Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis
Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was init...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
de Sousa, Jocy Ana Paixão [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer Nature B.V. 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Natural hazards - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988, 114(2022), 2 vom: 16. Juli, Seite 2311-2330 |
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| Übergeordnetes Werk: |
volume:114 ; year:2022 ; number:2 ; day:16 ; month:07 ; pages:2311-2330 |
| Links: |
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| DOI / URN: |
10.1007/s11069-022-05473-x |
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| Katalog-ID: |
SPR048410284 |
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| 520 | |a Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. | ||
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| 700 | 1 | |a Lourenço, Roberto Wagner |0 (orcid)0000-0002-5234-8944 |4 aut | |
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10.1007/s11069-022-05473-x doi (DE-627)SPR048410284 (SPR)s11069-022-05473-x-e DE-627 ger DE-627 rakwb eng de Sousa, Jocy Ana Paixão verfasserin (orcid)0000-0003-0937-786X aut Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2022 Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 do Nascimento Lopes, Elfany Reis (orcid)0000-0003-1269-3986 aut Duarte, Miqueias Lima (orcid)0000-0001-8232-4655 aut Ewbank, Henrique (orcid)0000-0003-4018-218X aut Lourenço, Roberto Wagner (orcid)0000-0002-5234-8944 aut Enthalten in Natural hazards Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988 114(2022), 2 vom: 16. Juli, Seite 2311-2330 (DE-627)315621729 (DE-600)2017806-2 1573-0840 nnns volume:114 year:2022 number:2 day:16 month:07 pages:2311-2330 https://dx.doi.org/10.1007/s11069-022-05473-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 114 2022 2 16 07 2311-2330 |
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10.1007/s11069-022-05473-x doi (DE-627)SPR048410284 (SPR)s11069-022-05473-x-e DE-627 ger DE-627 rakwb eng de Sousa, Jocy Ana Paixão verfasserin (orcid)0000-0003-0937-786X aut Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2022 Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 do Nascimento Lopes, Elfany Reis (orcid)0000-0003-1269-3986 aut Duarte, Miqueias Lima (orcid)0000-0001-8232-4655 aut Ewbank, Henrique (orcid)0000-0003-4018-218X aut Lourenço, Roberto Wagner (orcid)0000-0002-5234-8944 aut Enthalten in Natural hazards Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988 114(2022), 2 vom: 16. Juli, Seite 2311-2330 (DE-627)315621729 (DE-600)2017806-2 1573-0840 nnns volume:114 year:2022 number:2 day:16 month:07 pages:2311-2330 https://dx.doi.org/10.1007/s11069-022-05473-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 114 2022 2 16 07 2311-2330 |
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10.1007/s11069-022-05473-x doi (DE-627)SPR048410284 (SPR)s11069-022-05473-x-e DE-627 ger DE-627 rakwb eng de Sousa, Jocy Ana Paixão verfasserin (orcid)0000-0003-0937-786X aut Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2022 Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 do Nascimento Lopes, Elfany Reis (orcid)0000-0003-1269-3986 aut Duarte, Miqueias Lima (orcid)0000-0001-8232-4655 aut Ewbank, Henrique (orcid)0000-0003-4018-218X aut Lourenço, Roberto Wagner (orcid)0000-0002-5234-8944 aut Enthalten in Natural hazards Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988 114(2022), 2 vom: 16. Juli, Seite 2311-2330 (DE-627)315621729 (DE-600)2017806-2 1573-0840 nnns volume:114 year:2022 number:2 day:16 month:07 pages:2311-2330 https://dx.doi.org/10.1007/s11069-022-05473-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 114 2022 2 16 07 2311-2330 |
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10.1007/s11069-022-05473-x doi (DE-627)SPR048410284 (SPR)s11069-022-05473-x-e DE-627 ger DE-627 rakwb eng de Sousa, Jocy Ana Paixão verfasserin (orcid)0000-0003-0937-786X aut Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2022 Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 do Nascimento Lopes, Elfany Reis (orcid)0000-0003-1269-3986 aut Duarte, Miqueias Lima (orcid)0000-0001-8232-4655 aut Ewbank, Henrique (orcid)0000-0003-4018-218X aut Lourenço, Roberto Wagner (orcid)0000-0002-5234-8944 aut Enthalten in Natural hazards Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988 114(2022), 2 vom: 16. Juli, Seite 2311-2330 (DE-627)315621729 (DE-600)2017806-2 1573-0840 nnns volume:114 year:2022 number:2 day:16 month:07 pages:2311-2330 https://dx.doi.org/10.1007/s11069-022-05473-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 114 2022 2 16 07 2311-2330 |
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10.1007/s11069-022-05473-x doi (DE-627)SPR048410284 (SPR)s11069-022-05473-x-e DE-627 ger DE-627 rakwb eng de Sousa, Jocy Ana Paixão verfasserin (orcid)0000-0003-0937-786X aut Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature B.V. 2022 Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 do Nascimento Lopes, Elfany Reis (orcid)0000-0003-1269-3986 aut Duarte, Miqueias Lima (orcid)0000-0001-8232-4655 aut Ewbank, Henrique (orcid)0000-0003-4018-218X aut Lourenço, Roberto Wagner (orcid)0000-0002-5234-8944 aut Enthalten in Natural hazards Dordrecht [u.a.] : Springer Science + Business Media B.V., 1988 114(2022), 2 vom: 16. Juli, Seite 2311-2330 (DE-627)315621729 (DE-600)2017806-2 1573-0840 nnns volume:114 year:2022 number:2 day:16 month:07 pages:2311-2330 https://dx.doi.org/10.1007/s11069-022-05473-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 114 2022 2 16 07 2311-2330 |
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de Sousa, Jocy Ana Paixão @@aut@@ do Nascimento Lopes, Elfany Reis @@aut@@ Duarte, Miqueias Lima @@aut@@ Ewbank, Henrique @@aut@@ Lourenço, Roberto Wagner @@aut@@ |
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de Sousa, Jocy Ana Paixão |
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Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis Forest loss (dpeaa)DE-He213 Fire susceptibility (dpeaa)DE-He213 Fire outbreaks (dpeaa)DE-He213 Forest ecosystems (dpeaa)DE-He213 |
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forest fire risk indicator (ffri) based on geoprocessing and multicriteria analysis |
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Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis |
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Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. © The Author(s), under exclusive licence to Springer Nature B.V. 2022 |
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Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. © The Author(s), under exclusive licence to Springer Nature B.V. 2022 |
| abstract_unstemmed |
Abstract Forest fires negatively impact ecosystem services, affecting human welfare. The present study proposes a Forest Fire Risk Indicator (FFRI) based on the Fire and Burn Risk Indicator (FBRI). The instrument was applied to the Sorocabuçu River Basin in São Paulo State, Brazil. The FBRI was initially obtained by using the factors that most contribute to the start or spread of fires according to the literature. These factors were later grouped into anthropogenic, topographic, land cover/land use, and climatic variables. The factors of each variable were classified into intervals to which a fire risk value was assigned ranging from 0 (null risk) to 1 (very high risk). By applying the Analytical Hierarchy Process, we obtained the final FBRI, after which the FFRI was created. The final FBRI showed predominantly high risks (64.78%) throughout the basin, as well as the FFRI (82.56%). The present study evidences that most forest fragments need measures for ecosystem protection. This can be done in different ways such as monitoring through fire towers and conduction of environmental education activities. © The Author(s), under exclusive licence to Springer Nature B.V. 2022 |
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Forest fire risk indicator (FFRI) based on geoprocessing and multicriteria analysis |
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do Nascimento Lopes, Elfany Reis Duarte, Miqueias Lima Ewbank, Henrique Lourenço, Roberto Wagner |
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10.1007/s11069-022-05473-x |
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| score |
7.4002275 |