The surface air temperature dataset of the Tibetan Plateau is obtained by downscaling the China regional surface meteorological feature dataset (CRSMFD). It contains the daily mean surface air temperature and 3-hourly instantaneous surface air temperature. This dataset has a spatial resolution of 0.01°. Its time range for surface air temperature dataset is from 1979 to 2018. Spatial dimension of data: 73°E-106°E, 23°N-40°N. The surface air temperature with a 0.01° can serve as an important input for the modeling of land surface processes, such as surface evapotranspiration estimation, agricultural monitoring, and climate change analysis.
DING Lirong, ZHOU Ji, WANG Wei
1. Data overview Take Ganzhou District, Linze County and Gaotai County of Zhangye City in the middle reaches of Heihe River Basin as the research area, and carry out input-output survey on agricultural, industrial and service enterprises and individuals in the research area from May to November 2013. According to the survey data, use the survey method to compile the input-output table of 42 departments in 2012 in this area. 2. The data content Data mainly reflects the input-output of various national economic industries in the process of production, circulation and consumption in ganlingao region in 2012.
Based on the data of downscaling results in the precipitation historical period of CMIP5 (Coupled Model Intercomparison Project Phase 5), the combined Method of geographical weighted regression and HASM (High Accuracy Surface Modeling Method) was used to analyze the annual mean precipitation in the future three periods of 2011-2040, 2041-2070 and 2071-2100 in the scenario of rcp2.6, rcp4.5 and rcp8.5. Through downscaling simulation and prediction, the 1km downscaling results of the multi-year average precipitation in the three periods of 2011-2040, 2041-2070 and 2071-2100 are obtained.
YUE Tianxiang, ZHAO Na
From May 2008 to July 2008, several synchronous observation quadrats were set up in the intensive observation area of Linze grassland. According to the spatial resolution of transit sensing, a 1.8km × 1.8km quadrat h and five 360m × 360m quadrats a, B, C, D and E are set up within 2km × 2km around Linze grassland station. There are 64 sampling points in sample h, numbered H01 to H64, and the distance between two adjacent points is 250m, mainly for MODIS synchronization. The sample a, B, C, D and e of 360m × 360m contains 49 sample points, the sample spacing is 60m, and the sample number is 01-49 (for example, sample a is a01-a49). The surface type of sample a is Phragmites australis, the surface type of sample B is saline alkali, and there are sparse Phragmites australis. The surface type of sample C is saline alkali, and Phragmites australis is more sparse than that of sample a. the surface type of sample D is alfalfa, and the surface type of sample e is alfalfa The type of table is barley field. A small sample of 120m × 120m is nested in each sample of a, B, C, D and e. the spacing of sample points in the small sample is 30m (see "sample distribution. PDF" in the data folder). Quadrats a, B, C, D, e and their nested small quadrats are mainly for ASAR, PALSAR, aster and airborne OMIS, widas synchronization. In addition, there are 7 microwave synchronous transects with 25 sampling points in each transect. The interval between the transects is 200m, and the interval between the sampling points on the transect is 100m. The No. l3-11 indicates the No. 11 sampling point on the No. 3 transect. PR2 is a 3 grid × 3 grid quadrat, and the distance between sampling points is 30 m. The number is pr11. There are also two PR2 transects, a total of 11 transects. The coordinates of all sample points are in Excel.
WANG Xufeng, WU Lizong, QU Yonghua, LI Hongxing, ZHOU Hongmin, HUANG Chunlin
The dataset of the automatic meteorological observations (2008-2009) was obtained at the Pailugou grassland station (E100°17'/N38°34', 2731m) in the Dayekou watershed, Zhangye city, Gansu province. The items included multilayer (1.5m and 3m) of the air temperature and air humidity, the wind speed (2.2m and 3.7m) and direction, the air pressure, precipitation, the global radiation, the net radiation, co2 (2.8m and 3.5m), the multilayer soil temperature (10cm, 20cm, 40cm, 60cm, 120cm and 160cm), soil moisture (10cm, 20cm, 40cm, 60cm, 120cm and 160cm), and soil heat flux (5cm, 10cm and 15cm). For more details, please refer to Readme file.
HUANG Guanghui, WU Lizong, QU Yonghua, LI Hongxing, ZHOU Hongmin, ZHANG Zhihui
Data content: precipitation data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the new generation of global precipitation measurement (GPM) of NASA (version 06, global precipitation observation program), the daily rainfall can be obtained by adding the three-hour rainfall data, and then the eight day rainfall can be obtained. Data quality: the spatial resolution is 0.1 ° x 0.1 ° and the temporal resolution is 8 days. The value of each pixel is the sum of rainfall in 8 days. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics.
XIAO Qing, Wen Jianguang
This dataset contains the automatic weather station (AWS) measurements from Bajitan Gobi station in the flux observation matrix from 13 May to 21 September, 2012. The site (100.30420° E, 38.91496° N) was located in a Gobi surface, which is near Zhangye city, Gansu Province. The elevation is 1562 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 (PTB110; 2 m), rain gauge (TE525M; 10 m), wind speed (03001; 5 m and 10 m, towards north), wind direction (03001; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (IRTC3; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (ECh2o-5; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFT3; 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), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux observation matrix measurements obtained from the automatic weather station (AWS) at the Daman superstation between 10 May and 26 September, 2012. The site (100.37223° E, 38.85551° N) was located in a cropland (maize surface) in the Daman irrigation, which is near Zhangye, Gansu Province. The elevation is 1556.06 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (AV-14TH; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 2.5 m), four-component radiometer (PSP&PIR; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, vertically downward), photosynthetically active radiation (LI-190SB; 12 m, towards south), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil heat flux (HFP01SC; 3 duplicates with one below the vegetation; and the other between plants, -0.06 m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m, m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30 m, and WD_40 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/m^2), infrared temperature (IRT_1 and IR_2, ℃), photosynthetically active radiation (PAR, μmol/ (s m^-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2, and Gs_3, W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm, ℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 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.
LIU Shaomin, LI Xin, XU Ziwei
This data includes the general layout of the reconstruction project of the middle reaches of the Heihe River, and describes in detail the water diversion flow, irrigation area and other data of each diversion outlet in the middle reaches of the Heihe River. It is attached with the statistical table of the current situation of the diversion portal (listing the diversion form, bank type, irrigation area name, irrigation area name and diversion flow of all diversion portal), the statistical table of the relative distance of the reconstructed diversion portal in the middle reaches (including the relative distance between the reconstructed diversion portal and Zhengyi gorge, bank type and the distance from the previous one), and the general layout plan of the combined reconstruction of the diversion portal (including the combined one Water diversion type, bank type, irrigation area name, irrigation area and water diversion flow) There is no vector format for the data, we only collect JPG format, with a diversion channel table.
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019, the National Meteorological Science Data Center of China Meteorological Administration (CMA) was established. By calculating the oxygen content, it is found that there is a significant linear correlation between oxygen content and altitude, y = - 0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
HE Xiaobo, ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
This data includes the accessibility of 15 kinds of public facilities and services, such as roads and schools, in the communities of 1280 households at domestic and abroad, as well as the farmers' satisfaction with these public facilities and public services by comparing that with 3 years ago and current status with neighboring village. This data is used to support the analysis of the material capital part of sustainable livelihood. The data was collected by the research group through field survey in 2019. Before collecting the data, the research group and invited experts conducted a pretest and improved the survey questionnaire; Before the formal investigation, the members participating in the data collection were strictly trained; In the formal survey, each questionnaire is checked three times before it is filed. This data is of great value for understanding the physical capital accessibility and satisfaction of rural households in environment-economic fragile areas, and is an important supplement to national and macro data.
This project is based on the gsflow model of USGS to simulate the surface groundwater coupling in Zhangye basin in the middle reaches of Heihe River. The space-time range and accuracy of the simulation are as follows: Simulation period: 1990-2012; Simulation step: day by day; The spatial scope of simulation: Zhangye basin; The spatial accuracy of simulation: the underground part is 1km × 1km grid (5 layers, the total number of grids in each layer is 150 × 172 = 25800, among which the active grid 9106); the surface part is based on the hydrological response unit (HRU) (588 in total, each HRU covers an area of several square kilometers to dozens of square kilometers). The data include: surface infiltration, actual evapotranspiration, average soil moisture content, surface groundwater exchange, shallow groundwater level, simulated daily flow of Zhengyi gorge, simulated monthly flow of Zhengyi gorge, groundwater extraction and river diversion
1. Data overview: This data set is the daily scale groundwater level data of Qilian station from November 1, 2011 to December 31, 2011. In October 2011, two groundwater monitoring wells were arranged in hulugou small watershed. Well 1 is located beside the general control hydrological section of hulugou watershed, with a depth of 12.8m and an aperture of 12cm. Well 2 is located in the east of the Delta, about 100m away from the river, with a depth of 14.7m and an aperture of 12cm. 2. Data content: U20hobo water level sensor is arranged in the groundwater well, which is mainly used to monitor the change of groundwater level and temperature in hulugou small watershed. The data content is the temperature and atmospheric pressure inside the hole, and the data is the daily scale data. 3. Space time scope: Geographic coordinates of well 1: longitude: longitude: 99 ° 53 ′ E; latitude: 38 ° 16 ′ n; altitude: 2974m (near the hydrological section at the outlet of the basin). Geographic coordinates of well 2: longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3204.1m (east side of the East Branch of the delta).
HAN Chuntan, CHEN Rensheng, SONG Yaoxuan, LIU Junfeng, YANG Yong, QING Wenwu, LIU Zhangwen
The Land Surface Temperature in China STC dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
WANG Xusheng, HU Xiaonong
All data in this data set are original data, including meteorological and soil moisture content, stem sap flow, water potential of plant tissue, isotope characteristics of atmospheric and humidified water vapor, fluorescence tracer image, plant photosynthetic fluorescence, and basic data of five desert plants, Tamarix chinensis, Haloxylon ammodendron, Bawang, Nitraria tangutorum and red sand, which are related to field and indoor control experiments Because of the data of expression regulation. 1. Isotopic data of Tamarix chinensis. After humidifying for 1 hour, 2 hours and 3 hours, the tissue samples of indoor and outdoor plants of plexiglass were collected at the same time. The samples were put forward and processed by low-temperature vacuum distillation glass water extraction system, and then used euro The isotopic data were measured by ea3000 element analyzer and isoprime gas stability mass spectrometer. Tamarix Tamarix samples were collected from Sitan village, Jingtai County, including humidification and control samples. The variation data of isotopic composition can be used to determine the way and amount of water vapor absorbed by plant leaves. 2. Fluorescence section photo data: all the data in this data set are original data, including the structural photos under high-power microscope of Tamarix, Haloxylon ammodendron, Nitraria, Bawang, Hongsha and other desert plant leaves in Sitan village of Jingtai County and Ejin Banner. The specific method is as follows: apply fluorescent dye to the surface of desert plant leaves before humidification, collect plant leaves and stems after humidification for 1 hour, 2 hours and 3 hours, put them in liquid nitrogen, take them back to the laboratory, observe and take photos with fluorescence microscope. It can be used to analyze the tissue and organs of water absorption by desert plant leaves and the direction and path of water migration in plants. 3: Gene transcription and expression data: transcription and expression data of Tamarix chinensis, data collection time: May 25, 2014, location: Sitan village, Jingtai County, Gansu Province, data analysis platform: lllumina hisep TM 2000 platform, obtained by transcriptome analysis of baimaike company. 4. Photosynthetic and fluorescence data: photosynthetic and fluorescence parameters measured by photosynthetic apparatus in the field (Sitan village and Ejin Banner, Jingtai County). 5. Sap flow and environmental data: all data are original data. Sap flow data of desert plants measured by stem flow meter, including Tamarix chinensis, Haloxylon ammodendron, Nitraria tangutorum, red sand and other desert plants (Sitan village, Jingtai County and Ejin Banner), and environmental data monitored by automatic weather station, including temperature and humidity.
This data set includes the 2015 observation data of 9 water net nodes in the 5.5km × 5.5km observation matrix (red box in the thumbnail) of Yingke / Daman irrigation area in the middle reaches of Heihe River. The nine nodes contain 4cm and 10cm two-layer hydro probe II probes to observe the main variables such as soil moisture, soil temperature, conductivity and complex permittivity; the si-111 infrared temperature probe is set up at 4m height to observe the surface radiation infrared temperature of the underlying surface. The observation time frequency is 5 minutes. This data set can provide spatiotemporal continuous observation data set for remote sensing estimation of key water and heat variables of heterogeneous surface, remote sensing authenticity test, ecological hydrology research, irrigation optimization management and other research.
JIN Rui, KANG Jian, LI Xin, MA Mingguo
The dataset is the field soil measurement and analysis data of the upstream of Heihe River Basin from 2013 to 2014, including soil particle analysis, water characteristic curve, saturated water conductivity, soil porosity, infiltration analysis, and soil bulk density I. Soil particle analysis 1. The soil particle size data were measured in the particle size laboratory of the Key Laboratory of the Ministry of Education, West Ministry of Lanzhou University.The measuring instrument is Marvin laser particle size meter MS2000. 2. Particle size data were measured by laser particle size analyzer.As a result, sample points with large particles cannot be measured, such as D23 and D25 cannot be measured without data.Plus partial sample missing. Ii. Soil moisture characteristic curve 1. Centrifuge method: The unaltered soil of the ring-cutter collected in the field was put into the centrifuge, and the rotor weight of each time was measured with the rotation speed of 0, 310, 980, 1700, 2190, 2770, 3100, 5370, 6930, 8200 and 11600 respectively. 2. The ring cutter is numbered from 1 to the back according to the number. Since three groups are sampled at different places at the same time, in order to avoid repeated numbering, the first group is numbered from 1, the second group is numbered from 500, and the third group is numbered from 1000.It's consistent with the number of the sampling point.You can find the corresponding number in the two Excel. 3. The soil bulk density data in 2013 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 4. Weight after drying: The drying weight of some samples was not measured due to problems with the oven during the experiment. 3. Saturated water conductivity of soil 1. Description of measurement method: The measurement method is based on the self-made instrument of Yiyanli (2009) for fixing water hair.The mariot bottle was used to keep the constant water head during the experiment.At the same time, the measured Ks was finally converted to the Ks value at 10℃ for analysis and calculation.Detailed measurement record table refer to saturation conductivity measurement description.K10℃ is the data of saturated water conductivity after conversion to 10℃.Unit: cm/min. 2. Data loss explanation: The data of saturated water conductivity is partly due to the lack of soil samples and the insufficient depth of the soil layer to obtain the data of the 4th or 5th layer 3. Sampling time: July 2014 4. Soil porosity 1. Use bulk density method to deduce: according to the relationship between soil bulk density and soil porosity. 2. The data in 2014 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 5. Soil infiltration analysis 1. The infiltration data were measured by the "MINI DISK PORTABLE specific vector INFILTROMETER".The approximate saturation water conductivity under a certain negative pressure is obtained.The instrument is detailed in website: http://www.decagon.com/products/hydrology/hydraulic-conductivity/mini-disk-portable-tension-infiltrometer/ 2.D7 infiltration tests were not measured at that time because of rain. Vi. Soil bulk density 1. The bulk density of soil in 2014 refers to the undisturbed soil taken by ring cutter based on the basis of 2012. 2. The soil bulk density is dry soil bulk density, which is measured by drying method.The undisturbed ring-knife soil samples collected in the field were kept in an oven at 105℃ for 24 hours, and the dry weight of the soil was divided by the soil volume (100 cubic centimeters). 3. Unit: G /cm3
The experimental data of Yingke Daman in Heihe River Basin is supported by the key fund project of Heihe River plan, "eco hydrological effect of agricultural water saving in Heihe River Basin and multi-scale water use efficiency evaluation". Including: soil bulk density, soil water content, soil texture, corn sample biomass, cross-section flow, etc Data Description: 1. Sampling location of Lai and aboveground biomass: Yingke irrigation district; sampling time: May 2012 to September 2012; Lai and aboveground biomass of maize were measured by canopy analyzer (lp-80), and aboveground biomass was measured by sampling drying method; sample number: 16. 2. Soil texture: Sampling location: Yingke irrigation district and Shiqiao Wudou Er Nongqu farmland in Yingke irrigation district; soil sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm; sampling time: 2012; measurement method: laboratory laser particle size analyzer; sample number: 38. 3. Soil bulk density: Sampling location: Yingke irrigation district and Daman irrigation district; sampling depth of soil bulk density is 100 cm, sampling levels are 0-50 cm and 50-100 cm respectively; sampling time: 2012; measurement method: ring knife method; number of sample points: 34. 4. Soil moisture content: this data is part of the monitoring content of hydrological elements in Yingke irrigation district. The specific sampling location is: Shiqiao Wudou Er Nongqu farmland in Yingke Irrigation District, planting corn for seed production; soil moisture sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm Methods: soil drying method and TDR measurement; sample number: 17. 5. Cross section flow: Sampling location: the farmland of Wudou Er Nong canal in Shiqiao, Yingke irrigation district; measure the flow velocity, water level and water temperature of different canal system sections during each irrigation, record the time and calculated flow, monitor once every 3 hours until the end of irrigation; sampling time: 2012.5-2012.9; measurement method: Doppler ultrasonic flow velocity meter (hoh-l-01, Measurement times: Yingke irrigation data of four times.
HUANG Guanhua, JIANG Yao
This dataset includes three scenes, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin, which were acquired on (yy-mm-dd hh:mm, BJT) 2012-07-25 07:12, 2012-07-28 19:55, 2012-08-02 07:12. The data were all acquired at PingPong mode with product level of SLC, and these three images are of VV/VH, HH/HV and VV/VH polarization, respectively. COSMO-SkyMed dataset was acquired from Italian Space Agency (ASI) “COSMO-SkyMed project 1720: HYDROCOSMO” (Courtesy: Prof. Shi Jiancheng from the State Key Laboratory of Remote Sensing Science of China).
Agenzia Spaziale Italiana (ASI)
This dataset includes one scene acquired on (yy-mm-dd) 2012-09-06, covering the natural oasis eco-hydrology experimental area in the lower reaches of the Heihe River Basin. This datum contains panchromatic and multi-spectral bands, with spatial resolution of 2.5 m and 10 m, respectively. The data product level of this image is Level 1. QuickBird dataset was acquired through purchase.
China Centre for Resources Satellite Data and Application