Large-Scale Impervious Surface Area Mapping and Pattern Evolution of the Yellow River Delta Using Sentinel-1/2 on the GEE

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-01, Vol.15 (1), p.136
• Main Authors: Liu, Jiantao, Li, Yexiang, Zhang, Yan, Liu, Xiaoqian
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Anthropogenic factors; Cloud computing; Data processing; Deltas; Ecology; Estuaries; Evolution; Feature extraction; GEE; Geographical distribution; Geographical locations; Human influences; impervious surface area; Landsat satellites; Machine learning; Mapping; Natural resources; Parameter sensitivity; random forest; Remote sensing; Rivers; Sentinel-1/2; Spatial analysis; Surface area; Sustainable development; Urbanization; Workflow; Yellow River Delta
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15010136

The ecological environment of Yellow River Delta High-efficiency Ecological Economic Zone (YRDHEEZ) is adjacent to the Bohai Sea. The unique geographical location makes it highly sensitive to anthropogenic disturbances. As an important land surface biophysical parameter, the impervious surface area (ISA) can characterize the level of urbanization and measure the intensity of human activities, and hence, the timely understanding of ISA dynamic changes is of great significance to protect the ecological safety of the YRDHEEZ. Based on the multi-source and multi-modal Sentinel-1/2 remotely sensed data provided by Google Earth Engine (GEE) cloud computing platform, this study developed a novel approach for the extraction of time-series ISA in the YRDHEEZ through a combination of random forest algorithm and numerous representative features extracted from Sentinel-1/2. Subsequently, we revealed the pattern of the ISA spatial-temporal evolution in this region over the past five years. The results demonstrated that the proposed method has good performance with an average overall accuracy of 94.84% and an average kappa coefficient of 0.9393, which verified the feasibility of the proposed method for large-scale ISA mapping with 10 m. Spatial-temporal evolution analysis revealed that the ISA of the YRDHEEZ decreased from 5211.39 km2 in 2018 to 5147.02 km2 in 2022 with an average rate of −16.09 km2/year in the last 5 years, suggesting that the ISA of YRDHEEZ has decreased while its overall pattern was not significantly changed over time. The presented workflow can provide a reference for large-scale ISA mapping and its evolution analysis, especially in regions on estuarine deltas.