","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0005","article-title":"Downslope wind-driven fires in the Western United States. Earth\u2019s","volume":"11","author":"Abatzoglou","year":"2023","journal-title":"Future"},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103640_bb0010","article-title":"Post-wildfire stability of unsaturated hillslopes against rainfall-triggered landslides. Earth\u2019s","volume":"11","author":"Abdollahi","year":"2023","journal-title":"Future"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.apgeog.2020.102382","article-title":"Developing a geospatial data-driven solution for rapid natural wildfire risk assessment","volume":"126","author":"Adhikari","year":"2021","journal-title":"Appl. Geogr."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0025","author":"Adinews released"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0035","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.envsci.2021.12.015","article-title":"Towards a systemic approach to fire risk management","volume":"129","author":"Bacciu","year":"2022","journal-title":"Environ. Sci. Pol."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0040","series-title":"Using Suitability Modelling to Determine Wildfire Ignition Risk: A Case Study of the Adirondack State Park (Master\u2019s thesis, Syracuse University)","author":"Bailey","year":"2021"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.geomorph.2022.108401","article-title":"Assessing the utility of regionalized rock-mass geomechanical properties in rockfall susceptibility modelling in an alpine environment","volume":"415","author":"Bajni","year":"2022","journal-title":"Geomorphology"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0050","series-title":"Compilation of architecture design guidelines for Residental buildings in wildfire zones","author":"Bastem","year":"2023"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0055","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1109\/JSYST.2022.3188300","article-title":"Quantifying the risk of wildfire ignition by power lines under extreme weather conditions","volume":"17","author":"Bayani","year":"2022","journal-title":"IEEE Syst. J."},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0060","doi-asserted-by":"crossref","first-page":"522","DOI":"10.3390\/f12050522","article-title":"Understanding the impact of different landscape-level fuel management strategies on wildfire hazard in Central Portugal","volume":"12","author":"Benali","year":"2021","journal-title":"Forests"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0065","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s11069-021-05065-1","article-title":"Examining the influence of outdoor recreation on anthropogenic wildfire regime of the southern Rocky Mountains","volume":"111","author":"Benefield","year":"2022","journal-title":"Nat. Hazards"},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0070","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.1007\/s10694-023-01400-z","article-title":"Does human accessibility affect lightning-caused wildfires? A case study of the southern Rocky Mountains","volume":"59","author":"Benefield","year":"2023","journal-title":"Fire. Technol"},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0075","doi-asserted-by":"crossref","first-page":"166","DOI":"10.3390\/fire5050166","article-title":"Wildfire risk levels at the local scale: assessing the relative influence of hazard, exposure, and social vulnerability","volume":"5","author":"Bergonse","year":"2022","journal-title":"Fire"},{"issue":"4","key":"10.1016\/j.ecoinf.2026.103640_bib604","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1111\/gcb.13142","article-title":"Model\u2010specification uncertainty in future forest pest outbreak","volume":"22","author":"Boulanger","year":"2016","journal-title":"Glob. Change Biol."},{"issue":"5926","key":"10.1016\/j.ecoinf.2026.103640_bb0085","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1126\/science.1163886","article-title":"Fire in the earth system","volume":"324","author":"Bowman","year":"2009","journal-title":"Science"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2019.107668","article-title":"Using generalized additive models for interpolating microclimate in dry-site ponderosa pine forests","volume":"279","author":"Burnett","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0100","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.foreco.2017.04.033","article-title":"Interacting effects of topography, vegetation, human activities and wildland-urban interfaces on wildfire ignition risk","volume":"397","author":"Calvi\u00f1o-Cancela","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0105","doi-asserted-by":"crossref","first-page":"115","DOI":"10.54097\/v5zy0z92","article-title":"Research on fire risk analysis and prevention in wildland-urban Interface","volume":"127","author":"Cao","year":"2025","journal-title":"Highlights Sci. Eng. Technol."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.landurbplan.2022.104577","article-title":"Spatial patterns of social vulnerability in relation to wildfire risk and wildland-urban interface presence","volume":"228","author":"Chas-Amil","year":"2022","journal-title":"Landsc. Urban Plan."},{"issue":"15","key":"10.1016\/j.ecoinf.2026.103640_bb0115","doi-asserted-by":"crossref","first-page":"49","DOI":"10.14383\/cri.2020.15.2.49","article-title":"Climatic characteristics of a local wind called Yangganjipung blowing in the northeast coastal region of South Korea","volume":"15","author":"Choi","year":"2020","journal-title":"J. Clim. Res."},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103640_bb0120","first-page":"168","article-title":"Spatial patterns and temporal variability of the Haines index related to the wildland fire growth potential over the Korean peninsula","volume":"41","author":"Choi","year":"2006","journal-title":"\ub300\ud55c\uc9c0\ub9ac\ud559\ud68c\uc9c0"},{"key":"10.1016\/j.ecoinf.2026.103640_bib601","first-page":"1099","article-title":"A review of performance and emission characteristic of engine diesel fuelled by biodiesel","volume":"94","author":"Chuah","year":"2022","journal-title":"Chem. Eng. Trans."},{"issue":"7","key":"10.1016\/j.ecoinf.2026.103640_bb0125","doi-asserted-by":"crossref","first-page":"5713","DOI":"10.3390\/su15075713","article-title":"Causes, types and consequences of municipal waste landfill fires\u2014literature review","volume":"15","author":"Dabrowska","year":"2023","journal-title":"Sustainability"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0130","doi-asserted-by":"crossref","first-page":"2498955","DOI":"10.1080\/22797254.2025.2498955","article-title":"Assessment of land use and land cover (LULC) and vegetation degradation state from wildfire within the scope of forest landscape restoration (FLR) in Cameroon","volume":"58","author":"Dahan","year":"2025","journal-title":"Eur. J. Rem. Sens."},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0135","doi-asserted-by":"crossref","DOI":"10.1029\/2020JD033180","article-title":"Meteorological environments associated with California wildfires and their potential roles in wildfire changes during 1984\u20132017","volume":"126","author":"Dong","year":"2021","journal-title":"J. Geophys. Res. Atmos."},{"issue":"10","key":"10.1016\/j.ecoinf.2026.103640_bb0140","doi-asserted-by":"crossref","first-page":"407","DOI":"10.3390\/fire8100407","article-title":"Wildfire susceptibility mapping using deep learning and machine learning models based on multi-sensor satellite data fusion: a case study of Serbia","volume":"8","author":"Durlevi\u0107","year":"2025","journal-title":"Fire"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0145","series-title":"Fire Management \u2013 Global Assessment 2006","author":"FAO","year":"2007"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0150","series-title":"Stakeholders\u2019 Perspectives on Opportunities and Challenges in Engaging Communities in Fire Risk Management (Master\u2019s thesis, Universidade de Coimbra (Portugal))","author":"Fernandes","year":"2023"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0155","doi-asserted-by":"crossref","DOI":"10.1177\/11786221211028185","article-title":"Current wildland fire patterns and challenges in Europe: a synthesis of national perspectives","volume":"14","author":"Fernandez-Anez","year":"2021","journal-title":"Air Soil Water Res."},{"issue":"4","key":"10.1016\/j.ecoinf.2026.103640_bb0160","doi-asserted-by":"crossref","first-page":"2580","DOI":"10.3390\/heritage4040146","article-title":"Understanding the impacts of the October 2017 Portugal wildfires on cultural heritage","volume":"4","author":"Figueiredo","year":"2021","journal-title":"Heritage"},{"issue":"11","key":"10.1016\/j.ecoinf.2026.103640_bb0165","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2025.e43173","article-title":"Integrated multi-hazard risk assessment under compound disasters using analytical hierarchy process (AHP)","volume":"11","author":"Gacu","year":"2025","journal-title":"Heliyon"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.forpol.2021.102619","article-title":"Wildfire, smoke, and outdoor recreation in the western United States","volume":"134","author":"Gellman","year":"2022","journal-title":"Forest Policy Econ."},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0175","doi-asserted-by":"crossref","DOI":"10.3390\/geosciences14050112","article-title":"Analysis of wildfire susceptibility by weight of evidence, using geomorphological and environmental factors in the Marche region, Central Italy","volume":"14","author":"Gentilucci","year":"2024","journal-title":"Geosciences"},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103640_bb0180","doi-asserted-by":"crossref","first-page":"208","DOI":"10.3390\/fire5060208","article-title":"Collective effects of fire intensity and sloped terrain on wind-driven surface fire and its impact on a cubic structure","volume":"5","author":"Ghodrat","year":"2022","journal-title":"Fire"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0190","article-title":"Understanding wildfire evacuees\u2019 perceived safety on their evacuation route: a study of the 2018 Camp fire","volume":"31","author":"Grajdura","year":"2025","journal-title":"Transp. Res. Interdiscip. Perspect."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0200","doi-asserted-by":"crossref","DOI":"10.1080\/19475705.2025.2493211","article-title":"Evaluating thresholds: the impact of terrain modifications on landslide susceptibility in a mountainous city","volume":"16","author":"Heo","year":"2025","journal-title":"Geomat. Nat. Hazards Risk"},{"issue":"10","key":"10.1016\/j.ecoinf.2026.103640_bib600","doi-asserted-by":"crossref","first-page":"4416","DOI":"10.3390\/su17104416","article-title":"Land cover and wildfire risk: a multi-buffer spatial snalysis of the relationship between housing destruction and land cover in Chile\u2019s b\u00edo-b\u00edo region in 2023","volume":"17","author":"Hora","year":"2025","journal-title":"Sustainability"},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0205","first-page":"365","article-title":"Associations between wildfire risk and socio-economic-demographic characteristics using GIS technology","volume":"14","author":"Hwang","year":"2022","journal-title":"J. Geogr. Inf. Syst."},{"issue":"14","key":"10.1016\/j.ecoinf.2026.103640_bb0210","doi-asserted-by":"crossref","first-page":"2737","DOI":"10.3390\/rs13142737","article-title":"Utilizing the available open-source remotely sensed data in assessing the wildfire ignition and spread capacities of vegetated surfaces in Romania","volume":"13","author":"Hysa","year":"2021","journal-title":"Remote Sens."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0215","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/s41558-021-01224-1","article-title":"Observed increases in extreme fire weather driven by atmospheric humidity and temperature","volume":"12","author":"Jain","year":"2022","journal-title":"Nat. Clim. Chang."},{"key":"10.1016\/j.ecoinf.2026.103640_bib596","doi-asserted-by":"crossref","first-page":"14241","DOI":"10.3390\/su151914241","article-title":"Comprehensive study of the impact of waste fires on the environment and health","volume":"15","author":"Jakhar","year":"2023","journal-title":"Sustainability"},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103640_bb0220","first-page":"211","article-title":"Seasonal correlation between wildfire danger indices and meteorological variables in Central Korea","volume":"87","author":"Jeong","year":"2021","journal-title":"J. For. Sci."},{"issue":"8","key":"10.1016\/j.ecoinf.2026.103640_bb0225","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.3390\/f13081200","article-title":"Spatial predictions of human and natural-caused wildfire likelihood across Montana (USA)","volume":"13","author":"Jim\u00e9nez-Ruano","year":"2022","journal-title":"Forests"},{"issue":"5","key":"10.1016\/j.ecoinf.2026.103640_bb0230","doi-asserted-by":"crossref","first-page":"1446","DOI":"10.3390\/rs15051446","article-title":"Modeling historical and future forest fires in South Korea: the FLAM optimization approach","volume":"15","author":"Jo","year":"2023","journal-title":"Remote Sens."},{"issue":"12","key":"10.1016\/j.ecoinf.2026.103640_bb0235","doi-asserted-by":"crossref","first-page":"9756","DOI":"10.3390\/su15129756","article-title":"Fires in waste treatment facilities: challenges and solutions from a fire investigation perspective","volume":"15","author":"Juan","year":"2023","journal-title":"Sustainability"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0240","author":"Jungdo Ilbo released"},{"issue":"8","key":"10.1016\/j.ecoinf.2026.103640_bib597","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1038\/s43016-023-00803-z","article-title":"Pathways framework identifies wildfire impacts on agriculture","volume":"4","author":"Kabeshita","year":"2023","journal-title":"Nature Food"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0245","article-title":"Potential for forest thinning to reduce risk and increase resilience to wildfire in Australian temperate Eucalyptus forests","volume":"23","author":"Keenan","year":"2021","journal-title":"Curr. Opin. Environ. Sci Health"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0250","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s42408-021-00125-0","article-title":"A spatially explicit analytical framework to assess wildfire risks on brown bear habitat and corridors in conservation areas","volume":"18","author":"Khosravi","year":"2022","journal-title":"Fire Ecol."},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103640_bb0260","first-page":"123","article-title":"Analysis of meteorological factors influencing wildfires in South Korea (2005\u20132019)","volume":"10","author":"Kim","year":"2020","journal-title":"J. Meteorol. Res."},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103640_bb0265","doi-asserted-by":"crossref","first-page":"728","DOI":"10.3390\/f12060728","article-title":"Human activity affects forest fires: the impact of anthropogenic factors on the density of forest fires in Poland","volume":"12","author":"Kolanek","year":"2021","journal-title":"Forests"},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103640_bb0280","first-page":"153","article-title":"Analysis of the relationship between open burning and wildfire occurrence in rural Korea","volume":"109","author":"Lee","year":"2020","journal-title":"J. Korean Forest Soc."},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103640_bib598","first-page":"345","article-title":"A study on wildfire disaster response based on cases of international disaster safety management systems","volume":"40","author":"Lee","year":"2020","journal-title":"KSCE J. Civ. Environ. Eng. Res."},{"issue":"12","key":"10.1016\/j.ecoinf.2026.103640_bb0285","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.3390\/rs12121911","article-title":"Assessment of fire fuel load dynamics in shrubland ecosystems in the western United States using MODIS products","volume":"12","author":"Li","year":"2020","journal-title":"Remote Sens."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0290","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11676-025-01822-1","article-title":"Integrated spatial generalized additive modeling for forest fire prediction: a case study in Fujian Province, China","volume":"36","author":"Li","year":"2025","journal-title":"J. For. Res."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0295","doi-asserted-by":"crossref","DOI":"10.1016\/j.landusepol.2022.106372","article-title":"Wildfire, protected areas and forest ownership: the case of China","volume":"122","author":"Liu","year":"2022","journal-title":"Land Use Policy"},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103640_bb0300","article-title":"Fire risk assessment on wildland\u2013urban interface and adjoined urban areas: estimation vegetation ignitability by artificial neural network","volume":"5","author":"Mahamed","year":"2022","journal-title":"Fire"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0305","doi-asserted-by":"crossref","first-page":"109","DOI":"10.3390\/atmos12010109","article-title":"Data-driven wildfire risk prediction in northern California","volume":"12","author":"Malik","year":"2021","journal-title":"Atmosphere"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0310","first-page":"1","article-title":"Estimating wildfire ignition probabilities with geographic weighted logistic regression","author":"Marto","year":"2025","journal-title":"J. Appl. Stat."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0315","first-page":"1","article-title":"Impact of geophysical and anthropogenic factors on wildfire size: a spatiotemporal data-driven risk assessment approach using statistical learning","author":"Masoudvaziri","year":"2021","journal-title":"Stoch. Env. Res. Risk A."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0320","doi-asserted-by":"crossref","DOI":"10.1016\/j.landurbplan.2023.104997","article-title":"Post-wildfire neighborhood change: evidence from the 2018 Camp fire","volume":"247","author":"McConnell","year":"2024","journal-title":"Landsc. Urban Plan."},{"issue":"8","key":"10.1016\/j.ecoinf.2026.103640_bb0325","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1080\/01490400.2023.2267549","article-title":"Campfire smoke and the Anthropocene","volume":"46","author":"Medlin","year":"2024","journal-title":"Leis. Sci."},{"issue":"13","key":"10.1016\/j.ecoinf.2026.103640_bb0330","doi-asserted-by":"crossref","first-page":"6252","DOI":"10.3390\/ijerph20136252","article-title":"Wildfires and older adults: a scoping review of impacts, risks, and interventions","volume":"20","author":"Melton","year":"2023","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0335","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.142844","article-title":"Forecasting fire risk with machine learning and dynamic information derived from satellite vegetation index time-series","volume":"764","author":"Michael","year":"2021","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0340","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00477-022-02273-4","article-title":"Wildfire susceptibility mapping using two empowered machine learning algorithms","volume":"37","author":"Moayedi","year":"2023","journal-title":"Stoch. Env. Res. Risk A."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0350","first-page":"e02580","article-title":"Spatio-temporal dynamics, drivers of wildfire occurrence and distribution in the northern Savannah ecological zone of Ghana","volume":"27","author":"Naawa","year":"2025","journal-title":"Sci. Afr."},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103640_bb0355","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1007\/s10844-015-0368-1","article-title":"Types of minority class examples and their influence on learning classifiers from imbalanced data","volume":"46","author":"Napierala","year":"2016","journal-title":"J. Intell. Inf. Syst."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0360","first-page":"1","article-title":"Vulnerability of structures and infrastructure to wildfires: a perspective into assessment and mitigation strategies","author":"Naser","year":"2025","journal-title":"Nat. Hazards"},{"issue":"9","key":"10.1016\/j.ecoinf.2026.103640_bb0365","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1007\/s10661-022-10318-y","article-title":"Modeling wildfire risk in western Iran based on the integration of AHP and GIS","volume":"194","author":"Nasiri","year":"2022","journal-title":"Environ. Monit. Assess."},{"issue":"7","key":"10.1016\/j.ecoinf.2026.103640_bb0370","doi-asserted-by":"crossref","first-page":"6569","DOI":"10.1007\/s11069-024-06457-9","article-title":"Forest fire mapping: a comparison between GIS-based random forest and Bayesian models","volume":"120","author":"Noroozi","year":"2024","journal-title":"Nat. Hazards"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0375","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.rama.2022.08.004","article-title":"Grazing intensity effects on fire ignition risk and spread in sagebrush steppe","volume":"89","author":"Orr","year":"2023","journal-title":"Rangel. Ecol. Manag."},{"issue":"9","key":"10.1016\/j.ecoinf.2026.103640_bib599","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1007\/s10661-024-12982-8","article-title":"A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions","volume":"196","author":"\u00d6zcan","year":"2024","journal-title":"Environ. Monit. Assess."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0380","doi-asserted-by":"crossref","first-page":"33","DOI":"10.3390\/fire7010033","article-title":"Identifying influential spatial drivers of forest fires through geographically and temporally weighted regression coupled with a continuous invasive weed optimization algorithm","volume":"7","author":"Pahlavani","year":"2024","journal-title":"Fire"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0385","doi-asserted-by":"crossref","first-page":"6378","DOI":"10.1038\/s41598-022-10479-3","article-title":"A wildfire vulnerability index for buildings","volume":"12","author":"Papathoma-K\u00f6hle","year":"2022","journal-title":"Sci. Rep."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0390","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1038\/s43247-023-00977-1","article-title":"Abrupt, climate-induced increase in wildfires in British Columbia since the mid-2000s","volume":"4","author":"Parisien","year":"2023","journal-title":"Commun. Earth Environ."},{"issue":"11","key":"10.1016\/j.ecoinf.2026.103640_bb0395","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1071\/WF20139","article-title":"Comparing calibrated statistical and machine learning methods for wildland fire occurrence prediction: a case study of human-caused fires in lac La Biche, Alberta, Canada","volume":"30","author":"Phelps","year":"2021","journal-title":"Int. J. Wildland Fire"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0410","series-title":"Regression Modelling of Spatiotemporal Extreme US Wildfires Via Partially-Interpretable Neural Networks","author":"Richards","year":"2022"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0415","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1038\/s41612-022-00248-4","article-title":"Global increase in wildfire potential from compound fire weather and drought","volume":"5","author":"Richardson","year":"2022","journal-title":"NPJ Clim. Atmos. Sci."},{"key":"10.1016\/j.ecoinf.2026.103640_bib603","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.envsoft.2014.03.003","article-title":"An insight into machine-learning algorithms to model human-caused wildfire occurrence","volume":"57","author":"Rodrigues","year":"2014","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0425","doi-asserted-by":"crossref","DOI":"10.1016\/j.envres.2021.110794","article-title":"A scoping review of interventions targeting small-scale, individual-initiated burning practices","volume":"195","author":"Ryan","year":"2021","journal-title":"Environ. Res."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0435","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijdrr.2021.102286","article-title":"Review of vulnerability indicators for fire risk assessment in cultural heritage","volume":"60","author":"Salazar","year":"2021","journal-title":"Int. J. Disaster Risk Reduct."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0440","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/s42398-022-00259-0","article-title":"Prediction capability of the MCDA-AHP model in wildfire risk zonation of a protected area in the southern Western Ghats","volume":"6","author":"Salma","year":"2023","journal-title":"Environ. Sustain."},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103640_bb0445","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1007\/s11676-022-01502-4","article-title":"Identifying anthropogenic and natural causes of wildfires by maximum entropy method-based ignition susceptibility distribution models","volume":"34","author":"Sari","year":"2023","journal-title":"J. For. Res."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0450","doi-asserted-by":"crossref","first-page":"15624","DOI":"10.1038\/s41598-024-65355-z","article-title":"Fire protection priorities in the oak forests of Iran with an emphasis on vertebrate habitat preservation","volume":"14","author":"Sayahnia","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0455","series-title":"Climate-Resilient Spatial Planning in the Alps: An Analysis of the Integration of Climate Change Adaptation and Climate Resilience in Spatial Planning Systems and Practice in the Alpine Region","author":"Schindelegger","year":"2022"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0460","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1038\/s41598-021-04726-2","article-title":"Characterization of global wildfire burned area spatiotemporal patterns and underlying climatic causes","volume":"12","author":"Shi","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0465","doi-asserted-by":"crossref","DOI":"10.1016\/j.firesaf.2023.103743","article-title":"Human activity and demographics drive the fire regime in a highly developed European boreal region","volume":"136","author":"Sj\u00f6str\u00f6m","year":"2023","journal-title":"Fire Saf. J."},{"issue":"14","key":"10.1016\/j.ecoinf.2026.103640_bb0470","doi-asserted-by":"crossref","first-page":"2667","DOI":"10.3390\/rs16142667","article-title":"Development of an algorithm for assessing the scope of large forest fire using VIIRS-based data and machine learning","volume":"16","author":"Son","year":"2024","journal-title":"Remote Sens."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0475","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2023.167335","article-title":"The influence of regional wind patterns on air quality during forest fires near Sydney, Australia","volume":"905","author":"Storey","year":"2023","journal-title":"Sci. Total Environ."},{"issue":"11","key":"10.1016\/j.ecoinf.2026.103640_bb0480","doi-asserted-by":"crossref","first-page":"3703","DOI":"10.5194\/nhess-24-3703-2024","article-title":"The effect of wildfires on flood risk: a multi-hazard flood risk approach for the Ebro River basin, Spain","volume":"24","author":"Sutanto","year":"2024","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0485","doi-asserted-by":"crossref","DOI":"10.1016\/j.eti.2022.102419","article-title":"Modeling the organic matter of water using the decision tree coupled with bootstrap aggregated and least-squares boosting","volume":"27","author":"Tahraoui","year":"2022","journal-title":"Environ. Technol. Innovation"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0490","article-title":"A comprehensive review of geographic information systems (GIS)-based methodologies for urban fire risk assessment","volume":"2","author":"Thakare","year":"2025","journal-title":"Cureus J."},{"issue":"13","key":"10.1016\/j.ecoinf.2026.103640_bb0495","doi-asserted-by":"crossref","first-page":"eabm0320","DOI":"10.1126\/sciadv.abm0320","article-title":"Climate change increases risk of extreme rainfall following wildfire in the western United States","volume":"8","author":"Touma","year":"2022","journal-title":"Sci. Adv."},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103640_bib602","doi-asserted-by":"crossref","DOI":"10.1002\/ecy.3336","article-title":"A practical guide to selecting models for exploration, inference, and prediction in ecology","volume":"102","author":"Tredennick","year":"2021","journal-title":"Ecology"},{"issue":"3","key":"10.1016\/j.ecoinf.2026.103640_bb0500","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1071\/WF22138","article-title":"Wildfire hazard mapping in the eastern Mediterranean landscape","volume":"32","author":"Trucchia","year":"2023","journal-title":"Int. J. Wildland Fire"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0505","doi-asserted-by":"crossref","first-page":"119751","DOI":"10.1016\/j.envres.2024.119751","article-title":"Do machine learning methods improve prediction of ambient air pollutants with high spatial contrast? A systematic review","volume":"262","author":"Vachon","year":"2024","journal-title":"Environ. Res."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0515","doi-asserted-by":"crossref","first-page":"16","DOI":"10.3390\/fire5010016","article-title":"Megafires in a warming world: what wildfire risk factors led to California\u2019s largest recorded wildfire","volume":"5","author":"Varga","year":"2022","journal-title":"Fire"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0520","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1080\/19475705.2022.2039787","article-title":"Wildfire probability models calibrated using past human and lightning ignition patterns can inform mitigation of post-fire hydrologic hazards","volume":"13","author":"Villarreal","year":"2022","journal-title":"Geomat. Nat. Haz. Risk"},{"issue":"11","key":"10.1016\/j.ecoinf.2026.103640_bb0525","doi-asserted-by":"crossref","DOI":"10.3390\/f14112139","article-title":"Forest fire spread hazard and landscape pattern characteristics in the Mountainous District, Beijing","volume":"14","author":"Wang","year":"2023","journal-title":"Forests"},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0530","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1007\/s41651-023-00166-w","article-title":"Exploring multi-driver influences on Indonesia\u2019s biomass fire patterns from 2002 to 2019 through geographically weighted regression","volume":"8","author":"Wee","year":"2024","journal-title":"J. Geovis. Spat. Anal."},{"issue":"1","key":"10.1016\/j.ecoinf.2026.103640_bb0535","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5532\/KJAFM.2012.14.1.001","article-title":"Prediction of Forest fire danger rating over the Korean peninsula with the digital forecast data and daily weather index (DWI) model","volume":"14","author":"Won","year":"2012","journal-title":"Korean J. Agric. Forest Meterol."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0540","doi-asserted-by":"crossref","first-page":"1137372","DOI":"10.3389\/fenvs.2023.1137372","article-title":"Wildfire risks under a changing climate: synthesized assessments of wildfire risks over southwestern China","volume":"11","author":"Xu","year":"2023","journal-title":"Front. Environ. Sci."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0545","doi-asserted-by":"crossref","DOI":"10.1016\/j.fecs.2023.100104","article-title":"A geographical similarity-based sampling method of non-fire point data for spatial prediction of forest fires","volume":"10","author":"Xu","year":"2023","journal-title":"Forest Ecosyst."},{"issue":"10","key":"10.1016\/j.ecoinf.2026.103640_bb0550","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.3390\/f12101299","article-title":"Wildfire risk assessment and zoning by integrating Maxent and GIS in Hunan province, China","volume":"12","author":"Yang","year":"2021","journal-title":"Forests"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0555","series-title":"Predicting forest fire using remote sensing data and machine learning. In proceedings of the AAAI conference on artificial intelligence (Vol. 35, no. 17, pp. 14983-14990)","author":"Yang","year":"2021"},{"issue":"2","key":"10.1016\/j.ecoinf.2026.103640_bb0560","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s10109-022-00387-5","article-title":"Geographically weighted regression with the integration of machine learning for spatial prediction","volume":"25","author":"Yang","year":"2023","journal-title":"J. Geogr. Syst."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0565","doi-asserted-by":"crossref","DOI":"10.1016\/j.agrformet.2021.108540","article-title":"Relative humidity and agricultural activities dominate wildfire ignitions in Yunnan, Southwest China: patterns, thresholds, and implications","volume":"307","author":"Ying","year":"2021","journal-title":"Agric. For. Meteorol."},{"issue":"9","key":"10.1016\/j.ecoinf.2026.103640_bb0570","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2023.e19664","article-title":"Fire risk assessments and fire protection measures for wind turbines: a review","volume":"9","author":"You","year":"2023","journal-title":"Heliyon"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0575","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2023.165704","article-title":"Integrated wildfire danger models and factors: a review","volume":"899","author":"Zacharakis","year":"2023","journal-title":"Sci. Total Environ."},{"issue":"4","key":"10.1016\/j.ecoinf.2026.103640_bb0580","doi-asserted-by":"crossref","DOI":"10.3390\/f14040807","article-title":"Wildfire susceptibility of land use and topographic features in the Western United States: implications for the landscape management","volume":"14","author":"Zhai","year":"2023","journal-title":"Forests"},{"key":"10.1016\/j.ecoinf.2026.103640_bb0585","doi-asserted-by":"crossref","DOI":"10.1016\/j.foreco.2021.119638","article-title":"Important meteorological predictors for long-range wildfires in China","volume":"499","author":"Zhao","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"10.1016\/j.ecoinf.2026.103640_bb0590","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecolind.2021.108529","article-title":"Classification of Zambian grasslands using random forest feature importance selection during the optimal phenological period","volume":"135","author":"Zhao","year":"2022","journal-title":"Ecol. Indic."},{"issue":"6","key":"10.1016\/j.ecoinf.2026.103640_bb0595","doi-asserted-by":"crossref","first-page":"3578","DOI":"10.1002\/joc.7036","article-title":"Will land use land cover change drive atmospheric conditions to become more conducive to wildfires in the United States?","volume":"41","author":"Zhong","year":"2021","journal-title":"Int. J. Climatol."}],"container-title":["Ecological Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1574954126000464?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1574954126000464?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T04:30:03Z","timestamp":1774067403000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1574954126000464"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":113,"alternative-id":["S1574954126000464"],"URL":"https:\/\/doi.org\/10.1016\/j.ecoinf.2026.103640","relation":{},"ISSN":["1574-9541"],"issn-type":[{"value":"1574-9541","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Predicting wildfires triggered by human-caused ignition: A spatial framework integrating AI models","name":"articletitle","label":"Article Title"},{"value":"Ecological Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ecoinf.2026.103640","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"103640"}}