Impact of Land Use/Land Cover Changes on Urban Flooding: A Case Study of the Greater Bay Area, China

Urban flooding caused by heavy rainfall is a common natural hazard in cities globally. Impervious surfaces are often increased during urban development, but there is limited research on the impact of large-scale and long-term land use/land cover (LULC) changes on urban flooding, while considering the influence of using different remote sensing data sources. In this study, a framework to evaluate the correlation between LULC changes and flooding extents is proposed, mainly comprising: 1) classifying remote sensing time series, using different sources but adopting the same classifier, to obtain the LULC of the Greater Bay Area, China, over a one decade period; 2) designing flooding scenarios with different rainfall intensities, and using the soil conservation service curve number (SCS-CN) model and local equal volume method to extract the inundation extent of urban flooding; and 3) analyzing the influence of different data sources on flood simulation results, and calculating the correlations between LULC and inundation area over the decade to analyze the impact of LULC changes on urban flooding. The resulting correlation coefficients of water and built-up land are 0.93 and 0.42, and those of bare land, grassland, orchard, and forest are −0.40, −0.61, −0.57, and −0.75, respectively. The inundation derived by Sentinel and Landsat data showed around 99% consistency, while Landsat tends to derive more inundation areas, with the differences mainly scattered in flat areas.