Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification
Abstract
:1. Introduction
2. Study Area and Data Sources
2.1. Study Area
2.2. Data Sources
2.3. Spatial Distribution of Urban Morphology Factors
3. Methodology
3.1. Spatially Weighted Naive Bayes Model
3.2. Local Climate Zones Classification
3.3. Environmental Equity Calculation
3.4. Waterlogging Risk Classification
4. Results and Discussion
4.1. LCZs Classification Results
4.2. Spatial Distribution of Waterlogging Point and Risk Levels
4.3. Urban Waterlogging Risk in Different LCZs
4.4. Waterlogging Exposure Distribution in Different Streets
4.5. Theil Index of Different Streets
4.6. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Nomenclature
LCZ | Local climate zones |
DEM | Digital Elevation Model |
DW | Distance to the waterway |
FVC | Fractional vegetation cover |
ISF | Impervious surface fraction |
PWE | Population-weighted exposure |
RD | Road density |
SWR | Soil water retention |
WNB | Weighted naive Bayes |
WUDAPT | World Urban Database and Access Portal Tools |
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Theme | Sources | Resolution | Application |
---|---|---|---|
Waterlogging | Guangzhou Water Authority (https://swj.gz.gov.cn/index.html) Toutiao (https://www.toutiao.com/) | point | Waterlogging risk mapping |
DEM | Resource and Environmental Science Data Platform (https://www.resdc.cn/) (accessed on 6 April 2024) | 30 m | DEM, SLOPE mapping |
Waterway | OpenStreetMap (https://www.openstreetmap.org/) (accessed on 6 April 2024) | Polygon | DW calculating |
Road | OpenStreetMap (https://www.openstreetmap.org/) | Polyline | RD calculating |
Soil type | Resource and Environmental Science Data Platform (https://www.resdc.cn/) | 30 m | SWR calculating |
Fractional vegetation cover | Landsat 8 Operational Land Imager_Thermal Infrared Sensor | 30 m | FVC mapping |
Impervious surface fraction | Zhang et al. [45] | 30 m | ISF mapping |
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Zou, B.; Nie, Y.; Liu, R.; Wang, M.; Li, J.; Fan, C.; Zhou, X. Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification. Water 2024, 16, 2464. https://doi.org/10.3390/w16172464
Zou B, Nie Y, Liu R, Wang M, Li J, Fan C, Zhou X. Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification. Water. 2024; 16(17):2464. https://doi.org/10.3390/w16172464
Chicago/Turabian StyleZou, Binwei, Yuanyue Nie, Rude Liu, Mo Wang, Jianjun Li, Chengliang Fan, and Xiaoqing Zhou. 2024. "Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification" Water 16, no. 17: 2464. https://doi.org/10.3390/w16172464
APA StyleZou, B., Nie, Y., Liu, R., Wang, M., Li, J., Fan, C., & Zhou, X. (2024). Assessing the Impact of Urban Morphologies on Waterlogging Risk Using a Spatial Weight Naive Bayes Model and Local Climate Zones Classification. Water, 16(17), 2464. https://doi.org/10.3390/w16172464