Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia

Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Williams, George T. [verfasserIn] Jenkins, Susanna F. [verfasserIn] Biass, Sébastien [verfasserIn] Wibowo, Haryo Edi [verfasserIn] Harijoko, Agung [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Damage survey Remote sensing Vulnerability functions Volcanic ash Structures Kelud 2014 eruption

Übergeordnetes Werk:	Enthalten in: Journal of applied volcanology - Berlin : Springer, 2012, 9(2020), 1 vom: 24. Nov.
Übergeordnetes Werk:	volume:9 ; year:2020 ; number:1 ; day:24 ; month:11

Links:	Volltext

DOI / URN:	10.1186/s13617-020-00100-5

Katalog-ID:	SPR042117593

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520			\|a Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions.
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allfields	10.1186/s13617-020-00100-5 doi (DE-627)SPR042117593 (SPR)s13617-020-00100-5-e DE-627 ger DE-627 rakwb eng 550 ASE Williams, George T. verfasserin aut Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Damage survey (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Vulnerability functions (dpeaa)DE-He213 Volcanic ash (dpeaa)DE-He213 Structures (dpeaa)DE-He213 Kelud 2014 eruption (dpeaa)DE-He213 Jenkins, Susanna F. verfasserin aut Biass, Sébastien verfasserin aut Wibowo, Haryo Edi verfasserin aut Harijoko, Agung verfasserin aut Enthalten in Journal of applied volcanology Berlin : Springer, 2012 9(2020), 1 vom: 24. Nov. (DE-627)689717725 (DE-600)2657636-3 2191-5040 nnns volume:9 year:2020 number:1 day:24 month:11 https://dx.doi.org/10.1186/s13617-020-00100-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 1 24 11
spelling	10.1186/s13617-020-00100-5 doi (DE-627)SPR042117593 (SPR)s13617-020-00100-5-e DE-627 ger DE-627 rakwb eng 550 ASE Williams, George T. verfasserin aut Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Damage survey (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Vulnerability functions (dpeaa)DE-He213 Volcanic ash (dpeaa)DE-He213 Structures (dpeaa)DE-He213 Kelud 2014 eruption (dpeaa)DE-He213 Jenkins, Susanna F. verfasserin aut Biass, Sébastien verfasserin aut Wibowo, Haryo Edi verfasserin aut Harijoko, Agung verfasserin aut Enthalten in Journal of applied volcanology Berlin : Springer, 2012 9(2020), 1 vom: 24. Nov. (DE-627)689717725 (DE-600)2657636-3 2191-5040 nnns volume:9 year:2020 number:1 day:24 month:11 https://dx.doi.org/10.1186/s13617-020-00100-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 1 24 11
allfields_unstemmed	10.1186/s13617-020-00100-5 doi (DE-627)SPR042117593 (SPR)s13617-020-00100-5-e DE-627 ger DE-627 rakwb eng 550 ASE Williams, George T. verfasserin aut Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Damage survey (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Vulnerability functions (dpeaa)DE-He213 Volcanic ash (dpeaa)DE-He213 Structures (dpeaa)DE-He213 Kelud 2014 eruption (dpeaa)DE-He213 Jenkins, Susanna F. verfasserin aut Biass, Sébastien verfasserin aut Wibowo, Haryo Edi verfasserin aut Harijoko, Agung verfasserin aut Enthalten in Journal of applied volcanology Berlin : Springer, 2012 9(2020), 1 vom: 24. Nov. (DE-627)689717725 (DE-600)2657636-3 2191-5040 nnns volume:9 year:2020 number:1 day:24 month:11 https://dx.doi.org/10.1186/s13617-020-00100-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 1 24 11
allfieldsGer	10.1186/s13617-020-00100-5 doi (DE-627)SPR042117593 (SPR)s13617-020-00100-5-e DE-627 ger DE-627 rakwb eng 550 ASE Williams, George T. verfasserin aut Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Damage survey (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Vulnerability functions (dpeaa)DE-He213 Volcanic ash (dpeaa)DE-He213 Structures (dpeaa)DE-He213 Kelud 2014 eruption (dpeaa)DE-He213 Jenkins, Susanna F. verfasserin aut Biass, Sébastien verfasserin aut Wibowo, Haryo Edi verfasserin aut Harijoko, Agung verfasserin aut Enthalten in Journal of applied volcanology Berlin : Springer, 2012 9(2020), 1 vom: 24. Nov. (DE-627)689717725 (DE-600)2657636-3 2191-5040 nnns volume:9 year:2020 number:1 day:24 month:11 https://dx.doi.org/10.1186/s13617-020-00100-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 1 24 11
allfieldsSound	10.1186/s13617-020-00100-5 doi (DE-627)SPR042117593 (SPR)s13617-020-00100-5-e DE-627 ger DE-627 rakwb eng 550 ASE Williams, George T. verfasserin aut Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions. Damage survey (dpeaa)DE-He213 Remote sensing (dpeaa)DE-He213 Vulnerability functions (dpeaa)DE-He213 Volcanic ash (dpeaa)DE-He213 Structures (dpeaa)DE-He213 Kelud 2014 eruption (dpeaa)DE-He213 Jenkins, Susanna F. verfasserin aut Biass, Sébastien verfasserin aut Wibowo, Haryo Edi verfasserin aut Harijoko, Agung verfasserin aut Enthalten in Journal of applied volcanology Berlin : Springer, 2012 9(2020), 1 vom: 24. Nov. (DE-627)689717725 (DE-600)2657636-3 2191-5040 nnns volume:9 year:2020 number:1 day:24 month:11 https://dx.doi.org/10.1186/s13617-020-00100-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GEO SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2020 1 24 11
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source	Enthalten in Journal of applied volcanology 9(2020), 1 vom: 24. Nov. volume:9 year:2020 number:1 day:24 month:11
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title	Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia
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title_sort	remotely assessing tephra fall building damage and vulnerability: kelud volcano, indonesia
title_auth	Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia
abstract	Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions.
abstractGer	Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions.
abstract_unstemmed	Abstract Tephra from large explosive eruptions can cause damage to buildings over wide geographical areas, creating a variety of issues for post-eruption recovery. This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions.
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This means that evaluating the extent and nature of likely building damage from future eruptions is an important aspect of volcanic risk assessment. However, our ability to make accurate assessments is currently limited by poor characterisation of how buildings perform under varying tephra loads. This study presents a method to remotely assess building damage to increase the quantity of data available for developing new tephra fall building vulnerability models. Given the large number of damaged buildings and the high potential for loss in future eruptions, we use the Kelud 2014 eruption as a case study. A total of 1154 buildings affected by falls 1–10 cm thick were assessed, with 790 showing signs that they sustained damage in the time between pre- and post-eruption satellite image acquisitions. Only 27 of the buildings surveyed appear to have experienced severe roof or building collapse. Damage was more commonly characterised by collapse of roof overhangs and verandas or damage that required roof cladding replacement. To estimate tephra loads received by each building we used Tephra2 inversion and interpolation of hand-contoured isopachs on the same set of deposit measurements. Combining tephra loads from both methods with our damage assessment, we develop the first sets of tephra fall fragility curves that consider damage severities lower than severe roof collapse. Weighted prediction accuracies are calculated for the curves using K-fold cross validation, with scores between 0.68 and 0.75 comparable to those for fragility curves developed for other natural hazards. Remote assessment of tephra fall building damage is highly complementary to traditional field-based surveying and both approaches should ideally be adopted to improve our understanding of tephra fall impacts following future damaging eruptions.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Damage survey</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Remote sensing</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Vulnerability functions</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Volcanic ash</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Structures</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Kelud 2014 eruption</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jenkins, Susanna F.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Biass, Sébastien</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wibowo, Haryo Edi</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harijoko, Agung</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of applied volcanology</subfield><subfield code="d">Berlin : Springer, 2012</subfield><subfield code="g">9(2020), 1 vom: 24. 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Remotely assessing tephra fall building damage and vulnerability: Kelud Volcano, Indonesia

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