Assessment of Population Exposure to Urban Flood at the Building Scale

The assessment of populations affected by urban flooding is crucial for flood prevention and mitigation but is highly influenced by the accuracy of population datasets. The population distribution is related to buildings during the urban floods, so assessing the population at the building scale is m...

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Main Authors: Shaonan Zhu, Qiang Dai, Binru Zhao, Jiaqi Shao
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/12/11/3253
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spelling doaj-277f432098a547ad9cd0e3e8337e5f632020-11-25T04:12:26ZengMDPI AGWater2073-44412020-11-01123253325310.3390/w12113253Assessment of Population Exposure to Urban Flood at the Building ScaleShaonan Zhu0Qiang Dai1Binru Zhao2Jiaqi Shao3School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, ChinaDepartment of Civil Engineering, University of Bristol, Bristol BS8 1TR, UKKey Laboratory of VGE of Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaKey Laboratory of VGE of Ministry of Education, Nanjing Normal University, Nanjing 210023, ChinaThe assessment of populations affected by urban flooding is crucial for flood prevention and mitigation but is highly influenced by the accuracy of population datasets. The population distribution is related to buildings during the urban floods, so assessing the population at the building scale is more rational for the urban floods, which is possible due to the abundance of multi-source data and advances in GIS technology. Therefore, this study assesses the populations affected by urban floods through population mapping at the building scale using highly correlated point of interest (POI) data. The population distribution is first mapped by downscaling the grid-based WorldPop population data to the building scale. Then, the population affected by urban floods is estimated by superimposing the population data sets onto flood areas, with flooding simulated by the LISFLOOD-FP hydrodynamic model. Finally, the proposed method is applied to Lishui City in southeast China. The results show that the population affected by urban floods is significantly reduced for different rainstorm scenarios when using the building-scale population instead of WorldPop. In certain areas, populations not captured by WorldPop can be identified using the building-scale population. This study provides a new method for estimating populations affected by urban flooding.https://www.mdpi.com/2073-4441/12/11/3253population exposurepopulation mappingPOIsurban floods
collection DOAJ
language English
format Article
sources DOAJ
author Shaonan Zhu
Qiang Dai
Binru Zhao
Jiaqi Shao
spellingShingle Shaonan Zhu
Qiang Dai
Binru Zhao
Jiaqi Shao
Assessment of Population Exposure to Urban Flood at the Building Scale
Water
population exposure
population mapping
POIs
urban floods
author_facet Shaonan Zhu
Qiang Dai
Binru Zhao
Jiaqi Shao
author_sort Shaonan Zhu
title Assessment of Population Exposure to Urban Flood at the Building Scale
title_short Assessment of Population Exposure to Urban Flood at the Building Scale
title_full Assessment of Population Exposure to Urban Flood at the Building Scale
title_fullStr Assessment of Population Exposure to Urban Flood at the Building Scale
title_full_unstemmed Assessment of Population Exposure to Urban Flood at the Building Scale
title_sort assessment of population exposure to urban flood at the building scale
publisher MDPI AG
series Water
issn 2073-4441
publishDate 2020-11-01
description The assessment of populations affected by urban flooding is crucial for flood prevention and mitigation but is highly influenced by the accuracy of population datasets. The population distribution is related to buildings during the urban floods, so assessing the population at the building scale is more rational for the urban floods, which is possible due to the abundance of multi-source data and advances in GIS technology. Therefore, this study assesses the populations affected by urban floods through population mapping at the building scale using highly correlated point of interest (POI) data. The population distribution is first mapped by downscaling the grid-based WorldPop population data to the building scale. Then, the population affected by urban floods is estimated by superimposing the population data sets onto flood areas, with flooding simulated by the LISFLOOD-FP hydrodynamic model. Finally, the proposed method is applied to Lishui City in southeast China. The results show that the population affected by urban floods is significantly reduced for different rainstorm scenarios when using the building-scale population instead of WorldPop. In certain areas, populations not captured by WorldPop can be identified using the building-scale population. This study provides a new method for estimating populations affected by urban flooding.
topic population exposure
population mapping
POIs
urban floods
url https://www.mdpi.com/2073-4441/12/11/3253
work_keys_str_mv AT shaonanzhu assessmentofpopulationexposuretourbanfloodatthebuildingscale
AT qiangdai assessmentofpopulationexposuretourbanfloodatthebuildingscale
AT binruzhao assessmentofpopulationexposuretourbanfloodatthebuildingscale
AT jiaqishao assessmentofpopulationexposuretourbanfloodatthebuildingscale
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