Normalized Difference Water Index (NDWI), Green-Red Vegetation Index (GRVI), and other indices of remotely detected spectrum combinations have been proposed in order to evaluate the vegetation changes and distributions. The training area of artificial Japanese larch forest and deciduous broad leaved forest (Japanese white birch and Japanese oak) in Hokkaido were extracted from MODIS data based on RapidEye data and GIS data of Vegetation Survey on 6/7^th National Basic Survey on Natural Environment (Biodiversity Center of Japan, Ministry of the Environment (http://www.biodic.go.jp/index_e.html)), the mean elevation, and the monthly mean temperature. The NDWI and GRVI were obtained for each training area from MODIS data. As a result, i) the MODIS GRVI of artificial Japanese larch forest were around -0.1, while the MODIS NDWI were greater than 0.5, ii) the MODIS GRVI of deciduous broad leaved forest were around 0.0, while the MODIS NDWI were less than 0.5, iii) these MODIS GRVI of Japanese larch and deciduous broad leaved forest were similar to GRVI of yellow and red leaves of larch and leafless birch calculated from the camera image of the canopy.

We propose a method for interpolating a DEM (Digital Elevation Model). Our method is executed by smoothing the DEM and restoring it to the original DEM by using an invers filter. At this time, by automatically finding the optimum value in the parameter of the inverse filter, it is possible to interpolate the DEM with high accuracy. Through the experiments using the DEM of 5m mesh, we demonstrate the effectiveness of our method.

The “Global Change Observation Mission-Climate”(GCOM-C) is a project of Japan Aerospace Exploration Agency (JAXA) for the global and long-term observation of the Earth environment. The GCOM-C is expected to play an important role in monitoring and understanding global climate change. The GCOM-C is a part of the JAXA's GCOM mission which consists of two satellite series, GCOM-C and GCOM-W (Water). Whereas GCOM-W carries a multi-frequency, dual-polarized, passive microwave radiometer named Advanced Microwave Scanning Radiometer 2 (AMSR2) to observe water-related targets such as precipitation, sea surface temperature, soil moisture, and snow depth, GCOM-C carries a multi-spectral optical radiometer named Second Generation Global Imager (SGLI), which has special features of wide spectral coverage from 380nm to 12μm, a high spatial resolution of 250m, a swath width exceeding 1000km, two-direction simultaneous observation, and polarization observation. The GCOM-C mission aims to contribute to improving our knowledge and prediction of the global carbon cycle and radiation budget through high-accuracy observation of global vegetation, ocean color, temperature, cloud, aerosol, and snow and ice through the SGLI observations.