Historical average method used in MODIS image pixel cloud compensation: Exemplified by Gansu Province
CHEN Baolin1(), ZHANG Bincai2, WU Jing1(), LI Chunbin1, CHANG Xiuhong1
1. College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China 2. Gansu Geomatic Information Center, Lanzhou 730030, China
When a satellite is in transit, the presence of clouds or fog will cause shadows on some remote sensing images, and this accordingly directly affects the quality of image and the extraction, interpretation and recognition of the feature information. The authors firstly counted the data of 2017 MODIS11A1 in Gansu Province, and found that the data pixels values of 2017 MODIS11A1 are void to a large extent. Mainly because it is difficult for the remote sensing image to penetrate the cloud to obtain the feature information, the image pixel value is 0. Then the authors explored and compensated the missing value based on the phenological solar term as the time period, proposing the method of historical average value. After using the historical average method to compensate the data, the authors found that the effective utilization ratio of pixels could be greatly improved. The image information basically reflects the real feature information, and the compensation result can meet the demand of remote sensing images.
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2021, Vol. 33 
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