The VEGETATION sensor sponsored by the European Commission was launched by SPOT-4 in March 1998. Since April 1998, SPOTVGT data for global vegetation coverage observation has been received by Kiruna ground station in Sweden. The image quality monitoring center in Toulouse, France is responsible for image quality and provides relevant parameters (such as calibration coefficient number). Finally, the Belgian flemish institute for technological research (Vito)VEGETATION processing Centre (CTIV) is responsible for preprocessing into global data of 1km per day. Pretreatment includes atmospheric correction, radiation correction, geometric correction, production of 10 days to maximize the synthesized NDVI data, setting the value of -1 to -0.1 to -0.1, and then converting to the DN value of 0-250 through the formula DN= (NDVI+0.1)/0.004. The data set is the Shule River long-time series vegetation index data set, which is mainly aimed at normalized difference vegetation index (NDVI). It includes spectral reflectance of four bands synthesized every 10 days and maximum NDVI for 10 days from 1998 to 2008. The spatial resolution is 1km and the temporal resolution is ten days.

This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.

This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.

This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment". The 1:100,000 land use data set in gansu province adopts a hierarchical land cover classification system, which divides the whole country into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.

This data set comes from the Land use data of Zhangye city in 2005 completed by YAN Changzhen and others from Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The data was generated by manual interpretation based on Landsat TM and ETM remote sensing data around 2005. This data uses a hierarchical land cover classification system. There are six first-class classifications (cultivated land, woodland, grassland, waters, urban and rural areas, industrial and mining, residential land and unused land), and 25 second-class classifications covering five counties and one district of Zhangye City, Gansu Province. The land use classification criteria used by the Chinese Academy of Sciences since 1986 are adopted in this data. The data type is vector polygon, stored in Shape format, and the data range covers Zhangye City.

The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and International Institute for Applied System Analysis in Vienna (IIASA), which released version 1.1 on March 26, 2009. The data resolution is 1 km. The data source in China is 1: 1 million soil data. The soil classification system used is mainly FAO-90. The main fields of the soil property sheet include: SU_SYM90 (name of soil in FAO90 soil classification system) SU_SYM85 (FAO85 classification) T_TEXTURE (top soil texture) DRAINAGE (19.5); ROOTS: String (depth classification to the bottom of the soil with obstacles); SWR: String (characteristics of soil water content); ADD_PROP: Real (specific soil type in the soil unit related to agricultural use); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA Soil Texture Classification); T_REF_BULK: Real (soil bulk density); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cation exchange capacity of the sticky layer soil); T_CEC_SOIL: Real (soil cation exchange capacity) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field at the beginning of T_ indicates the upper soil attribute (0-30 cm), and the attribute field at the beginning of S_ indicates the lower layer soil attribute (30-100 cm) (FAO 2009). This data provides model input parameters for Earth system modelers, and in agricultural perspective, it can be used to study eco-agricultural divisions, food security, and climate change.

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.

The year-end ecological investigation was conducted in the late September and early October when plants stopped growing. There are 8 investigation and observation fields, they are: piedmont desert, piedmont Gobi, desert in the middle, Gobi in the middle reaches, desert in the middle reaches, downstream desert, downstream Gobi, and downstream desert, the size of each filed is 40m×40m. Three large quadrats of 20m×20m were selected in each observation field, named S1, S2, and S3, to conduce the regular shrub investigation; four small quadrats were selected from each large quadrat with a size of 5m×5m, named A, B, C, D, to conduct herbal investigation.

The micro-meteorological field is located in the grassland of Pailugou watershed of Qilian Mountain with an altitude of 2700m. The data were recorded from January 2011 to July 2012, and the time interval was half an hour, including 1.5m humidity, 3m temperature, 2.8m air pressure, 1.3m rainfall, 2.2m wind speed, 3.1m total radiation, the units are %, °C, Pa, m, m/s, W•M-2.

The runoff record of Pailugou watershed in the upper reaches of Heihe River, dated from January 2011 to September 2012. The data measuring device is the measuring weir at the exit of the small watershed, the unit of the data is m³/day.

The sampling and distribution of plant materials in the arid regions of the middle and lower reaches of Heihe River Basin. The plants are mainly shrubs and a few herbs. The numbering of plant materials is consistent with the morphological structural characteristics analysis table and is used in correspondence with each other.

The meteorological field is located at 3200m above sea level in Pailugou watershed of Qilian Mountain, which belongs to the high mountain forest line zone, the ecotone of Picea crassifolia forest and alpine shrub. This data set includes precipitation, air temperature, radiation, wind speed, etc., with units are mm, ℃, W/m^2 and m/s respectively. The date of data recording is from June 2012 to October 2013, in which the temperature data is partially missing due to the instrument.