A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data

(1) Background: Hurricane events are expected to increase as a consequence of climate change, increasing their intensity and severity. Destructive hurricane activities pose the greatest threat to coastal communities along the U.S. Gulf of Mexico and Atlantic Coasts in the conterminous United States....

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Autor principal:	Gainbi Park
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	hurricane damage storm surge wind damage geospatial big data hurricane-prone coastal counties population vulnerability Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/1f80a31d2c6b48389081300e2d8eb599
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spelling	oai:doaj.org-article:1f80a31d2c6b48389081300e2d8eb5992021-11-25T17:53:13ZA Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data10.3390/ijgi101107812220-9964https://doaj.org/article/1f80a31d2c6b48389081300e2d8eb5992021-11-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/781https://doaj.org/toc/2220-9964(1) Background: Hurricane events are expected to increase as a consequence of climate change, increasing their intensity and severity. Destructive hurricane activities pose the greatest threat to coastal communities along the U.S. Gulf of Mexico and Atlantic Coasts in the conterminous United States. This study investigated the historical extent of hurricane-related damage, identifying the most at-risk areas of hurricanes using geospatial big data. As a supplement to analysis, this study further examined the overall population trend within the hurricane at-risk zones. (2) Methods: The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model and the HURRECON model were used to estimate the geographical extent of the storm surge inundation and wind damage of historical hurricanes from 1950 to 2018. The modeled results from every hurricane were then aggregated to a single unified spatial surface to examine the generalized hurricane patterns across the affected coastal counties. Based on this singular spatial boundary coupled with demographic datasets, zonal analysis was applied to explore the historical population at risk. (3) Results: A total of 777 counties were found to comprise the “hurricane-prone coastal counties” that have experienced at least one instance of hurricane damage over the study period. The overall demographic trends within the hurricane-prone coastal counties revealed that the coastal populations are growing at a faster pace than the national average, and this growth puts more people at greater risk of hurricane hazards. (4) Conclusions: This study is the first comprehensive investigation of hurricane vulnerability encompassing the Atlantic and Gulf Coasts stretching from Texas to Maine over a long span of time. The findings from this study can serve as a basis for understanding the exposure of at-risk populations to hurricane-related damage within the coastal counties at a national scale.Gainbi ParkMDPI AGarticlehurricane damagestorm surgewind damagegeospatial big datahurricane-prone coastal countiespopulation vulnerabilityGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 781, p 781 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hurricane damage storm surge wind damage geospatial big data hurricane-prone coastal counties population vulnerability Geography (General) G1-922
spellingShingle	hurricane damage storm surge wind damage geospatial big data hurricane-prone coastal counties population vulnerability Geography (General) G1-922 Gainbi Park A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
description	(1) Background: Hurricane events are expected to increase as a consequence of climate change, increasing their intensity and severity. Destructive hurricane activities pose the greatest threat to coastal communities along the U.S. Gulf of Mexico and Atlantic Coasts in the conterminous United States. This study investigated the historical extent of hurricane-related damage, identifying the most at-risk areas of hurricanes using geospatial big data. As a supplement to analysis, this study further examined the overall population trend within the hurricane at-risk zones. (2) Methods: The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model and the HURRECON model were used to estimate the geographical extent of the storm surge inundation and wind damage of historical hurricanes from 1950 to 2018. The modeled results from every hurricane were then aggregated to a single unified spatial surface to examine the generalized hurricane patterns across the affected coastal counties. Based on this singular spatial boundary coupled with demographic datasets, zonal analysis was applied to explore the historical population at risk. (3) Results: A total of 777 counties were found to comprise the “hurricane-prone coastal counties” that have experienced at least one instance of hurricane damage over the study period. The overall demographic trends within the hurricane-prone coastal counties revealed that the coastal populations are growing at a faster pace than the national average, and this growth puts more people at greater risk of hurricane hazards. (4) Conclusions: This study is the first comprehensive investigation of hurricane vulnerability encompassing the Atlantic and Gulf Coasts stretching from Texas to Maine over a long span of time. The findings from this study can serve as a basis for understanding the exposure of at-risk populations to hurricane-related damage within the coastal counties at a national scale.
format	article
author	Gainbi Park
author_facet	Gainbi Park
author_sort	Gainbi Park
title	A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
title_short	A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
title_full	A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
title_fullStr	A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
title_full_unstemmed	A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data
title_sort	comprehensive analysis of hurricane damage across the u.s. gulf and atlantic coasts using geospatial big data
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/1f80a31d2c6b48389081300e2d8eb599
work_keys_str_mv	AT gainbipark acomprehensiveanalysisofhurricanedamageacrosstheusgulfandatlanticcoastsusinggeospatialbigdata AT gainbipark comprehensiveanalysisofhurricanedamageacrosstheusgulfandatlanticcoastsusinggeospatialbigdata
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A Comprehensive Analysis of Hurricane Damage across the U.S. Gulf and Atlantic Coasts Using Geospatial Big Data

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