Vegetation change by human activities and evaluation of its effect to climate change

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1) A system to process huge volume of GAC data efficiently and automatically, connecting many PC's via network, has been developed and GAC data processing has started. It became possible to process one year's data about within one month.2) Mosaic of LANDSAT images of Southeast Asia region was generated automatically and a technique for land cover classification more efficiently and accurately, combining LANDSAT images with NOAA images has been developed. Studies of land cover change detection from time series LANDSAT images are going on.3) A software was developed to build a distributed data base of ground photographs taken for ground validation of land cover classification and vegetation classification and a data base was constructed. This system makes it possible to integrate data bases generated by researchers independently and to archive ground photographic data easily.4) Combining vegetation indexes derived from time series satellite data with temperature and precipitation data, temporal and spatial correlation between seasonal vegetation variations and environmental conditions such as temperature and precipitation becomes clear. There is an interesting discovery that East Siberia, which is extremely cold area in Eurasia, is latest in that forest become green, but is latest in falling leaves.5) A frame work of estimation model for land use change based on agricultural productivity estimation of land was established and validation was made for Thailand. As the basis of productivity estimation a productivity estimation model for paddy rice, which is most important crop in Asia, was developed.6) To improve the reliability of vegetation index estimated from satellite images, techniques for atmospheric correction and geographical correction was developed and implemented. Vegetation data are generated periodically and composite images are generating.