{"id":"https://openalex.org/W3015900272","doi":"https://doi.org/10.3390/sym12040604","title":"Comparisons of Diverse Machine Learning Approaches for Wildfire Susceptibility Mapping","display_name":"Comparisons of Diverse Machine Learning Approaches for Wildfire Susceptibility Mapping","publication_year":2020,"publication_date":"2020-04-10","ids":{"openalex":"https://openalex.org/W3015900272","doi":"https://doi.org/10.3390/sym12040604","mag":"3015900272"},"language":"en","primary_location":{"id":"doi:10.3390/sym12040604","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12040604","pdf_url":"https://www.mdpi.com/2073-8994/12/4/604/pdf?version=1586528145","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/12/4/604/pdf?version=1586528145","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010457221","display_name":"Khalil Gholamnia","orcid":"https://orcid.org/0000-0002-3860-8674"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Khalil Gholamnia","raw_affiliation_strings":["Department of Remote Sensing and GIS, University of Tabriz, Tabriz 5166616471, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing and GIS, University of Tabriz, Tabriz 5166616471, Iran","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049734142","display_name":"Thimmaiah Gudiyangada Nachappa","orcid":"https://orcid.org/0000-0002-1341-3264"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Thimmaiah Gudiyangada Nachappa","raw_affiliation_strings":["Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089503857","display_name":"Omid Ghorbanzadeh","orcid":"https://orcid.org/0000-0002-9664-8770"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Omid Ghorbanzadeh","raw_affiliation_strings":["Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056842687","display_name":"Thomas Blaschke","orcid":"https://orcid.org/0000-0002-1860-8458"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Thomas Blaschke","raw_affiliation_strings":["Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria"],"affiliations":[{"raw_affiliation_string":"Department of Geoinformatics\u2013Z_GIS, University of Salzburg, 5020 Salzburg, Austria","institution_ids":["https://openalex.org/I182212641"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089503857"],"corresponding_institution_ids":["https://openalex.org/I182212641"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":1275,"currency":"EUR","value_usd":1375},"fwci":7.9159,"has_fulltext":true,"cited_by_count":136,"citation_normalized_percentile":{"value":0.98149857,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"12","issue":"4","first_page":"604","last_page":"604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10555","display_name":"Fire effects on ecosystems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10555","display_name":"Fire effects on ecosystems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10535","display_name":"Landslides and related hazards","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6084461808204651},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5619875192642212},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5587046146392822},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5313988924026489},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.49848175048828125},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.47634127736091614},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.46482470631599426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45979875326156616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4594785273075104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45911023020744324},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4064001739025116},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.3593747019767761},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2586045563220978}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6084461808204651},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5619875192642212},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5587046146392822},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5313988924026489},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.49848175048828125},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.47634127736091614},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.46482470631599426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45979875326156616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4594785273075104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45911023020744324},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4064001739025116},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3593747019767761},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2586045563220978}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym12040604","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12040604","pdf_url":"https://www.mdpi.com/2073-8994/12/4/604/pdf?version=1586528145","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a87c0b78758240e28b5e3b90ef8f48d0","is_oa":true,"landing_page_url":"https://doaj.org/article/a87c0b78758240e28b5e3b90ef8f48d0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 12, Iss 4, p 604 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/12/4/604/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/sym12040604","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym12040604","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym12040604","pdf_url":"https://www.mdpi.com/2073-8994/12/4/604/pdf?version=1586528145","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G1124707694","display_name":null,"funder_award_id":"W 1237","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G3085262636","display_name":null,"funder_award_id":"W 1237-N23","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G4108532496","display_name":null,"funder_award_id":"DK W 1237-N23","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G4760041171","display_name":null,"funder_award_id":"(DK W 1237-N23).","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"},{"id":"https://openalex.org/G86119818","display_name":null,"funder_award_id":"237-N23","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"}],"funders":[{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3015900272.pdf","grobid_xml":"https://content.openalex.org/works/W3015900272.grobid-xml"},"referenced_works_count":61,"referenced_works":["https://openalex.org/W1430220953","https://openalex.org/W1520585040","https://openalex.org/W1888709858","https://openalex.org/W1942836393","https://openalex.org/W1967902943","https://openalex.org/W1970580850","https://openalex.org/W1970972394","https://openalex.org/W1974614011","https://openalex.org/W1977377474","https://openalex.org/W1978784463","https://openalex.org/W1985288162","https://openalex.org/W1990748933","https://openalex.org/W1993934953","https://openalex.org/W1994214164","https://openalex.org/W2002620848","https://openalex.org/W2012118327","https://openalex.org/W2036063587","https://openalex.org/W2057039778","https://openalex.org/W2063978378","https://openalex.org/W2065642067","https://openalex.org/W2090454671","https://openalex.org/W2112315008","https://openalex.org/W2120630093","https://openalex.org/W2130269771","https://openalex.org/W2148470216","https://openalex.org/W2151207589","https://openalex.org/W2225976211","https://openalex.org/W2556989296","https://openalex.org/W2580219088","https://openalex.org/W2582623062","https://openalex.org/W2640557513","https://openalex.org/W2754716656","https://openalex.org/W2775745878","https://openalex.org/W2793532906","https://openalex.org/W2888067248","https://openalex.org/W2888231268","https://openalex.org/W2892289985","https://openalex.org/W2894859748","https://openalex.org/W2896949512","https://openalex.org/W2907066318","https://openalex.org/W2911252155","https://openalex.org/W2912361013","https://openalex.org/W2913649977","https://openalex.org/W2914068061","https://openalex.org/W2953423956","https://openalex.org/W2954992390","https://openalex.org/W2963019697","https://openalex.org/W2964406534","https://openalex.org/W2972175198","https://openalex.org/W2973710071","https://openalex.org/W2984248680","https://openalex.org/W2984594085","https://openalex.org/W2995555089","https://openalex.org/W2995742865","https://openalex.org/W2998709485","https://openalex.org/W3001555788","https://openalex.org/W3004334875","https://openalex.org/W6639729252","https://openalex.org/W6640462745","https://openalex.org/W6730155028","https://openalex.org/W6753979435"],"related_works":["https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645","https://openalex.org/W4366990902","https://openalex.org/W4388550696","https://openalex.org/W4224922629","https://openalex.org/W4321636153","https://openalex.org/W4313289487","https://openalex.org/W2076543106"],"abstract_inverted_index":{"Climate":[0],"change":[1],"has":[2,65],"increased":[3],"the":[4,7,17,49,51,85,97,101,115,128,135,194,223,244,247,252,269],"probability":[5],"of":[6,9,61,137,197,246,255,263,272],"occurrence":[8],"catastrophes":[10],"like":[11],"wildfires,":[12],"floods,":[13],"and":[14,29,35,54,68,96,112,188,225,266],"storms":[15],"across":[16],"globe":[18],"in":[19,48,57,147,285],"recent":[20],"years.":[21],"Weather":[22],"conditions":[23],"continue":[24],"to":[25,71,133,242],"grow":[26],"more":[27,55],"extreme,":[28],"wildfires":[30,74],"are":[31,36,157],"occurring":[32],"quite":[33],"frequently":[34],"spreading":[37],"with":[38,122,193,217,260],"greater":[39],"intensity.":[40],"Wildfires":[41],"ravage":[42],"forest":[43,175],"areas,":[44],"as":[45,215],"recently":[46,56],"seen":[47],"Amazon,":[50],"United":[52],"States,":[53],"Australia.":[58],"The":[59,118,150,209],"availability":[60],"remotely":[62],"sensed":[63],"data":[64,80,98,212],"vastly":[66],"improved,":[67],"enables":[69],"us":[70],"precisely":[72],"locate":[73],"for":[75,114,127,143,154,205,221,229,281],"monitoring":[76],"purposes.":[77],"Wildfire":[78],"inventory":[79,119,211],"was":[81,131,213,240],"created":[82],"by":[83,258],"integrating":[84],"polygons":[86],"collected":[87,99],"through":[88],"field":[89],"surveys":[90],"using":[91],"global":[92],"positioning":[93],"systems":[94],"(GPS)":[95],"from":[100],"moderate":[102],"resolution":[103],"imaging":[104],"spectrometer":[105],"(MODIS)":[106],"thermal":[107],"anomalies":[108],"product":[109],"between":[110],"2012":[111],"2017":[113],"study":[116,129,156,288],"area.":[117,289],"data,":[120],"along":[121,192],"sixteen":[123],"conditioning":[124],"factors":[125],"selected":[126],"area,":[130],"used":[132,220,228,241],"appraise":[134],"potential":[136],"various":[138],"machine":[139,186],"learning":[140],"(ML)":[141],"methods":[142,152],"wildfire":[144,206,210,282],"susceptibility":[145,207,283],"mapping":[146],"Amol":[148],"County.":[149],"ML":[151,248],"chosen":[153],"this":[155],"artificial":[158],"neural":[159],"network":[160],"(ANN),":[161],"dmine":[162],"regression":[163,169,199],"(DR),":[164],"DM":[165],"neural,":[166],"least":[167],"angle":[168],"(LARS),":[170],"multi-layer":[171],"perceptron":[172],"(MLP),":[173],"random":[174],"(RF),":[176],"radial":[177],"basis":[178],"function":[179],"(RBF),":[180],"self-organizing":[181],"maps":[182],"(SOM),":[183],"support":[184],"vector":[185],"(SVM),":[187],"decision":[189],"tree":[190],"(DT),":[191],"statistical":[195],"approach":[196],"logistic":[198],"(LR),":[200],"which":[201],"is":[202,278],"very":[203],"apt":[204],"studies.":[208],"categorized":[214],"three-fold,":[216],"66%":[218],"being":[219,227],"training":[222],"models":[224],"33%":[226],"accuracy":[230,245,254,262,271],"assessment":[231],"within":[232],"three-fold":[233],"cross-validation":[234],"(CV).":[235],"Receiver":[236],"operating":[237],"characteristics":[238],"(ROC)":[239],"assess":[243],"approaches.":[249],"RF":[250,277],"had":[251,268],"highest":[253],"88%,":[256],"followed":[257],"SVM":[259],"an":[261],"almost":[264],"79%,":[265],"LR":[267],"lowest":[270],"65%.":[273],"This":[274],"shows":[275],"that":[276],"better":[279],"suited":[280],"assessments":[284],"our":[286],"case":[287]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":6}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}