Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard
| Main Author: | |
|---|---|
| Publication Date: | 2020 |
| Other Authors: | , , , , , , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10362/104069 |
Summary: | Sakellariou, S., Cabral, P., Caetano, M., Pla, F., Painho, M., Christopoulou, O., ... Vasilakos, C. (2020). Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard. Sensors (Switzerland), 20(17), 1-20. [5014]. https://doi.org/10.3390/s20175014 |
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Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazardAnalytical Hierarchy ProcessForest fire hazardFuzzy logicRemote sensingSpatial variabilitySpatiotemporal analysisAnalytical ChemistryBiochemistryAtomic and Molecular Physics, and OpticsInstrumentationElectrical and Electronic EngineeringSDG 11 - Sustainable Cities and CommunitiesSDG 13 - Climate ActionSDG 15 - Life on LandSakellariou, S., Cabral, P., Caetano, M., Pla, F., Painho, M., Christopoulou, O., ... Vasilakos, C. (2020). Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard. Sensors (Switzerland), 20(17), 1-20. [5014]. https://doi.org/10.3390/s20175014Forest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Future projections predict that, under a climate change environment, the fire season would be lengthier with higher levels of droughts, leading to higher fire severity. The main aim of this paper is to perform a spatiotemporal analysis and explore the variability of fire hazard in a small Greek island, Skiathos (a prototype case of fragile environment) where the land uses mixture is very high. First, a comparative assessment of two robust modeling techniques was examined, namely, the Analytical Hierarchy Process (AHP) knowledge-based and the fuzzy logic AHP to estimate the fire hazard in a timeframe of 20 years (1996–2016). The former technique was proven more representative after the comparative assessment with the real fire perimeters recorded on the island (1984–2016). Next, we explored the spatiotemporal dynamics of fire hazard, highlighting the risk changes in space and time through the individual and collective contribution of the most significant factors (topography, vegetation features, anthropogenic influence). The fire hazard changes were not dramatic, however, some changes have been observed in the southwestern and northern part of the island. The geostatistical analysis revealed a significant clustering process of high-risk values in the southwestern and northern part of the study area, whereas some clusters of low-risk values have been located in the northern territory. The degree of spatial autocorrelation tends to be greater for 1996 rather than for 2016, indicating the potential higher transmission of fires at the most susceptible regions in the past. The knowledge of long-term fire hazard dynamics, based on multiple types of remotely sensed data, may provide the fire and land managers with valuable fire prevention and land use planning tools.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNSakellariou, StavrosCabral, PedroCaetano, MárioPla, FilibertoPainho, MarcoChristopoulou, OlgaSfougaris, AthanassiosDalezios, NicolasVasilakos, Christos2020-09-14T22:36:15Z2020-09-032020-09-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article20application/pdfhttp://hdl.handle.net/10362/104069eng1424-8220PURE: 19827865https://doi.org/10.3390/s20175014info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:47:30Zoai:run.unl.pt:10362/104069Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:18:42.122514Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| title |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| spellingShingle |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard Sakellariou, Stavros Analytical Hierarchy Process Forest fire hazard Fuzzy logic Remote sensing Spatial variability Spatiotemporal analysis Analytical Chemistry Biochemistry Atomic and Molecular Physics, and Optics Instrumentation Electrical and Electronic Engineering SDG 11 - Sustainable Cities and Communities SDG 13 - Climate Action SDG 15 - Life on Land |
| title_short |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| title_full |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| title_fullStr |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| title_full_unstemmed |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| title_sort |
Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard |
| author |
Sakellariou, Stavros |
| author_facet |
Sakellariou, Stavros Cabral, Pedro Caetano, Mário Pla, Filiberto Painho, Marco Christopoulou, Olga Sfougaris, Athanassios Dalezios, Nicolas Vasilakos, Christos |
| author_role |
author |
| author2 |
Cabral, Pedro Caetano, Mário Pla, Filiberto Painho, Marco Christopoulou, Olga Sfougaris, Athanassios Dalezios, Nicolas Vasilakos, Christos |
| author2_role |
author author author author author author author author |
| dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) Information Management Research Center (MagIC) - NOVA Information Management School RUN |
| dc.contributor.author.fl_str_mv |
Sakellariou, Stavros Cabral, Pedro Caetano, Mário Pla, Filiberto Painho, Marco Christopoulou, Olga Sfougaris, Athanassios Dalezios, Nicolas Vasilakos, Christos |
| dc.subject.por.fl_str_mv |
Analytical Hierarchy Process Forest fire hazard Fuzzy logic Remote sensing Spatial variability Spatiotemporal analysis Analytical Chemistry Biochemistry Atomic and Molecular Physics, and Optics Instrumentation Electrical and Electronic Engineering SDG 11 - Sustainable Cities and Communities SDG 13 - Climate Action SDG 15 - Life on Land |
| topic |
Analytical Hierarchy Process Forest fire hazard Fuzzy logic Remote sensing Spatial variability Spatiotemporal analysis Analytical Chemistry Biochemistry Atomic and Molecular Physics, and Optics Instrumentation Electrical and Electronic Engineering SDG 11 - Sustainable Cities and Communities SDG 13 - Climate Action SDG 15 - Life on Land |
| description |
Sakellariou, S., Cabral, P., Caetano, M., Pla, F., Painho, M., Christopoulou, O., ... Vasilakos, C. (2020). Remotely sensed data fusion for spatiotemporal geostatistical analysis of forest fire hazard. Sensors (Switzerland), 20(17), 1-20. [5014]. https://doi.org/10.3390/s20175014 |
| publishDate |
2020 |
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2020-09-14T22:36:15Z 2020-09-03 2020-09-03T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/10362/104069 |
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http://hdl.handle.net/10362/104069 |
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eng |
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eng |
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1424-8220 PURE: 19827865 https://doi.org/10.3390/s20175014 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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20 application/pdf |
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