ABSTRACT
Vegetation phenology is a comprehensive indictor for the responses of terrestrial ecosystem to climatic and environmental changes. Remote sensing spectrum has been widely used in the extraction of vegetation phenology information. However, there are many differences between phenology extracted by remote sensing and site observations, with their physical meaning remaining unclear. We selected one tile of MODIS data in northeastern China (2000-2014) to examine the SOS and EOS differences derived from the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (SR) based on both the red and near-infrared bands. The results showed that there were significant differences between NDVI-phenology and SR-phenology. SOS derived from NDVI averaged 18.9 days earlier than that from SR. EOS derived from NDVI averaged 19.0 days later than from SR. NDVI-phenology had a longer growing season. There were significant differences in the inter-annual variation of phenology from NDVI and SR. More than 20% of the pixel SOS and EOS derived from NDVI and SR showed the opposite temporal trend. These results caused by the seasonal curve characteristics and noise resistance differences of NDVI and SR. The observed data source of NDVI and SR were completely consistent, only the mathematical expressions were different, but phenology results were significantly different. Our results indicated that vegetation phenology monitoring by remote sensing is highly dependent on the mathematical expression of vegetation index. How to establish a reliable method for extracting vegetation phenology by remote sensing needs further research.
Subject(s)
Ecosystem , Remote Sensing Technology , China , Environmental Monitoring , SeasonsABSTRACT
Inter-annual dynamics of grassland yield of the Three Rivers Headwaters Region of Qinghai-Tibet Plateau of China in 1988-2005 was analyzed using the GLO-PEM model, and the herbage supply function was evaluated. The results indicate that while grassland yield in the region showed marked inter-annual fluctuation there was a trend of increased yield over the 18 years of the study. This increase was especially marked for Alpine Desert and Alpine Steppe and in the west of the region. The inter-annual coefficient of variation of productivity increased from the east to the west of the region and from Marsh, Alpine Meadow, Alpine Steppe, Temperate Steppe to Alpine Desert grasslands. Climate change, particularly increased temperatures in the region during the study period, is suggested to be the main cause of increased grassland yield. However, reduced grazing pressure and changes to the seasonal pattern of grazing could also have influenced the grassland yield trend. These findings indicate the importance of understanding the function of the grassland ecosystems in the region and the effect of climate change on them especially in regard to their use to supply forage for animal production. Reduction of grazing pressure, especially during winter, is indicated to be critical for the restoration and sustainable use of grassland ecosystems in the region.
