Abstract
This paper is concerned with evaluating the compositing algorithms for mosaic NOAA/AVHRR images 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 10-day mosaic images of four seasons by using the data received at Bangkok and Ulaanbaartar. Evaluation was undertaken from the view points of cloud removal, percentage of near-nadir observation data, image smoothness and providing the appropriate data for vegetation growing change. Each algorithm was accompanied with various advantages and disadvantages, but MaTNiS was nominated to be superior as overall.
