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NSFC 2017-XiaoyunWang-Impacts of standing litter on vegetation indexes and green-up date(41601064)

National Science Foundation of China41601064Impacts of standing litter on the remote sensing estimation of the vegetation indexes and green-up date of alpine grasslands on the Qinghai-Tibet Plateau2017-01 to 2019-12250,000 PI

 

Abstract

The Qinghai-Tibetan Plateau is a sensitive and ecologically fragile zone of climate change and it response very quickly to both climate change and human activities. In the past decades, the Qinghai-Tibetan Plateau has experienced significant climate warming, and this warming trend will continue. How does the green-up date of alpine grasslands on the Qinghai-Tibetan Plateau respond to climate warming has drew a lot of attention, without unified conclusion. It is worthy to note that during the period of regreening, standing litter is widespread on the Qinghai-Tibetan Plateau. Meanwhile, along with climate warming, the vegetation activity on the Qinghai-Tibetan Plateau has increased universally, as a result, the content of standing litter increased during the non-growing season and the regreening period. Besides, the change of meteorological factors and grazing policies on the Qinghai-Tibetan Plateau are both beneficial to the accumulation of standing litter. The spatial and temporal variations of standing litter is bound to have a significant impact on the procedures of vegetation index calculation and green-up date estimation, which are both based on remote sensing data, namely NDVI. Therefore, the quantitative evaluations of the spatial and temporal variations of standing litter and its influences on the remote sensing estimation results of NDVI and green-up date of alpine grasslands, on one hand, is very important to improve the estimate precision of the remote sensing vegetation index products and reduce the uncertainties of remote sensing estimation results of green-up date of alpine grasslands; on the other hand, can also provide a basis data for ecological simulation in this region.


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