4.0 Article

Spatial-Temporal NDVI Variation of Different Alpine Grassland Classes and Groups in Northern Tibet from 2000 to 2013

Journal

MOUNTAIN RESEARCH AND DEVELOPMENT
Volume 35, Issue 3, Pages 254-263

Publisher

MOUNTAIN RESEARCH & DEVELOPMENT
DOI: 10.1659/MRD-JOURNAL-D-14-00110.1

Keywords

Normalized Difference Vegetation Index (NDVI); alpine grassland; precipitation; temperature; northern Tibet

Funding

  1. National Natural Science Foundation of China [41371267]
  2. Action-plan of the Chinese Academy of Sciences (CAS) for West Development [KZCX2-XB3-08]
  3. 135 Strategic Programs of the Institute of Mountain Hazards and Environment [sds-135-1203-03]

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The Normalized Difference Vegetation Index (NDVI) can usually be used as a good proxy for evaluating potential variability in regional ecosystems and under climate change. We used 16-day MODIS-NDVI composite satellite data with 250-m resolution for the period 2000 to 2013 to assess the temporal and spatial variation of the NDVI among different alpine grassland classes and groups in northern Tibet. The annual average NDVI of the whole alpine grassland area in northern Tibet generally increased slightly from 2000 to 2003, and the annual average NDVI values ranged from 0.112 to 0.492 across all alpine grassland groups and years. The NDVI clearly decreased from the southeastern to the northwestern areas, with 22.50% of total grasslands significantly having increased or decreased, while 77.50% presented little change during 2000-2013. Both temperature and precipitation were key factors that controlled the NDVI variations of the entire alpine grassland. However, for different alpine grassland classes and groups, the NDVI displayed different correlation patterns with temperature and precipitation. Our results demonstrate that the NDVI variations of alpine grassland generally increased slightly but differed among different classes and groups. Although temperature and precipitation were the driving forces influencing the NDVI of the entire alpine grassland, it was more difficult to define the driving forces for the individual classes and groups, and more detailed analyses covering prolonged observation periods are still needed.

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