%0 Dataset
%T A long time-series 250m resolution monthly NDVI dataset for the Tibetan Plateau based on temporal and spatial data fusion (1981-2020)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/1f87b070-e38d-4c86-84f9-20292e8498d7
%W NCDC
%R 10.57760/sciencedb.j00001.00856
%A liu feng gui
%K NDVI;Qinghai Tibet Plateau;high temporal and spatial resolution
%X This data is based on the GIMMS NDVI3g and MOD13Q1 NDVI datasets. The monthly maximum value is synthesized by calling the Arcpy service in Python language. Then, the Savitsky Golay filter denoising, regression analysis, and 250 meter resolution NDVI data processing are performed on the annual monthly NDVI data using the GDAL and sklearn software packages in Python language. Using Savitzky Golay filter and sklearn software package to remove noise from monthly NDVI data, regressing the overlapping years of the two sets of data, analyzing the data, and expanding the NDVI dataset with a resolution of 250 meters, finally integrating the monthly NDVI time series dataset with a resolution of 250 meters on the Qinghai Tibet Plateau from 1981 to 2020. This dataset can reflect the spatiotemporal changes of NDVI on the Qinghai Tibet Plateau from 1981 to 2020, and can be used to improve the spatiotemporal resolution of long-term series data, providing data support for the study of vegetation dynamics and spatial patterns, as well as ecological environment monitoring on the Qinghai Tibet Plateau.