This dataset was derived from long-term daily snow depth in China based on the boundary of the three-river-source area. The snow depth ranges from 0 to 100 cm, and the temporal coverage is from January 1 1980 to December 31 2020. The spatial and temporal resolutions are 0.25o and daily, respectively. Snow depth was produced from satellite passive microwave remote sensing data which came from three different sensors that are SMMR, SSM/I and SSMI/S. Considering the systematic bias among these sensors, the inter-sensor calibrations were performed to obtain temporal consistent passive microwave remote sensing data. And the long-term daily snow depth in China were produced from this consistent data based on the spectral gradient method.For header file information, refer to the data set header.txt.
0 2021-04-20
The dataset was produced based on MODIS data. Parameters and algorithm were revised to be suitable for the land cover type in the Three-River-Source Regions. By using the Markov de-cloud algorithm, SSM/I snow water equivalent data was fused to the result. Finally, high accuracy daily de-cloud snow cover data was produced. The data value is 0(no snow) or 1(snow). The spatial resolution is 500m, the time period is from 2000-2-24 to 2019-12-31. Data format is geotiff, Arcmap or python+GDAL were recommended to open and process the data.
0 2021-04-20
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". According to the 1:100,000 land use data of gansu province, a hierarchical land cover classification system is adopted, 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.
0 2020-03-31
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.
0 2020-06-11
This data set contains meteorological element observation data of heihe remote sensing station in the middle reaches of heihe hydrometeorological observation network from January 1, 2015 to December 31, 2015.The station is located in the east of dangzhai town, zhangye city, gansu province.The longitude and latitude of the observation point are 100.4756e, 38.8270n and 1560m above sea level.The air temperature and humidity sensor is located at 1.5, facing due north.The barometer is in the waterproof box;The tilting bucket rain gauge is installed at 0.7 m;The wind speed and direction sensor is located at 10m, facing due north;The installation height of the four-component radiometer is 1.5m, facing due south;The installation height of the two infrared thermometers is 1.5m, facing due south and the probe facing vertically downward.The soil temperature probe is buried at 0cm on the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground.The soil water probe was buried at 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm.Average soil temperature probes were buried in 2cm and 4cm;The soil heat flow plate (3 pieces) is buried 6cm underground.Two photosynthetically active radiometers were set up 1.5m above the canopy (one probe vertically upwards and one probe vertically downwards), facing due south.Steam dishes were also observed (E601B, diameter 61.8cm). Observation projects are: air temperature and humidity (Ta_1. 5 m, RH_1. 5 m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (in watts/m2), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (in:Degrees Celsius), soil moisture (Ms_0cm Ms_2cm Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: c), up and down photosynthetic active radiation (PAR_U_up, PAR_U_down) (unit: second micromoles/m2), the average soil temperature (TCAV) (unit: c), the evaporating dish in the depth of the water, the depth (unit: mm). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;Data missing due to power supply problems;Due to collector problem, many observation elements have more error values;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: June 10, 2015, 10:30;(6) the naming rule is: AWS+ site name. For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).
0 2020-04-10
Data content: price index_ Consumer price index (CPI) (2010-2019) Data source and processing method: obtain the economic original data of the third pole (China region) price index from the official website of the world bank and sina.com from 2015 to 2019, and obtain the economic data set of the third pole (China region) price index from 2010 to 2019 through data sorting, screening and cleaning. The data start time is from 2010 to 2019 in Microsoft Excel (xlsx) format.
0 2020-11-03
On July 3, 2012, airborne ground synchronous observation was carried out in plmr sample belt near Linze station. Plmr (polarimetric L-band multibeam radiometer) is a dual polarized (H / V) L-band microwave radiometer, with a center frequency of 1.413 GHz, a bandwidth of 24 MHz, a resolution of 1 km (relative altitude of 3 km), six beam simultaneous observations, an incidence angle of ± 7 °, ± 21.5 °, ± 38.5 °, and a sensitivity of < 1K. The local synchronous data set can provide the basic ground data set for the development and verification of passive microwave remote sensing soil moisture inversion algorithm. Quadrat and sampling strategy: According to the typical ground surface type represented by three points near Linze station and taking part of neutron tube observation into account, the three routes from northwest to southeast are designed, with an interval of 200 m, a design altitude of about 300 m and a plmr ground resolution of 100 m. According to the observation characteristics of the route and plmr, three observation transects are designed on both sides of the route, each of which is about 6 km long. From west to East are L1, L2 and L3 respectively. Among them, L1 and L2 are centered on the middle route, 80 m apart; L2 and L3 are 200 m apart. Four hydroprobe data acquisition systems (HDAS, ref. 2) were used to measure at the same time. Measurement content: About 4500 points on the sample belt were obtained, each point was observed twice, that is to say, in each sampling point, once in the film (marked as a in the data record) and once out of the film (marked as B in the data record). As the HDAS system uses pogo portable soil sensor, the soil temperature, soil moisture (volume moisture content), loss tangent, soil conductivity, real part and virtual part of soil complex dielectric are observed. Vegetation parameter observation was carried out in some representative soil water sampling points, and the measurement of plant height and biomass (vegetation water content) was completed. Note: the observation date coincides with the irrigation of large area of farmland in this area, which makes it difficult for the observer to move forward, the field block is difficult to enter, and the observation point position deviates from the preset point position. Data: This data set includes two parts: soil moisture observation and vegetation observation. The former saves the data format as a vector file, the spatial location is the location of each sampling point (WGS84 + UTM 47N), and the measurement information of soil moisture is recorded in the attribute file; the vegetation sampling information is recorded in the excel table.
0 2020-03-14
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.
0 2020-03-31
China 1:100000 data of land use is a major application in the Chinese Academy of Sciences "five-year" project "the national resources and environment remote sensing macroscopic investigation and study of dynamic organized 19 Chinese Academy of Sciences institute of remote sensing science and technology team, by means of satellite remote sensing, in three years based on Landsat MSS, TM and ETM remote sensing data established China 1:100000 images and vector of land use database.The main contents include: China 1:100,000 land use data;China 1:100,000 land use graph data and attribute data. The data was directly clipped from China's 1:100,000 land-use data.A hierarchical land cover classification system was adopted for the land use data of heihe basin of 1:100,000, and the whole basin was divided 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 26 secondary categories.The data type is vector polygon, which is stored in Shape format.There are two types of data projection: WGS84/ALBERS;Data coverage covers the new heihe watershed boundary (lack of outer Mongolia data). Land use classification attributes: The first class type and the second class type attributes encode the spatial distribution position Cultivated paddy field 113 is mainly distributed in alluvial plain, basin and valley Cultivated paddy field 112 distributed in hilly valley narrow valley platform or beach (with irrigation conditions) Cultivated paddy field 111 is mainly distributed in mountain valley narrow valley platform or beach (with better irrigation conditions) Arable land 124 is mainly distributed in mountainous areas, the slope is generally more than 25 degrees (belongs to the steep slope hanging land), should be returned to forest. Cultivated dry land 123 is mainly distributed in basins, piedmont belts, river alluvial, diluvial or lacustrine plains (water shortage and poor irrigation conditions). Cultivated dry land 122 is mainly distributed in hilly areas (shaanxi, gan, ning, qing).In general, the plot is distributed on gentle slopes and x and sockets of hills. Arable land 121 is mainly distributed in the mountainous area, with an elevation of 4000 meters below the slope (gentle slope, mountainside, steep slope platform, etc.) and mountain front belt. Woodlands have woodlands (trees) 21 mainly distributed in the mountains (below 4000 meters above sea level) or in the slope, valley two slopes, mountain tops, plains.In qinghai nanshan, qilian mountains are. Woodland shrub 22 is mainly distributed in the higher mountain areas (below 4500 m), most of the distribution of hillside and valley and sand. Forest dredging 23 mainly distributed in the mountains, hills, plains and sandy land, gobi (soil, gravel) edge. Other woodlands 24 are mainly distributed in the oasis ridge, river, roadside and rural residential areas around. Grassland 31 is generally distributed in mountainous areas (gentle slopes), hills (steep slopes) and interriver beaches, gobi desert, sandy hills, etc. The covered grassland 32 is mainly distributed in dry places (next door low-lying land and sandy hills, etc.). Grassland low cover grassland 33 mainly grows in drier places (loess hills and sandy edges). The river channel 41 is mainly distributed in the plain, the cultivated land between the rivers and the valleys in the mountains. Water lakes are mainly distributed in low-lying areas. The reservoirs are mainly distributed in the intermountain lowlands and intersandy hills in qinghai province. Water area glaciers and permanent snow 44 mainly distributed in the plain, the valley between the river, there are surrounding residents and arable land. Waters and beaches are mainly distributed on the top of (over 4000) mountains.
0 2020-03-15
Based on the downscaling temperature result data in the historical period of CMIP5 (Coupled Model Intercomparison Project Phase 5), the future multi-year average temperature in the three periods of 2011-2040, 2041-2070, and 2071-2100 was predicted. Under the scenarios of rcp2.6, rcp4.5, and rcp8.5, the method of combining ordinary least squares regression with HASM (High Accuracy Surface Modeling Method) was used to downscaling simulate and predict, and the 1km downscaling results of the multi-year average temperature in the three scenarios of 2011-2040, 2041-2070 and 2071-2100 were obtained.
0 2020-03-02
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
