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dc.contributor.editorMohammad Mokhtaries
dc.creatorRamírez Juidias, Emilioes
dc.creatorCabello Franco, Emilio Josées
dc.date.accessioned2024-02-20T18:37:21Z
dc.date.available2024-02-20T18:37:21Z
dc.date.issued2023-07-19
dc.identifier.citationRamírez Juidias, E. y Cabello Franco, E.J. (2023). New Remote Sensing Technologies Applied to the Prediction of Spontaneous Forest Fires. En Mohammad Mokhtari (Ed.), Natural Hazards - New Insights (pp. 327-342). Londres: Intechopen.
dc.identifier.isbn978-1-80355-850-9es
dc.identifier.urihttps://hdl.handle.net/11441/155396
dc.description.abstractOne of the causes of a forest fire is a combination of environmental variables such as temperature and relative humidity, as well as wind speed. When environmental conditions are favorable, chemical reactions occur at the forest mass level, resulting in pre-ignition. A big-data analysis of three spontaneous forest fires that occurred in Spain between 2015 and 2019 was performed to determine the chemical compound from which the forest fire starts. After analyzing satellite data, it was discovered that the critical temperature at which a fire starts spontaneously is 51.27°C, a value that coincides with the maximum limit of decrease in environmental sulfur dioxide concentration ([SO2]), presumably due to sulfur capture by part of the wood, an element that is released into the environment after the fire occurs. The Spontaneous Forest Fire Process (SFFP) and fAPAR have a close relationship because pre-ignition occurs when the critical temperature determined by environmental conditions is reached.es
dc.formatapplication/pdfes
dc.format.extent16es
dc.language.isoenges
dc.publisherIntechopenes
dc.relation.ispartofNatural Hazards - New Insightses
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectsulfur dioxidees
dc.subjectthermal plugginges
dc.subjectBroglie Lawes
dc.subjectIberian Peninsulaes
dc.subjectremote sensing technologieses
dc.titleNew Remote Sensing Technologies Applied to the Prediction of Spontaneous Forest Fireses
dc.typeinfo:eu-repo/semantics/bookPartes
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería Gráficaes
dc.identifier.doihttp://dx.doi.org/10.5772/intechopen.110501es
dc.publication.initialPage327
dc.publication.endPage342
dc.relation.publicationplaceLondreses

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