The ASTER Global Digital Elevation Model (ASTER GDEM) is a global digital elevation data product jointly released by the National Aeronautics and Space Administration of America (NASA) and the Ministry of Economy, Trade and Industry of Japan (METI). The DEM data were based on the observation results of NASA’s new generation of Earth observation satellite, TERRA, and generated from 1.3 million stereo image pairs collected by ASTER (Advanced Space borne Thermal Emission and Reflection Radio meter) sensors, covering more than 99% of the land surface of the Earth. These data were downloaded from the ASTER GDEM data distribution website. For the convenience of using the data, based on framing the ASTER GDEM data, we used Erdas software to splice and prepare the ASTER GDEM mosaic of the Tibetan Plateau. This data set contains three data files: ASTER_GDEM_TILES ASTERGDEM_MOSAIC_DEM ASTERGDEM_MOSAIC_NUM The ASTER GDEM data of the Tibetan Plateau have an accuracy of 30 meters, the raw data are in tif format, and the mosaic data are stored in the img format. The raw data of this data set were downloaded from the ASTERGDEM website and completely retained the original appearance of the data. ASTER GDEM was divided into several 1×1 degree data blocks during distribution. The distribution format was the zip compression format, and each compressed package included two files. The file naming format is as follows: ASTGTM_NxxEyyy_dem.tif ASTGTM_NxxEyyy_num.tif xx is the starting latitude, and yyy is the starting longitude. _dem.tif is the dem data file, and _num.tif is the data quality file. ASTER GDEM TILES: The original, unprocessed raw data are retained. ASTERGDEM_MOSAIC_DEM: Inlay the dem.tif data using Erdas software, and parameter settings use default values. ASRERGDEM_MOSAIC_NUM: Inlay the num.tif data using Erdas software, and parameter settings use default values. The original raw data are retained, and the accuracy is consistent with that of the ASTERGDEM data distribution website. The horizontal accuracy of the data is 30 meters, and the elevation accuracy is 20 meters. The mosaic data are made by Erdas, and the parameter settings use the default values.
METI, National Aeronautics and Space Administration
This is the vegetation index (NDVI) for Maduo County in July, August and September of 2016. It is obtained through calculation based on the multispectral data of GF-1. The spatial resolution is 16 m. The GF-1 data are processed by mosaicking, projection coordinating, data subsetting and other methods. The maximum synthesis is then conducted every month in July, August, and September.
LI Fei, Fei Li, Zhijun Zhang
The data set includes the estimated data on the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on GIMMS3g version 1.0, the latest version of the GIMMS NDVI data set. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage ranges from 1982 to 2015, and the spatial resolution is 8 km.
WANG Xufeng
The data set includes estimated data on the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on the MODIS 16-day synthetic NDVI product (MOD13A2 collection 6). Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage ranges from 2001 to 2014, and the spatial resolution is 1 km.
WANG Xufeng
The data set includes the estimated data of the SOS (start of season) and the EOS (end of season) of vegetation in Sanjiangyuan based on 10-day synthetic NDVI products from the SPOT satellite. Two common phenological estimation methods were adopted: the threshold extraction method based on polynomial fitting (the term “poly” was included in the file names) and the inflection point extraction method based on double logistic function fitting (the term “sig” was included in the file names). These data can be used to analyse the relationship between vegetation phenology and climate change. The temporal coverage is from 1999 to 2013, and the spatial resolution is 1 km.
WANG Xufeng
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
