A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces
Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements....
Ausführliche Beschreibung
Autor*in: |
Elia, Mario [verfasserIn] |
---|
Format: |
Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2014 |
---|
Schlagwörter: |
---|
Anmerkung: |
© Springer Science+Business Media Dordrecht 2014 |
---|
Übergeordnetes Werk: |
Enthalten in: Landscape ecology - Springer Netherlands, 1987, 29(2014), 10 vom: 27. Juli, Seite 1771-1784 |
---|---|
Übergeordnetes Werk: |
volume:29 ; year:2014 ; number:10 ; day:27 ; month:07 ; pages:1771-1784 |
Links: |
---|
DOI / URN: |
10.1007/s10980-014-0070-7 |
---|
Katalog-ID: |
OLC2075233675 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | OLC2075233675 | ||
003 | DE-627 | ||
005 | 20230503171203.0 | ||
007 | tu | ||
008 | 200820s2014 xx ||||| 00| ||eng c | ||
024 | 7 | |a 10.1007/s10980-014-0070-7 |2 doi | |
035 | |a (DE-627)OLC2075233675 | ||
035 | |a (DE-He213)s10980-014-0070-7-p | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 570 |a 910 |a 630 |q VZ |
084 | |a 12 |2 ssgn | ||
084 | |a BIODIV |q DE-30 |2 fid | ||
100 | 1 | |a Elia, Mario |e verfasserin |4 aut | |
245 | 1 | 0 | |a A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
264 | 1 | |c 2014 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
338 | |a Band |b nc |2 rdacarrier | ||
500 | |a © Springer Science+Business Media Dordrecht 2014 | ||
520 | |a Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. | ||
650 | 4 | |a Coupled Natural and Human Systems (CNHS) | |
650 | 4 | |a Fuel treatment | |
650 | 4 | |a Kernel density | |
650 | 4 | |a Mediterranean landscape | |
650 | 4 | |a Wildland–urban interface (WUI) | |
700 | 1 | |a Lafortezza, Raffaele |4 aut | |
700 | 1 | |a Colangelo, Giuseppe |4 aut | |
700 | 1 | |a Sanesi, Giovanni |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Landscape ecology |d Springer Netherlands, 1987 |g 29(2014), 10 vom: 27. Juli, Seite 1771-1784 |w (DE-627)130857424 |w (DE-600)1027798-5 |w (DE-576)052841901 |x 0921-2973 |7 nnns |
773 | 1 | 8 | |g volume:29 |g year:2014 |g number:10 |g day:27 |g month:07 |g pages:1771-1784 |
856 | 4 | 1 | |u https://doi.org/10.1007/s10980-014-0070-7 |z lizenzpflichtig |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_OLC | ||
912 | |a FID-BIODIV | ||
912 | |a SSG-OLC-ARC | ||
912 | |a SSG-OLC-FOR | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4082 | ||
912 | |a GBV_ILN_4219 | ||
951 | |a AR | ||
952 | |d 29 |j 2014 |e 10 |b 27 |c 07 |h 1771-1784 |
author_variant |
m e me r l rl g c gc g s gs |
---|---|
matchkey_str |
article:09212973:2014----::sralndprahoteptaalctoofermvliw |
hierarchy_sort_str |
2014 |
publishDate |
2014 |
allfields |
10.1007/s10980-014-0070-7 doi (DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Elia, Mario verfasserin aut A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media Dordrecht 2014 Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) Lafortezza, Raffaele aut Colangelo, Giuseppe aut Sanesi, Giovanni aut Enthalten in Landscape ecology Springer Netherlands, 1987 29(2014), 10 vom: 27. Juli, Seite 1771-1784 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 https://doi.org/10.1007/s10980-014-0070-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 AR 29 2014 10 27 07 1771-1784 |
spelling |
10.1007/s10980-014-0070-7 doi (DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Elia, Mario verfasserin aut A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media Dordrecht 2014 Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) Lafortezza, Raffaele aut Colangelo, Giuseppe aut Sanesi, Giovanni aut Enthalten in Landscape ecology Springer Netherlands, 1987 29(2014), 10 vom: 27. Juli, Seite 1771-1784 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 https://doi.org/10.1007/s10980-014-0070-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 AR 29 2014 10 27 07 1771-1784 |
allfields_unstemmed |
10.1007/s10980-014-0070-7 doi (DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Elia, Mario verfasserin aut A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media Dordrecht 2014 Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) Lafortezza, Raffaele aut Colangelo, Giuseppe aut Sanesi, Giovanni aut Enthalten in Landscape ecology Springer Netherlands, 1987 29(2014), 10 vom: 27. Juli, Seite 1771-1784 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 https://doi.org/10.1007/s10980-014-0070-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 AR 29 2014 10 27 07 1771-1784 |
allfieldsGer |
10.1007/s10980-014-0070-7 doi (DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Elia, Mario verfasserin aut A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media Dordrecht 2014 Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) Lafortezza, Raffaele aut Colangelo, Giuseppe aut Sanesi, Giovanni aut Enthalten in Landscape ecology Springer Netherlands, 1987 29(2014), 10 vom: 27. Juli, Seite 1771-1784 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 https://doi.org/10.1007/s10980-014-0070-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 AR 29 2014 10 27 07 1771-1784 |
allfieldsSound |
10.1007/s10980-014-0070-7 doi (DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p DE-627 ger DE-627 rakwb eng 570 910 630 VZ 12 ssgn BIODIV DE-30 fid Elia, Mario verfasserin aut A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media Dordrecht 2014 Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) Lafortezza, Raffaele aut Colangelo, Giuseppe aut Sanesi, Giovanni aut Enthalten in Landscape ecology Springer Netherlands, 1987 29(2014), 10 vom: 27. Juli, Seite 1771-1784 (DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 0921-2973 nnns volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 https://doi.org/10.1007/s10980-014-0070-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 AR 29 2014 10 27 07 1771-1784 |
language |
English |
source |
Enthalten in Landscape ecology 29(2014), 10 vom: 27. Juli, Seite 1771-1784 volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 |
sourceStr |
Enthalten in Landscape ecology 29(2014), 10 vom: 27. Juli, Seite 1771-1784 volume:29 year:2014 number:10 day:27 month:07 pages:1771-1784 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) |
dewey-raw |
570 |
isfreeaccess_bool |
false |
container_title |
Landscape ecology |
authorswithroles_txt_mv |
Elia, Mario @@aut@@ Lafortezza, Raffaele @@aut@@ Colangelo, Giuseppe @@aut@@ Sanesi, Giovanni @@aut@@ |
publishDateDaySort_date |
2014-07-27T00:00:00Z |
hierarchy_top_id |
130857424 |
dewey-sort |
3570 |
id |
OLC2075233675 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2075233675</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503171203.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2014 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10980-014-0070-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2075233675</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10980-014-0070-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="a">910</subfield><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">12</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Elia, Mario</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2014</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media Dordrecht 2014</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Coupled Natural and Human Systems (CNHS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fuel treatment</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Kernel density</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mediterranean landscape</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wildland–urban interface (WUI)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lafortezza, Raffaele</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Colangelo, Giuseppe</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sanesi, Giovanni</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Landscape ecology</subfield><subfield code="d">Springer Netherlands, 1987</subfield><subfield code="g">29(2014), 10 vom: 27. Juli, Seite 1771-1784</subfield><subfield code="w">(DE-627)130857424</subfield><subfield code="w">(DE-600)1027798-5</subfield><subfield code="w">(DE-576)052841901</subfield><subfield code="x">0921-2973</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:29</subfield><subfield code="g">year:2014</subfield><subfield code="g">number:10</subfield><subfield code="g">day:27</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:1771-1784</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10980-014-0070-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-ARC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4082</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4219</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">29</subfield><subfield code="j">2014</subfield><subfield code="e">10</subfield><subfield code="b">27</subfield><subfield code="c">07</subfield><subfield code="h">1771-1784</subfield></datafield></record></collection>
|
author |
Elia, Mario |
spellingShingle |
Elia, Mario ddc 570 ssgn 12 fid BIODIV misc Coupled Natural and Human Systems (CNHS) misc Fuel treatment misc Kernel density misc Mediterranean landscape misc Wildland–urban interface (WUI) A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
authorStr |
Elia, Mario |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)130857424 |
format |
Article |
dewey-ones |
570 - Life sciences; biology 910 - Geography & travel 630 - Agriculture & related technologies |
delete_txt_mv |
keep |
author_role |
aut aut aut aut |
collection |
OLC |
remote_str |
false |
illustrated |
Not Illustrated |
issn |
0921-2973 |
topic_title |
570 910 630 VZ 12 ssgn BIODIV DE-30 fid A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces Coupled Natural and Human Systems (CNHS) Fuel treatment Kernel density Mediterranean landscape Wildland–urban interface (WUI) |
topic |
ddc 570 ssgn 12 fid BIODIV misc Coupled Natural and Human Systems (CNHS) misc Fuel treatment misc Kernel density misc Mediterranean landscape misc Wildland–urban interface (WUI) |
topic_unstemmed |
ddc 570 ssgn 12 fid BIODIV misc Coupled Natural and Human Systems (CNHS) misc Fuel treatment misc Kernel density misc Mediterranean landscape misc Wildland–urban interface (WUI) |
topic_browse |
ddc 570 ssgn 12 fid BIODIV misc Coupled Natural and Human Systems (CNHS) misc Fuel treatment misc Kernel density misc Mediterranean landscape misc Wildland–urban interface (WUI) |
format_facet |
Aufsätze Gedruckte Aufsätze |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
nc |
hierarchy_parent_title |
Landscape ecology |
hierarchy_parent_id |
130857424 |
dewey-tens |
570 - Life sciences; biology 910 - Geography & travel 630 - Agriculture |
hierarchy_top_title |
Landscape ecology |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)130857424 (DE-600)1027798-5 (DE-576)052841901 |
title |
A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
ctrlnum |
(DE-627)OLC2075233675 (DE-He213)s10980-014-0070-7-p |
title_full |
A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
author_sort |
Elia, Mario |
journal |
Landscape ecology |
journalStr |
Landscape ecology |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
500 - Science 900 - History & geography 600 - Technology |
recordtype |
marc |
publishDateSort |
2014 |
contenttype_str_mv |
txt |
container_start_page |
1771 |
author_browse |
Elia, Mario Lafortezza, Raffaele Colangelo, Giuseppe Sanesi, Giovanni |
container_volume |
29 |
class |
570 910 630 VZ 12 ssgn BIODIV DE-30 fid |
format_se |
Aufsätze |
author-letter |
Elia, Mario |
doi_str_mv |
10.1007/s10980-014-0070-7 |
dewey-full |
570 910 630 |
title_sort |
a streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
title_auth |
A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
abstract |
Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. © Springer Science+Business Media Dordrecht 2014 |
abstractGer |
Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. © Springer Science+Business Media Dordrecht 2014 |
abstract_unstemmed |
Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources. © Springer Science+Business Media Dordrecht 2014 |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-ARC SSG-OLC-FOR GBV_ILN_70 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4219 |
container_issue |
10 |
title_short |
A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces |
url |
https://doi.org/10.1007/s10980-014-0070-7 |
remote_bool |
false |
author2 |
Lafortezza, Raffaele Colangelo, Giuseppe Sanesi, Giovanni |
author2Str |
Lafortezza, Raffaele Colangelo, Giuseppe Sanesi, Giovanni |
ppnlink |
130857424 |
mediatype_str_mv |
n |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1007/s10980-014-0070-7 |
up_date |
2024-07-04T00:46:36.267Z |
_version_ |
1803607339191762944 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2075233675</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503171203.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200820s2014 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s10980-014-0070-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2075233675</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s10980-014-0070-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="a">910</subfield><subfield code="a">630</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">12</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Elia, Mario</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">A streamlined approach for the spatial allocation of fuel removals in wildland–urban interfaces</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2014</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media Dordrecht 2014</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Major concerns are arising on the expansion of wildland–urban interfaces defined as zones where infrastructures and other man-made systems interact with undeveloped areas. Wildland–urban interfaces create an environment in which fire can easily spread from forest fuels to human settlements. In this context, there is a need to prevent fire spread by determining the sound allocation of fuel treatment (fuel removal). To this end, the Spatial Allocation Index was developed as a streamlined approach to determine where and what type of forest areas may be eligible for fuel removal in terms of fire suppression. This approach was developed as a case study example using forest landscapes located in the province of Taranto (Apulia region) in southern Italy. By using geostatistical techniques, we scaled up 210 data points of plot-level fuel load and developed maps for different forest types. These spatial predictions were combined with other landscape-level variables such as population density, urban density, and road density. Through our modelling approach we were able to determine the fuel model types and spatial allocations of wildland areas that are likely to be treated by fuel removal. Our results suggest that the predominant forest typology requiring treatment in the study area is the Mediterranean maquis (shrub-land), which covers 44 % of the wildland–urban interface landscape. The areas on the map where the Spatial Allocation Index reaches its maximum value are those with the highest priority in terms of fuel removal; i.e., the highest number of people, houses, and roads benefitting from wildfire suppression. By adopting this streamlined approach, forest managers and decision makers may avail of a fast and effective tool to improve efforts in landscape management and budgeting of financial resources.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Coupled Natural and Human Systems (CNHS)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fuel treatment</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Kernel density</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mediterranean landscape</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Wildland–urban interface (WUI)</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lafortezza, Raffaele</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Colangelo, Giuseppe</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sanesi, Giovanni</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Landscape ecology</subfield><subfield code="d">Springer Netherlands, 1987</subfield><subfield code="g">29(2014), 10 vom: 27. Juli, Seite 1771-1784</subfield><subfield code="w">(DE-627)130857424</subfield><subfield code="w">(DE-600)1027798-5</subfield><subfield code="w">(DE-576)052841901</subfield><subfield code="x">0921-2973</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:29</subfield><subfield code="g">year:2014</subfield><subfield code="g">number:10</subfield><subfield code="g">day:27</subfield><subfield code="g">month:07</subfield><subfield code="g">pages:1771-1784</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s10980-014-0070-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-ARC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4082</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4219</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">29</subfield><subfield code="j">2014</subfield><subfield code="e">10</subfield><subfield code="b">27</subfield><subfield code="c">07</subfield><subfield code="h">1771-1784</subfield></datafield></record></collection>
|
score |
7.400649 |