Publications

Ma, HY; Li, YA; Wu, XJ; Feng, HH; Ran, YZ; Jiang, BB; Wang, W (2022). A large-region fog detection algorithm at dawn and dusk for high-frequency Himawari-8 satellite data. INTERNATIONAL JOURNAL OF REMOTE SENSING, 43(7), 2620-2637.

Abstract
Satellite remote sensing provides effective methods for fog detection at large scales. At dawn or dusk, however, the separation of fog from the surface remains a great challenge because of the minor radiation difference between fog and the surface. This study develops a novel algorithm for fog detection suitable for dawn and dusk from high-frequency data of the Himawari-8 satellite. Methodologically, the area was divided into three subregions according to the distance of the terminator line. In regions at daytime that are far from the terminator line, a fog detection index of the low solar altitude angle (FDI (LSAA)) was built to isolate the fog through the relationship between the mid-infrared (MIR) brightness temperature (I ( MIR )) and its difference with the thermal infrared (TIR) brightness temperature (BTD = I ( MIR ) - I ( TIR ), where I ( MIR ) and I ( TIR ) are the brightness temperatures at the MIR and TIR bands). In regions near the terminator line, the fog was extracted from the surface by a Gaussian mixture model (FD-GMM (NTL)) by the differences in MIR and TIR radiation changes. After that, the fog was further extracted from the low and mid-high clouds by the enhanced low cloud detection index (ELCDI) and by the difference in BTD and TIR characteristics. In regions at night, a BTD threshold value was adopted to detect fog. Validation results demonstrated that the algorithm in this study could precisely detect large-region radiation fog including dawn and dusk, with the overall probability of detection (POD) accuracies range from 76.3% to 89.2% at dawn and 67.3% to 77.0% at dusk. The relatively low accuracy at dusk was mainly attributed to desert in the study area, which has a similar BTD with fog after a day of solar radiation. Results of this study provide new insight for fog detection at dawn and dusk, which enhances the application of remote sensing in meteorology forecasting.

DOI:
10.1080/01431161.2022.2065895

ISSN:
1366-5901