Ⅰ. Overview Landsat5 was launched in March 1984. The Thematic Mapper (TM) sensor on it includes seven bands, except for the 6th band with a resolution of 120 m, the other 6 bands have a resolution of 30 m. This data set was collected in 1990 and 2010. There are 77 scenes of TM data in the upper reaches of the Yellow River. Ⅱ. Data processing description The product level is L1 and has been geometrically corrected. Ⅲ. Data content description The naming method is LT5 line number column number _ column number year month day, such as LT5129032_03220040816. Ⅳ. Data usage description The main applications are soil use / cover and desertification monitoring.
0 2020-06-09
The data set contains the flux observation data of large aperture scintillator at areau station upstream of heihe hydrometeorological observation network.Two large aperture scintillation devices of German BLS450_AR and national zzlas were set up in the upstream areau station. The north tower was the receiving end of zzlas and the transmitting end of BLS450_AR, and the south tower was the transmitting end of zzlas and the receiving end of BLS450_AR.The observation period of zzlas is January 1, 2014, solstice, December 31, 2014, and the observation time of BLS450_AR is January 19, 2014, solstice, December 12, 2014.The station is located in the grass daban village, a soft township, qilian county, qinghai province.The latitude and longitude of the north tower is 100.4712e, 38.0568n, and the latitude and longitude of the south tower is 100.4572e, 38.0384 N, with an altitude of about 3033m.The effective height of the large aperture scintillator is 9.5m, the optical diameter length is 2390m, and the sampling frequency is 1min. Large aperture flicker meter raw observation data for 1 min, data released for 30 min after processing and quality control of data, including sensible heat flux is mainly combined with the automatic meteorological station observation data, based on similarity theory alonzo mourning - Mr. Hoff is obtained by iterative calculation, the quality control of the main steps include: (1) excluding Cn2 reach saturation data (BLS450_AR: Cn2 > 7.25 e-14, zzlas: Cn2 > 7.84 E - 14).(2) data with weak demodulation signal Intensity were removed (BLS450_AR: Average X Intensity<1000, zzlas: Demod>-20mv);(3) data at the time of precipitation were excluded;(4) data of weak turbulence under stable conditions were excluded (u* < 0.1m/s).In the iterative calculation process, for BLS450_AR, the stability universal function of Thiermann and Grassl, 1992 was selected.For zzlas, select Andreas 1988's stability universal function.Please refer to Liu et al.(2011, 2013) for detailed introduction. Several notes on the released data :(1) the upstream LAS data is mainly BLS450_AR, the missing time is supplemented by zzlas observation, and the missing time of both is marked by -6999.(2) missing period: on August 10, 2014, solstice, 16th, October 3, 2014, solstice, October 13, 2014, and October 17, 2014, solstice, 20th, data was missing due to instrument failure.(3) data table head: Date/Time: Date/Time (format: yyyy-m-d h:mm), Cn2: structural parameters of air refraction index (unit: m-2/3), H_LAS: sensible heat flux (unit: W/m2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format, please refer to the references for details. Please refer to Li et al.(2013) for hydrometeorological network or site information, and Liu et al.(2011) for observation data processing.
0 2020-03-05
In 2007 and 2008, Landsat data set 49 scenes, covering the entire black river basin. The acquisition time is:2007-08-12, 2007-09-23, 2008-01-05, 2008-02-06, 2008-03-17, 2008-03-25, 2008-05-10, 2008-05-19, 2008-05-28, 2008-06-04, 2008-07-07, 2008-07-15, 2008-07-22, 2008-07-23, 2008-08-16, 2008-08-30,2008-09-08, 2008-09-15, 2008-09-17, 2008-10-01, 2008-10-10, 2008-10-19, 2008-10-26, 2008-11-02, 2008-11-04, 2008-11-18, 2008-11-20, 2008-11-27, 2008-12-06, 2008-12-13, 2008-12-14. The product is class L1 and has been geometrically corrected.It includes 4 scenes of TM image and 45 scenes of ETM+ image. The Landsat satellite remote sensing data set of heihe integrated remote sensing joint experiment was obtained through free download.
0 2020-06-08
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of A’rou sunny slope station between 8 August, 2013, and 31 December, 2013. The site (100.520° E, 38.090° N) was located on a cold grassland surface in the sunny slope, which is near north of A’rou town, Qilian county, Qinghai Province. The elevation is 3529 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 m, north), wind speed and direction profile (034B; 10 m, north), air pressure (CS100; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109; 0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and two photosynthetically active radiation (PQS-1; 6 m, south, one vertically downward and one vertically upward). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content), and photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/(s m-2)). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2020-04-10
This dataset contains the automatic weather station (AWS) measurements from Zhangye wetland station in the flux observation matrix from 25 June to 21 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m and 10 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed (03002; 5 m and 10 m, towards north), wind direction (03002; 10 m, towards north), a four-component radiometer (NR01; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, and -0.4 m), and soil heat flux (HFP01; 3 duplicates, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m, RH_5 m and RH_10 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_5 m and Ws_10 m, m/s), wind direction (WD_10 m, °), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation; W/m^2), infrared temperature (IRT_1 and IR_2, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3, W/m^2), and soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, ℃). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
0 2019-09-15
Arctic 1:100,000 stream data set includes Arctic_River vector space data and related attribute data of different grades within the arctic range: Name and Type. The data comes from the 1:100,000 ADC_WorldMap global data set, which is a comprehensive, up-to-date and seamless geographic digital data after the data quality inspection of topology, warehousing and other data. The world map coordinate system is latitude and longitude, WGS84 datum surface, and the arctic data set is the special projection parameter for the arctic (North_Pole_Stereographic).
0 2019-09-15
Because of its unique natural conditions and geographical location, the Arctic region plays a very important role in global change. Polar sea ice, as an important influencing factor of climate change, is a sensitive instrument of global climate change. The Yellow River Station, one of China's research stations in the Arctic, focuses on supporting the three scientific fields of global change and its regional response, the polar space environment and space climate, and the life characteristics and processes in the polar environment, providing an important platform for China's in-depth scientific research activities in the Arctic. Therefore, the product data set of data validation for key areas of Arctic sea ice in recent years is constructed to monitor the key areas of Arctic sea ice.
0 2020-01-19
The data is the river dataset of the north slope of Tianshan River Basin. It is revised according to the topographic map and TM remote sensing image. The scale is 250,000, and the projection is latitude and longitude. The data includes spatial data and attribute data, attribute data fields: HYD_CODE (river code), Name (river name), SHAPE_ leng (river length).The data includes spatial data and attribute data. , SHAPE_leng (river length).
0 2020-04-06
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, on which basis the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations for the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
0 2021-01-08
The routine meteorological observation data set of four times a day provided by the data management center of Heihe plan is adopted, including 13 stations. The daily evaporation was statistically sorted out, and the monthly evaporation data of 2000-2009 years was calculated. The spatial stability analysis is carried out to calculate the coefficient of variation. If the coefficient of variation is greater than 100%, the geographical weighted regression is used to calculate the relationship between the station and the geographical terrain factors, and the monthly evaporation distribution trend is obtained; if the coefficient of variation is less than or equal to 100%, the common least square regression is used to calculate the relationship between the station evaporation value and the geographical terrain factors (latitude, longitude, elevation, slope, aspect, etc.) After the trend is removed, the residuals are fitted and corrected by HASM (high accuracy surface modeling method). Finally, the monthly average evaporation distribution of the Heihe River Basin in 1961-2010 is obtained by adding the trend surface results and the residual correction results. Time resolution: monthly average evaporation in 2000-2009. Spatial resolution: 500M.
0 2020-03-28
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