Article: A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990-2018

The Tibetan Plateau is a unique, biodiverse ecosystem with an important role in the climate and hydrological system of Asia. Its vegetation supports important functions including fodder provision, erosion prevention and water retention. Assessing vegetation trends of the Tibetan Plateau is crucial to understand effects of recent climate and land-use changes. Most existing vegetation trend products covering the entire Tibetan Plateau have a coarse spatial grain and cover short temporal ranges. This hampers their applicability in studies conducted at local scales where land-use decisions take place and at time scales where climate changes become apparent. Here, we present vegetation trend products for the entire Tibetan Plateau at a spatial resolution of 30 m for the time period 1990-2018. These products include results of a modified Mann-Kendall trend test applied to annual Landsat-based NDVI mosaics, composed from all satellite observations acquired during the vegetation periods as well as NDVI difference images. These data can be valuable to many researchers including for example wildlife ecologists, rangeland experts and climate change researchers.

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References

1.

Tian L, Chen J, Zhang Y . Growing season carries stronger contributions to albedo dynamics on the Tibetan plateau. PLoS One. 2017; 12(9):e0180559. PMC: 5590739. DOI: 10.1371/journal.pone.0180559. View

2.

Vermote E, Justice C, Claverie M, Franch B . Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sens Environ. 2020; Volume 185(Iss 2):46-56. PMC: 6999666. DOI: 10.1016/j.rse.2016.04.008. View

3.

Roy D, Kovalskyy V, Zhang H, Vermote E, Yan L, Kumar S . Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens Environ. 2020; Volume 185(Iss 1):57-70. PMC: 6999663. DOI: 10.1016/j.rse.2015.12.024. View

4.

Fassnacht F, Schiller C, Kattenborn T, Zhao X, Qu J . A Landsat-based vegetation trend product of the Tibetan Plateau for the time-period 1990-2018. Sci Data. 2019; 6(1):78. PMC: 6544617. DOI: 10.1038/s41597-019-0075-9. View

5.

Li J, Liu D, Wang T, Li Y, Wang S, Yang Y . Grassland restoration reduces water yield in the headstream region of Yangtze River. Sci Rep. 2017; 7(1):2162. PMC: 5438355. DOI: 10.1038/s41598-017-02413-9. View

A Landsat-based Vegetation Trend Product of the Tibetan Plateau for the Time-period 1990-2018