Using MOD13Q1, GIMMS NDVI 3g vegetation index dataset, combined with digital elevation model and other data sources, a 250 m spatial resolution NDVI data product was generated based on the stochastic forest downscaling model for the Tibetan Plateau from 1982 to 2020, and passed the validation evaluation. The data can provide basic data support for grassland ecosystem research on the Tibetan Plateau.
The GIMMS NDVI 3g product is provided by the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the United States National and Atmospheric Administration (NOAA) polar orbiting meteorological satellite (https://ecocast.arc.nasa.gov/data/pub/gimms). Introduced between 1982-2015, this product has a temporal resolution of 15 d and a spatial resolution of 8 km, eliminating the effects of volcanic eruptions, solar altitude angle, and sensor sensitivity variations over time, and is widely used globally.The MODIS NDVI data are derived from the MODIS Vegetation Index (MVI) product, which has been developed by the MODIS Terrestrial Products Group of NASA based on the Harmonised Algorithm (HAP). Download the MOD13Q1 NDVI dataset with 16 d temporal resolution and 250 m spatial resolution used in this paper from the MODIS Web site (https://modis.gsfc.nasa.gov/). The product has a time frame of 28 February 2000 to 31 December 2020.The DEM data were provided by the Shuttle Radar Topography Mapping Mission (SRTM) operated by the National Geospatial-Intelligence Agency (NGA) and the National Aeronautics and Space Administration (NASA). The DEM data used have a spatial resolution of 90 m and are available at http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp访问获取.
(1) Using the MRT tool, data splicing and projection transformation of MODIS 13Q1, with the projection coordinate system of WGS84; (2) using the maximum value compositing (MVC) method to integrate the MODIS and GIMMS NDVI results into a monthly time series of each pixel; (3) using the nearest neighbour method to resample the GIMMS data and the DEM data up to 250 m, so as to match the MODIS NDVI resolution; (4) selecting the intersection time period (2001-2015) of the two datasets, GIMMS and MODIS, for model construction and evaluation, in which the month-by-month downscaling model is constructed with data from odd-numbered years, and the accuracy of the downscaling products is evaluated with data from even-numbered years.
good quality
| # | number | name | type |
| 1 | 41971293 | Snow accumulation processes in the permafrost region of the Tibetan Plateau and snow parameters inversion using multi-source remote sensing. | National Natural Science Foundation of China |
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
CSTR:11738.11.NCDC.LZU.DB6634.2024
10.12072/ncdc.lzu.db6634.2024