Multi-temporal and multi-channel cloud detection algorithm based on GF-4 data

Aiming at the problem that the traditional cloud detection algorithm is difficult to distinguish between clouds and ice pixels due to the lack of bands of the Gaofen-4 (GF-1) satellite imagery, a multi-temporal and multi-channel cloud detection algorithm was proposed. The algorithm first carried out the radiation calibration and registration of the GF-1 satellite image, used the spectral difference between the cloud and the typical ground surface to obtain potential cloud pixels, and then used the difference between the sequence GF-4 satellite image to identify cloud pixels. Finally, the mid-infrared band was used to retrieve the brightness temperature of the surface to remove the ice and snow pixels. The algorithm was verified in three research areas of Hainan, Liaoning and Anhui, and the detection results were compared with the detection results of traditional single-phase cloud detection algorithm, SVM cloud detection algorithm, and RTD cloud detection algorithm. The results show that the algorithm is better than the others. The proposed algorithm has an accurate recognition rate of more than 90%, and the false detection rate is less than 5%, which is conducive to further use of GF-4 satellite imagery.