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23 November 2011 The research on day fog detection using FY2E data
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Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 80060V (2011) https://doi.org/10.1117/12.901898
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
The traditional fog detection methods based on remote sensing mainly used polar-orbiting satellite data (MODIS, AVHRR) to establish the fog detection model, but the transit time are always later and the time resolution are about one day, so they cannot be good to meet the requirements of fog detection. FY2E (a geostationary satellite) data will be chosen to build the day fog detection model for its high time resolution (one hour) and relatively rich spectrum. In this paper object-oriented thinking and texture differences between fog and cloud were introduced to the fog detection model. According to the simulation results of streamer radiative transfer model based on FY2E data, Snow Separation Index (SSI) will be built to extract snow from fog and Cloud Separation Index (CSI) will be built to extract low clouds from fog. A day fog detection model for FY2E data will be built based on object-oriented thinking and several characteristic parameters. The experiments shows that the fog detection model proposed in this paper achieved good results.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Li, Liangming Liu, and Juan Du "The research on day fog detection using FY2E data", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060V (23 November 2011); https://doi.org/10.1117/12.901898
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