| Technology and Methodology |
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Method for detecting cloud at night from VIIRS data based on DNB |
| XIA Lang1, MAO Kebiao1, SUN Zhiwen2, MA Ying3, ZHAO Fen1 |
1. National Hulun Buir Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
2. Space Star Technology Co., Ltd., Beijing 100086, China;
3. A-World Consulting, Hong Kong Logistics Association, Hong Kong 999077, China |
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Abstract Validating the cloud detection result at night and distinguishing low cloud from fog through satellite data are difficult in southern mountain areas of China. In this paper, a method is presented by analyzing the new features of the visible infrared imaging radiometer suite (VIIRS) sensor data and the theory of the cloud detection. The viability of VIIRS day and night (DNB) data in night cloud detection is discussed in detail and the result shows that the DNB data can be used to validate the result when lunar zenith angle is less than 60°. The application and validation show that the method is effective, and the estimation accuracy is higher than 91% when scan angle is less than 15°, and the BTM12-BTM13 and BTM12-BTM15 can be used to effectively distinguish low clouds and fog. In addition, the detection thresholds are sensitive to the sensor zenith angle, and the detection accuracy is higher when the sensor zenith angle is small.
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| Keywords
Middle-Lower Yangtze Plain
cropland
remote sensing
spatial-temporal change characteristics
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Issue Date: 01 July 2014
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2014,
Vol. 26
