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Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau
Authors:Lei Zhong  Yaoming Ma  Mhd Suhyb Salama  Zhongbo Su
Institution:1. Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, No. 18, Shuangqing Rd., P.O. Box 2871, Beijing, 100085, People’s Republic of China
2. International Institute for Geo-Information Science and Earth Observation, Enschede, 7500 AA, The Netherlands
3. Institute of Plateau Meteorology, China Meteorological Administration, Chengdu, 610071, China
4. School of Geography and Remote Sensing, Beijing Normal University, Beijing, 100875, China
Abstract:The Tibetan Plateau is a region sensitive to climate change, due to its high altitude and large terrain. This sensitivity can be measured through the response of vegetation patterns to climate variability in this region. Time series analysis of Normalized Difference Vegetation Index (NDVI) imagery and correlation analyses are effective tools to study land cover changes and their response to climatic variations. This is especially important for regions like the Tibetan Plateau, which has a complex ecosystem but lacks a lot of detailed in-situ observation data due to its remoteness, vastness and the severity of its climatic conditions. In this research a time series of 315 SPOT VEGETATION scenes, covering the period between 1998 and 2006, has been processed with the Harmonic ANalysis of Time Series (HANTS) algorithm in order to reveal the governing spatiotemporal pattern of variability. Results show that the spatial distribution of NDVI values is in agreement with the general climate pattern in the Tibetan Plateau. The seasonal variation is greatly influenced by the Asian monsoon. Interannual analysis shows that vegetation density (recorded here by the NDVI values) in the entire Tibetan Plateau has generally increased. Using a 1 km resolution land cover map from GLC2000, seven meteorological stations, presenting monthly data on near surface air temperature and precipitation, were selected for correlation analysis between NDVI and climate conditions in this research. A time lag response has also been found between NDVI and climate variables. Except in desert grassland (Shiquanhe station), the NDVI of all selected sites showed strong correlation with air temperature and precipitation, with variations in correlation according to the different land cover types at different locations. The strongest relationship was found in alpine and subalpine plain grass, the weakest in desert grassland.
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