Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing

Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal areas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely benefits sustainable development. This study uses the nighttime light (NTL) dat...

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Main Authors: Huang, Xiao, Wang, Cuizhen, Lu, Junyu
Format: Text
Language:English
Published: Scholar Commons 2019
Subjects:
Online Access:https://scholarcommons.sc.edu/geog_facpub/220
https://doi.org/10.5194/nhess-19-2141-2019;
https://scholarcommons.sc.edu/context/geog_facpub/article/1222/viewcontent/nhess_19_2141_2019__1_.pdf
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spelling ftunivsouthcar:oai:scholarcommons.sc.edu:geog_facpub-1222 2024-05-19T07:45:23+00:00 Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing Huang, Xiao Wang, Cuizhen Lu, Junyu 2019-10-01T07:00:00Z application/pdf https://scholarcommons.sc.edu/geog_facpub/220 https://doi.org/10.5194/nhess-19-2141-2019; https://scholarcommons.sc.edu/context/geog_facpub/article/1222/viewcontent/nhess_19_2141_2019__1_.pdf English eng Scholar Commons https://scholarcommons.sc.edu/geog_facpub/220 doi: https://doi.org/10.5194/nhess-19-2141-2019 https://scholarcommons.sc.edu/context/geog_facpub/article/1222/viewcontent/nhess_19_2141_2019__1_.pdf © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Faculty Publications Hurricane Hurricane-Prone United State Atlantic Gulf Coasts remote sensing Geography text 2019 ftunivsouthcar https://doi.org/10.5194/nhess-19-2141-2019;10.5194/nhess-19-2141-2019 2024-04-30T23:59:54Z Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal areas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely benefits sustainable development. This study uses the nighttime light (NTL) data from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) to examine human settlement development in areas with different levels of hurricane proneness from 1992 to 2013. The DMSP/OLS NTL data from six satellites were intercalibrated and desaturated with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) optical imagery to derive the Vegetation Adjusted NTL Urban Index (VANUI), a popular index that quantifies human settlement intensity. The derived VANUI time series was examined with the Mann–Kendall test and Theil–Sen test to identify significant spatiotemporal trends. To link the VANUI product to hurricane impacts, four hurricane-prone zones were extracted to represent different levels of hurricane proneness. Aside from geographic division, a wind-speed-weighted track density function was developed and applied to historical storm tracks which originated in the North Atlantic Basin to better categorize the four levels of hurricane proneness. Spatiotemporal patterns of human settlement in the four zones were finally analyzed. The results clearly exhibit a north–south and inland–coastal discrepancy of human settlement dynamics. This study also reveals that both the zonal extent and zonal increase rate of human settlement positively correlate with hurricane proneness levels. The intensified human settlement in high hurricane-exposure zones deserves further attention for coastal resilience. Text North Atlantic University of South Carolina Libraries: Scholar Commons
institution Open Polar
collection University of South Carolina Libraries: Scholar Commons
op_collection_id ftunivsouthcar
language English
topic Hurricane
Hurricane-Prone
United State
Atlantic
Gulf Coasts
remote sensing
Geography
spellingShingle Hurricane
Hurricane-Prone
United State
Atlantic
Gulf Coasts
remote sensing
Geography
Huang, Xiao
Wang, Cuizhen
Lu, Junyu
Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
topic_facet Hurricane
Hurricane-Prone
United State
Atlantic
Gulf Coasts
remote sensing
Geography
description Hurricanes, as one of the most devastating natural hazards, have posed a great threat to people in coastal areas. A better understanding of the spatiotemporal dynamics of human settlement in hurricane-prone areas largely benefits sustainable development. This study uses the nighttime light (NTL) data from the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) to examine human settlement development in areas with different levels of hurricane proneness from 1992 to 2013. The DMSP/OLS NTL data from six satellites were intercalibrated and desaturated with the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) optical imagery to derive the Vegetation Adjusted NTL Urban Index (VANUI), a popular index that quantifies human settlement intensity. The derived VANUI time series was examined with the Mann–Kendall test and Theil–Sen test to identify significant spatiotemporal trends. To link the VANUI product to hurricane impacts, four hurricane-prone zones were extracted to represent different levels of hurricane proneness. Aside from geographic division, a wind-speed-weighted track density function was developed and applied to historical storm tracks which originated in the North Atlantic Basin to better categorize the four levels of hurricane proneness. Spatiotemporal patterns of human settlement in the four zones were finally analyzed. The results clearly exhibit a north–south and inland–coastal discrepancy of human settlement dynamics. This study also reveals that both the zonal extent and zonal increase rate of human settlement positively correlate with hurricane proneness levels. The intensified human settlement in high hurricane-exposure zones deserves further attention for coastal resilience.
format Text
author Huang, Xiao
Wang, Cuizhen
Lu, Junyu
author_facet Huang, Xiao
Wang, Cuizhen
Lu, Junyu
author_sort Huang, Xiao
title Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
title_short Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
title_full Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
title_fullStr Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
title_full_unstemmed Understanding the Spatiotemporal Development of Human Settlement in Hurricane-Prone Areas on the US Atlantic and Gulf Coasts Using Nighttime Remote Sensing
title_sort understanding the spatiotemporal development of human settlement in hurricane-prone areas on the us atlantic and gulf coasts using nighttime remote sensing
publisher Scholar Commons
publishDate 2019
url https://scholarcommons.sc.edu/geog_facpub/220
https://doi.org/10.5194/nhess-19-2141-2019;
https://scholarcommons.sc.edu/context/geog_facpub/article/1222/viewcontent/nhess_19_2141_2019__1_.pdf
genre North Atlantic
genre_facet North Atlantic
op_source Faculty Publications
op_relation https://scholarcommons.sc.edu/geog_facpub/220
doi: https://doi.org/10.5194/nhess-19-2141-2019
https://scholarcommons.sc.edu/context/geog_facpub/article/1222/viewcontent/nhess_19_2141_2019__1_.pdf
op_rights © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
op_doi https://doi.org/10.5194/nhess-19-2141-2019;10.5194/nhess-19-2141-2019
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