High-Resolution Fog Dection over a Mountainous Lake Basin.

Dense fog occurs frequently on the surface of the complex mountainous areas in southern China, seriously affecting human life, industrial production, and transportation. To mitigate the risks brought by dense fog weather events, we take the Poyang Lake Basin as an example and propose a new fog detection method with high spatiotemporal resolution. The method includes the following steps: Firstly, use the D8 algorithm embedded in ArcGIS 10.2 to calculate the boundaries of the third-level sub-basins of Poyang Lake and divide them into multiple groups according to the boundaries. Then, utilize the FY4A meteorological satellite data and Digital Elevation Models, set remote sensing thresholds group by group based on the cumulative distribution statistical law of the Gaussian function. Finally, piece together the fog identification results of each group to obtain the final product. The study evaluated the effectiveness of the method for 48 heavy fog cases in the Poyang Lake Basin from 2021 to 2023, using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI). The results show that this method has an excellent ability to identify fog and can distinguish fog from other surface features, such as land surfaces, clouds, and low-level mist. The average POD, FAR, and CSI from 2021 to 2023 are 0.719, 0.109, and 0.660, respectively. The performance of this method shows obvious monthly variations, and the scores generally present a unimodal feature from September to June of the following year. The optimal detection periods for spring, autumn, and winter are 6:00–9:00, 7:00–10:00, and 8:00–10:30, respectively. Among the fog-concentrated seasons (spring, autumn, winter), detection performance is best in autumn, followed by winter, and poorest in spring. In addition, this method enables the observation of dynamic changes, boundary textures, and other detailed variations in fog areas.