2013 年 33 巻 1 号 p. 48-55
Vegetation, which extensively covers the global land area, is closely related to the climate system. According to the predictions of some earth system models, the boreal forest will redistribute northward as a result of climate change that will occur within the next three hundred years. This paper reviews recent remote sensing studies that have investigated the spatio-temporal variability of vegetation in boreal regions with specific reference to the impact of the climate. Based on the time series of the normalized difference vegetation index (NDVI) derived from satellite observations, the decadal change in vegetation can be examined. Increasing trends in the vegetation index and advancing trends in the green-up date have been found in Siberia and in the tundra region in Alaska from the 1980s to the 1990s, although some uncertainties remain. These trends are presumably due to warming in high-latitude regions. The development of an estimation algorithm of vegetation that defines biophysical parameters such as the leaf area index (LAI) and above-ground biomass (AGB) is another important task of remote sensing that can contribute to climate system modeling. The snow cover concealing the forest floor allows us to extract forest overstory greenness data from total greenness data by satellite observation and consequently, the LAI arising only from the forest overstory can be estimated. Additionally, we suggest that the relative sparseness of the boreal forest may be suitable for AGB estimation by microwave radar remote sensing.