Application and analysis of the algorithm called CLAVR were made for the remote sensing of cloud cover using multispectral radiance measurements from the Advanced Very High Resolution Radiometer （AVHRR） on board National Oceanic and Atmospheric Administration （NOAA） polar-orbiting satellites. The algorithm classifies 2×2 pixel arrays from the HRPT 1.1-km-resolution data into CLEAR

MIXED

and CLOUDY categories. It uses a sequence of multispectral contrast

spectral

and spatial signature threshold tests to perform the classification. The algorithms on China land area were applied to realtime NOAA-14 data and about 10 years dataset of China land area have been processed. It did well in classifying perfectly clear and cloudy pixel arrays except existing some errors for mixed pixel arrays. Different images in China land area show some difference

and the complicacy of landform and underlying surface influences cloud’s appearance or structure

thereby resulting contrast for different steps of the algorithm. The thresholds of main steps （RRCT

TUT and RUT） have been modified in the algorithm that required in the application of decision tree tests. It retrieves some CLOUDY and CLEAR pixels from the original classified MIXED pixels

separately the 4.31% and 1.09%. The CLAVR has been integrated into the Crop Growing Monitoring system of China.