This data set is a three-level classification map of Eurasian grassland remote sensing in 2009. The data is in TIF grid format, with a spatial resolution of 1km. The three-level grassland is classified as: temperate meadow grassland, temperate typical grassland, temperate desertification grassland, temperate grassland desertification, and temperate desert. The data is processed according to the ESA global cover 2009 Product global cover map, combined with the historical meteorological data (precipitation, annual accumulated temperature, humidity coefficient, evaporation) and DEM data of ECMWF website. The data can be used to provide the basis for the distribution information and temporal and spatial variation analysis of warm grassland in Eurasia.
TANG Jiakui
This data set is a spatiotemporal variation map of temperate grassland types in Eurasia - three level classification of Inner Mongolia region of China (2009). The data is in TIF grid format with a spatial resolution of 1km. The data is processed on the basis of the existing grass type map of Inner Mongolia grassland. The grassland type map of Inner Mongolia grassland is based on the field survey data, neimengqi County as the unit, the grassland type classification system, on the basis of prediction, the field sample data, remote sensing image and other information data are superposed, and the local historical grassland survey data and relevant data are referred to, and the field plot is modified. We select 2000-2009 historical meteorological data, further analyze and modify the satellite data, and carry out spatial interpolation calculation. The classification of temperate grassland in Inner Mongolia was obtained. The data can be used to provide the basis for the distribution information and temporal and spatial variation analysis of warm grassland in Eurasia.
TANG Jiakui
This data set is the annual maximum value data (ndvi-am) of the normalized vegetation index of the Qinghai Tibet Plateau from 2000 to 2018. The data is in grid TIFF format, with a spatial resolution of 250m and a grid data value range of [- 1,1]. It can be used to study the change of vegetation coverage, grassland degradation and other ecological environment changes in the Qinghai Tibet Plateau, and can also provide data support for the study of urbanization and ecological environment interaction stress. The data is calculated based on the land level 2 standard data product of MODIS medium resolution sensor mod13 series (https://modis.gsfc.nasa.gov/data/dataprod/mod13.php). The level 2 Product data is a specific application data product generated after processing the original MODIS original data set. Ndvi-am data is processed by calculating the annual maximum value of NDVI of each pixel based on the normalized vegetation index data.
DU Yunyan, YI Jiawei
The “Eco-Hydro Integrated Atlas of Heihe River Basin” is supported by the Synthetic Research on the Eco-hydrological Process of the Heihe River Basin– a key project to provide data collation and service for the Heihe River Basin eco-hydrological process integration study. This atlas will provide researchers with a comprehensive and detailed introduction to the Heihe River Basin background and basic data sets. The 1:100,000 topographic framing index of the Heihe River Basin is one of the basic geographs of the atlas, with a scale of 1:2500000, Lambert conformal conic projection, and a standard latitude: north latitude 25 47 . Data source: 1:100000 topographic map index data, Heihe River boundary.
ZHAO Jun, WANG Jianhua
The “Eco-Hydrology Integrated Atlas of the Heihe River Basin ” was supported by the major program: Synthetic Research on the Eco-hydrological Process of the Heihe River Basin. It provided data collation and service for Synthetic Research on the Eco-hydrological Process of the Heihe River Basin. The Atlas will provide researchers with a comprehensive and detailed introduction of the background and basic data sets of the Heihe River Basin. Eco-Hydrology Integrated Atlas of the Heihe River Basin: Remote Sensing Mosaicing of the Heihe River Basin, scale 1:2500000, positive-axis equivalence conical projection, standard parallel: north latitude 25 47 Data source: Landsat TM Mosaic Image of the Heihe River Basin in 2010, Heihe River Basin Boundary,River Network Dataset of the Heihe River Basin, The Resident Site Distribution Data of the Heihe River Basin, etc.
WANG Jianhua, ZHAO Jun
This dataset includes the monthly air temperature at 2 m in the Qilian Mountain area on the Qinghai-Tibetan Plateau during 1980 to 2013. The dataset was obtained from the ERA-interim reanalysis product. The ERA-interim system includes a 4-dimensional variational analysis (4D-Var). The quality of the data has been improved using the bias correction of satellite data. The spatial resolution of the dataset is 0.125°. The dataset includes the grid data of the air temperature in the Qilian Mountain area during the past 30 years, and provides a basic data for the studies such as climatic change, ecosystem succession, and earth system models.
WU Xiaodong
This data set is the land use data of the key areas of Qilian mountain in 2018, spatial resolution 2m. This data set is based on the data of climate, altitude, topography, and land cover type of the Qilian mountain. Through the high-resolution remote sensing images to interprets the surface cover types. For the land types that cannot be reflected by the images, collect relevant data in the field, check and correct the land use types. At the same time, the maps and attribute information are uniformly entered and edited to form land use data in the Qilian Mountain area in 2018.
QI Yuan, ZHANG Jinlong, YAN Changzhen, DUAN Hanchen, JIA Yongjuan
This dataset is blended by two other sets of data, snow cover dataset based on optical instrument remote sensing with 1km spatial resolution on the Qinghai-Tibet Plateau (1989-2018) produced by National Satellite Meteorological Center, and near-real-time SSM/I-SSMIS 25km EASE-grid daily global ice concentration and snow extent (NISE, 1995-2018) provided by National Snow and Ice Data Center (NSIDC, U.S.A). It covers the time from 1995 to 2018 (two periods, from January to April and from October to December) and the region of Qinghai-Tibet Plateau (17°N-41°N, 65°E-106°E) with daily product, which takes equal latitude and longitude projection with 0.01°×0.01° spatial resolution, and characterizes whether the ground is covered by snow. The input data sources include daily snow cover products generated by NOAA/AVHRR, MetOp/AVHRR, and alternative to AVHRR taken from TERRA/MODIS corresponding observation, and snow extent information of NISE derived from observation by SSM/I or SSMIS of DMSP satellites. The processing method of data collection is as following: first, taking 1km snow cover product from optical instruments as initial value, and fully trusting its snow and clear sky without snow information; then, under the aid of sea-land template with relatively high resolution, replacing the pixels or grids where is cloud coverage, no decision, or lack of satellite observation, by NISE's effective terrestrial identification results. For some water and land boundaries, there still may be a small amount of cloud coverage or no observation data area that can’t be replaced due to the low spatial resolution of NISE product. Blended daily snow cover product achieves about 91% average coincidence rate of snow and non-snow identification compared to ground-based snow depth observation in years. The dataset is stored in the standard HDF4 files each having two SDSs of snow cover and quality code with the dimensions of 4100-column and 2400-line. Complete attribute descriptions is written in them.
ZHENG Zhaojun, CAO Guangzhen
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