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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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 |
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1724415463677493248 |