An algorithm of extracting optimal pixels for AVHRR 10-day composite image data set of Asian region

This paper is concerned with evaluating the compositing algorithms for NOAA/AVHRR composite image data set of Asian region. Five algorithms, such as (1) maximum NDVI method (MaN) by Holben, (2) maximum brightness temperature method (MaT) by Chilar et al., (3) maximum NDVI followed by minimum scan angle method(MaNiS) by Chilar et al., (4) multiple-object composite method (MOC) by Stoms et al., and (5) maximum brightness temperature followed by maximum NDVI and minimum scan angle method(MaTNiS) by the authors, were applied to compose the 10-day images by using the data of four seasons received at Bangkok (Thailand) and Ulaanbaatar (Mongolia). Evaluation was undertaken from the view points, i.e., cloud removal, percentage of near-nadir viewing data, smoothness of image and providing the appropriate temporal observation of vegetation. Each algorithm was accompanied with various advantages and disadvantages, but MaTNiS was nominated to be superior as overall