Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy
Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapte...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Elia, Mario [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2015 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental management - New York, NY : Springer, 1976, 56(2015), 3 vom: 12. Mai, Seite 754-764 |
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| Übergeordnetes Werk: |
volume:56 ; year:2015 ; number:3 ; day:12 ; month:05 ; pages:754-764 |
| Links: |
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| DOI / URN: |
10.1007/s00267-015-0531-z |
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| Katalog-ID: |
SPR003383482 |
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| 245 | 1 | 0 | |a Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy |
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| 520 | |a Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. | ||
| 650 | 4 | |a Fire management |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Cluster analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Mediterranean basin |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Fuel model |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wildland fire |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wildland–urban interface |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Lafortezza, Raffaele |4 aut | |
| 700 | 1 | |a Lovreglio, Raffaella |4 aut | |
| 700 | 1 | |a Sanesi, Giovanni |4 aut | |
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10.1007/s00267-015-0531-z doi (DE-627)SPR003383482 (SPR)s00267-015-0531-z-e DE-627 ger DE-627 rakwb eng Elia, Mario verfasserin aut Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2015 Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 Lafortezza, Raffaele aut Lovreglio, Raffaella aut Sanesi, Giovanni aut Enthalten in Environmental management New York, NY : Springer, 1976 56(2015), 3 vom: 12. Mai, Seite 754-764 (DE-627)27117532X (DE-600)1478932-2 1432-1009 nnns volume:56 year:2015 number:3 day:12 month:05 pages:754-764 https://dx.doi.org/10.1007/s00267-015-0531-z 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 56 2015 3 12 05 754-764 |
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10.1007/s00267-015-0531-z doi (DE-627)SPR003383482 (SPR)s00267-015-0531-z-e DE-627 ger DE-627 rakwb eng Elia, Mario verfasserin aut Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2015 Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 Lafortezza, Raffaele aut Lovreglio, Raffaella aut Sanesi, Giovanni aut Enthalten in Environmental management New York, NY : Springer, 1976 56(2015), 3 vom: 12. Mai, Seite 754-764 (DE-627)27117532X (DE-600)1478932-2 1432-1009 nnns volume:56 year:2015 number:3 day:12 month:05 pages:754-764 https://dx.doi.org/10.1007/s00267-015-0531-z 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 56 2015 3 12 05 754-764 |
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10.1007/s00267-015-0531-z doi (DE-627)SPR003383482 (SPR)s00267-015-0531-z-e DE-627 ger DE-627 rakwb eng Elia, Mario verfasserin aut Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2015 Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 Lafortezza, Raffaele aut Lovreglio, Raffaella aut Sanesi, Giovanni aut Enthalten in Environmental management New York, NY : Springer, 1976 56(2015), 3 vom: 12. Mai, Seite 754-764 (DE-627)27117532X (DE-600)1478932-2 1432-1009 nnns volume:56 year:2015 number:3 day:12 month:05 pages:754-764 https://dx.doi.org/10.1007/s00267-015-0531-z 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 56 2015 3 12 05 754-764 |
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10.1007/s00267-015-0531-z doi (DE-627)SPR003383482 (SPR)s00267-015-0531-z-e DE-627 ger DE-627 rakwb eng Elia, Mario verfasserin aut Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2015 Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 Lafortezza, Raffaele aut Lovreglio, Raffaella aut Sanesi, Giovanni aut Enthalten in Environmental management New York, NY : Springer, 1976 56(2015), 3 vom: 12. Mai, Seite 754-764 (DE-627)27117532X (DE-600)1478932-2 1432-1009 nnns volume:56 year:2015 number:3 day:12 month:05 pages:754-764 https://dx.doi.org/10.1007/s00267-015-0531-z 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 56 2015 3 12 05 754-764 |
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10.1007/s00267-015-0531-z doi (DE-627)SPR003383482 (SPR)s00267-015-0531-z-e DE-627 ger DE-627 rakwb eng Elia, Mario verfasserin aut Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Science+Business Media New York 2015 Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 Lafortezza, Raffaele aut Lovreglio, Raffaella aut Sanesi, Giovanni aut Enthalten in Environmental management New York, NY : Springer, 1976 56(2015), 3 vom: 12. Mai, Seite 754-764 (DE-627)27117532X (DE-600)1478932-2 1432-1009 nnns volume:56 year:2015 number:3 day:12 month:05 pages:754-764 https://dx.doi.org/10.1007/s00267-015-0531-z 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_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_4012 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 56 2015 3 12 05 754-764 |
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Enthalten in Environmental management 56(2015), 3 vom: 12. Mai, Seite 754-764 volume:56 year:2015 number:3 day:12 month:05 pages:754-764 |
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Enthalten in Environmental management 56(2015), 3 vom: 12. Mai, Seite 754-764 volume:56 year:2015 number:3 day:12 month:05 pages:754-764 |
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Elia, Mario @@aut@@ Lafortezza, Raffaele @@aut@@ Lovreglio, Raffaella @@aut@@ Sanesi, Giovanni @@aut@@ |
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Elia, Mario |
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Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy Fire management (dpeaa)DE-He213 Cluster analysis (dpeaa)DE-He213 Mediterranean basin (dpeaa)DE-He213 Fuel model (dpeaa)DE-He213 Wildland fire (dpeaa)DE-He213 Wildland–urban interface (dpeaa)DE-He213 |
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developing custom fire behavior fuel models for mediterranean wildland–urban interfaces in southern italy |
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Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy |
| abstract |
Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. © Springer Science+Business Media New York 2015 |
| abstractGer |
Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. © Springer Science+Business Media New York 2015 |
| abstract_unstemmed |
Abstract The dramatic increase of fire hazard in wildland–urban interfaces (WUIs) has required more detailed fuel management programs to preserve ecosystem functions and human settlements. Designing effective fuel treatment strategies allows to achieve goals such as resilient landscapes, fire-adapted communities, and ecosystem response. Therefore, obtaining background information on forest fuel parameters and fuel accumulation patterns has become an important first step in planning fuel management interventions. Site-specific fuel inventory data enhance the accuracy of fuel management planning and help forest managers in fuel management decision-making. We have customized four fuel models for WUIs in southern Italy, starting from forest classes of land-cover use and adopting a hierarchical clustering approach. Furthermore, we provide a prediction of the potential fire behavior of our customized fuel models using FlamMap 5 under different weather conditions. The results suggest that fuel model IIIP (Mediterranean maquis) has the most severe fire potential for the 95th percentile weather conditions and the least severe potential fire behavior for the 85th percentile weather conditions. This study shows that it is possible to create customized fuel models directly from fuel inventory data. This achievement has broad implications for land managers, particularly forest managers of the Mediterranean landscape, an ecosystem that is susceptible not only to wildfires but also to the increasing human population and man-made infrastructures. © Springer Science+Business Media New York 2015 |
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Developing Custom Fire Behavior Fuel Models for Mediterranean Wildland–Urban Interfaces in Southern Italy |
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Lafortezza, Raffaele Lovreglio, Raffaella Sanesi, Giovanni |
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2024-07-03T19:13:21.894Z |
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| score |
7.3999014 |