A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island
Urban Flood (UF) and Urban Heat Island (UHI) become prevalent “urban diseases” currently. Previous studies usually regarded UF and UHI as separate issues that requires respective concentration; however, UF and UHI are inextricably connected so that they should be considered together. Hence, this pap...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224000402 |
| _version_ | 1797303417191792640 |
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| author | Xianzhe Tang Xi Huang Juwei Tian Yuhao Jiang Xue Ding Wei Liu |
| author_facet | Xianzhe Tang Xi Huang Juwei Tian Yuhao Jiang Xue Ding Wei Liu |
| author_sort | Xianzhe Tang |
| collection | DOAJ |
| description | Urban Flood (UF) and Urban Heat Island (UHI) become prevalent “urban diseases” currently. Previous studies usually regarded UF and UHI as separate issues that requires respective concentration; however, UF and UHI are inextricably connected so that they should be considered together. Hence, this paper proposes a spatiotemporal framework to link UF and UHI by developing an Urban Flood Heat Island (UFHI) index, taking the Greater Bay Area (GBA) in China as the study case. Random Forest (RF) classifier and Urban-Rural Dichotomy were selected to compute the spatiotemporal distribution of UF susceptibility (UFS) and UHI intensity (UHII), respectively. Theil-Sen Median Slope, Mann-Kendall Test, and Hurst analysis were used to explore the spatiotemporal variation pattern of the UF-UHI joint risk. Spatial Durbin Model was used to compute the correlation between UFS and UHII. RF regressor was employed to quantify the contribution of the common driving factors. We found: (1) UFS and UHII are spatiotemporally correlated, thus UHII can be used as a control variable for the refined UFS assessments, (2) the areas with the UF-UHI joint risk of persistently significant increase (∼7.9 %) majorly distributed in the central region, (3) according to the contributions of factors, UF and UHI in the GBA could be effectively alleviated by breaking the continuous impervious surfaces by introducing blue-green structures. This study offers a new perspective for the effective alleviation of UF and UHI, which would be helpful for the sustainable development of cities in developing countries where human and material sources are limited. |
| first_indexed | 2024-03-07T23:52:26Z |
| format | Article |
| id | doaj.art-d400eb85113a4491bf5557d9b5d9eaaf |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-07T23:52:26Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-d400eb85113a4491bf5557d9b5d9eaaf2024-02-19T04:13:16ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322024-03-01127103686A spatiotemporal framework for the joint risk assessments of urban flood and urban heat islandXianzhe Tang0Xi Huang1Juwei Tian2Yuhao Jiang3Xue Ding4Wei Liu5Guangdong Province Key Laboratory for Land Use and Consolidation, South China Agricultural University, Guangzhou 510642, China; College of Natural Resources and Environment, Joint Institute for Environment & Education, South China Agricultural University, Guangzhou 510642, ChinaGuangdong Province Key Laboratory for Land Use and Consolidation, South China Agricultural University, Guangzhou 510642, ChinaGuangdong Province Key Laboratory for Land Use and Consolidation, South China Agricultural University, Guangzhou 510642, ChinaAcademy of Forest Inventory and Planning, National Forestry and Grassland Administration, Beijing 100013, ChinaCollege of Land Management, Nanjing Agricultural University, Nanjing 210095, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Corresponding author at: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.Urban Flood (UF) and Urban Heat Island (UHI) become prevalent “urban diseases” currently. Previous studies usually regarded UF and UHI as separate issues that requires respective concentration; however, UF and UHI are inextricably connected so that they should be considered together. Hence, this paper proposes a spatiotemporal framework to link UF and UHI by developing an Urban Flood Heat Island (UFHI) index, taking the Greater Bay Area (GBA) in China as the study case. Random Forest (RF) classifier and Urban-Rural Dichotomy were selected to compute the spatiotemporal distribution of UF susceptibility (UFS) and UHI intensity (UHII), respectively. Theil-Sen Median Slope, Mann-Kendall Test, and Hurst analysis were used to explore the spatiotemporal variation pattern of the UF-UHI joint risk. Spatial Durbin Model was used to compute the correlation between UFS and UHII. RF regressor was employed to quantify the contribution of the common driving factors. We found: (1) UFS and UHII are spatiotemporally correlated, thus UHII can be used as a control variable for the refined UFS assessments, (2) the areas with the UF-UHI joint risk of persistently significant increase (∼7.9 %) majorly distributed in the central region, (3) according to the contributions of factors, UF and UHI in the GBA could be effectively alleviated by breaking the continuous impervious surfaces by introducing blue-green structures. This study offers a new perspective for the effective alleviation of UF and UHI, which would be helpful for the sustainable development of cities in developing countries where human and material sources are limited.http://www.sciencedirect.com/science/article/pii/S1569843224000402Urban Flood Heat Island indexUrban Flood SusceptibilityUrban Heat Island IntensityRandom ForestSpatiotemporal analysis |
| spellingShingle | Xianzhe Tang Xi Huang Juwei Tian Yuhao Jiang Xue Ding Wei Liu A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island International Journal of Applied Earth Observations and Geoinformation Urban Flood Heat Island index Urban Flood Susceptibility Urban Heat Island Intensity Random Forest Spatiotemporal analysis |
| title | A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| title_full | A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| title_fullStr | A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| title_full_unstemmed | A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| title_short | A spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| title_sort | spatiotemporal framework for the joint risk assessments of urban flood and urban heat island |
| topic | Urban Flood Heat Island index Urban Flood Susceptibility Urban Heat Island Intensity Random Forest Spatiotemporal analysis |
| url | http://www.sciencedirect.com/science/article/pii/S1569843224000402 |
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