@prefix adms: . @prefix cnt: . @prefix dc: . @prefix dcat: . @prefix dcmitype: . @prefix dct: . @prefix foaf: . @prefix gsp: . @prefix locn: . @prefix rdf: . @prefix rdfs: . @prefix vcard: . @prefix xsd: . a dct:LinguisticSystem . a dct:LinguisticSystem . a dcat:Dataset ; dc:language "es" ; dct:accessRights ; dct:conformsTo , , ; dct:created "2025-05-23"^^xsd:date ; dct:creator [ a foaf:Agent ; dct:identifier "E05068001" ; dct:type ; foaf:mbox ; foaf:name "Martínez, J., Vega-Garcia, C. y Chuvieco, E."@es ] ; dct:description "This paper identifies human factors associated with high forest fire risk in Spain and analyses the spatial distribution of fire occurrence in the country. The spatial units were 6,066 municipalities of the Spanish peninsular territory and Balearic Islands. The study covered a 13-year series of fire occurrence data. One hundred and eight variables were generated and input to a dedicated Geographic Information System (GIS) to model different factors related to fire ignition. After exploratory analysis, 29 were selected to build a predictive model of human fire ignition using logistic regression analysis. The binary model estimated the probability of high or low occurrence of forest fires, as defined by an ignition danger index that is currently used by the Spanish forest service (number of fires divided by forest area in each municipality). Thirteen explanatory variables were identified by the model. They were related to agricultural …"@en, "This paper identifies human factors associated with high forest fire risk in Spain and analyses the spatial distribution of fire occurrence in the country. The spatial units were 6,066 municipalities of the Spanish peninsular territory and Balearic Islands. The study covered a 13-year series of fire occurrence data. One hundred and eight variables were generated and input to a dedicated Geographic Information System (GIS) to model different factors related to fire ignition. After exploratory analysis, 29 were selected to build a predictive model of human fire ignition using logistic regression analysis. The binary model estimated the probability of high or low occurrence of forest fires, as defined by an ignition danger index that is currently used by the Spanish forest service (number of fires divided by forest area in each municipality). Thirteen explanatory variables were identified by the model."@es ; dct:identifier "https://pro.iepnb.gob.es/catalogo/dataset/bfbece04-59e6-5015-831b-6295e9690c3e" ; dct:issued "2025-05-23T00:00:00+00:00"^^xsd:dateTime ; dct:license ; dct:modified "2026-06-25T00:00:00+00:00"^^xsd:dateTime ; dct:publisher ; dct:spatial ; dct:title "Human-caused wildfire risk rating for prevention planning in Spain."@es ; dct:type dcmitype:Text ; adms:status ; dcat:contactPoint ; dcat:distribution ; dcat:keyword "fragmentacion"@es ; dcat:landingPage ; dcat:theme . a foaf:Agent . a dct:Location ; locn:geometry "POLYGON ((-18.1600 27.6400, 4.3200 27.6400, 4.3200 43.7900, -18.1600 43.7900, -18.1600 27.6400))"^^gsp:wktLiteral . a foaf:Document . a dcat:Distribution ; dc:language "es" ; dct:accessRights ; dct:byteSize 0 ; dct:description "Revista"@es ; dct:format [ a dct:IMT ; rdfs:label "HTML" ; rdf:value "text/html" ] ; dct:identifier "https://pro.iepnb.gob.es/catalogo/dataset/bfbece04-59e6-5015-831b-6295e9690c3e/resource/5c13b91c-8fb8-4436-9d4d-70229275b934" ; dct:issued "2009-02-01T00:00:00+00:00"^^xsd:dateTime ; dct:license , ; dct:modified "2026-06-25T00:00:00+00:00"^^xsd:dateTime ; dct:title "Acceso al recurso"@es ; cnt:characterEncoding "UTF-8" ; dcat:accessURL . a vcard:Kind ; vcard:fn "Organismo publicador del Catálogo"@es ; vcard:hasEmail ; vcard:hasURL ; vcard:role . a dct:Standard . dct:type .