A method, device, medium and equipment for fast extraction of morning and evening land fog based on h8/ahi

Abstract

The invention discloses a method, device, medium and equipment for quickly extracting morning and evening land fog based on H8 / AHI. The method firstly uses a low solar elevation angle surface removal index to remove the surface and near-morning line Gaussian in the low solar elevation angle area in an image The hybrid surface removal model removes the surface of the morning and evening line area, the traditional nighttime fog detection algorithm removes the surface of the nighttime area, and then combined with the low cloud detection index to remove the low clouds in the image, the traditional cloud removal method removes the medium and high clouds in the image, and the low sun height is removed. The surface removal results of the corner area and the surface removal results of the area near the twilight line are intersected with the low cloud removal results and the middle and high cloud removal results, respectively, to obtain the fog detection results in the low sun altitude area and the area near the dawn and dusk, and then combined with the surface removal results in the nighttime area. The results are merged to obtain the fog detection results at dawn and dusk in the remote sensing images, so as to realize the detection of land fog at dawn and dusk in a large range. The invention can accurately, efficiently and quickly realize the extraction of land fog at dawn and dusk.

Description

technical field [0001] The invention relates to the field of environmental monitoring and weather forecasting, in particular to a method, device, medium and equipment for quickly extracting morning and dusk land fog based on H8 / AHI. Background technique [0002] At dawn and dusk, the sun elevation angle is lower, the surface temperature is lower, and the relatively high water vapor content makes fog prone to occur at this time. The appearance of fog greatly reduces the visibility on the ground and seriously affects people's travel and traffic safety. Therefore, the real-time dynamic monitoring and forecasting of fog at dawn and dusk is of great significance to people's daily travel. Traditional fog detection is mainly based on the measured data of meteorological observation sites, which has low temporal and spatial resolution, and it is difficult to capture the distribution and dynamic characteristics of fog. With the rapid development of remote sensing satellite technology...

AI Technical Summary

Problems solved by technology

In addition, affected by factors such as time resolution of remote sensing data, funds, equipment, etc., looking at the research status of fog detection at home and abroad, it is still difficult to extract near-real-time, accurate and fast fog at dawn and dusk.

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