The project of material and energy exchange and community stability of soil-plant gas interface in oasis-gobi transition zone belongs to the major research program of "environmental and ecological science in western China" sponsored by the national natural science foundation, and is headed by professor Wang genxuan of Lanzhou university. the running time of the project is from January 2002 to December 2004. Data collected for this project: 1. Status of energy utilization rate of desert natural vegetation The data is in Excel format. The individual size of plants and biomass of green photosynthetic tissue measured by randomly selecting some plants from the desert natural vegetation sample are mainly used to explore the energy utilization rate model of desert plants in this project, including variables such as average total biomass, average biomass of photosynthetic tissue and population density. 2. Survey data on basic information of natural vegetation community institutions in sample plots The data is in Excel format, including survey and analysis data of vegetation density and average underground biomass in Lanzhou, Baiyin and Jingtai.
0 2020-06-09
Forest survey is the application of measurement, tree measurement, remote sensing and other professional techniques and methods, survey, sampling and computer technology and other means to understand the quantity, quality, distribution and growth of forests within a specific range, so as to provide basic data for the formulation of forestry policies and scientific management of forests, as well as for scientific research. In the drainage ditch watershed of Qilian Mountain, there are three plots of Picea crassifolia forest in Qinghai Province, each of which is 2800m, 2900m and 3000m above sea level. Plot 01 is 20 * 30m and plot 02-09 is 20 * 35m. The traditional methods were used to investigate the tree height, DBH, base diameter and crown diameter of Picea crassifolia, providing basic data for the study of ecological hydrology of Picea crassifolia forest in the upper reaches of Heihe River.
0 2020-03-10
This glacier inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nations Environment Programme/Regional Resource Centre, Asia and The Pacific (UNEP/RRC-AP). 1.The glacier inventory incorporates topographic map data, and reflects the status of glaciers in the region in 2000. 2.The spatial coverage of the glacier inventory includes the following: Pa Chu Sub-basin,Mo Chu Sub-basin,Thim Chu Sub-basin,Pho Chu Sub-basin,Mangde Chu Sub-basin, Chamkhar Chu Sub-basin,Kuri Chu Sub-basin,Dangme Chu Sub-basin,Northern Basin, etc. 3.The glacier inventory includes the following data fields: glacier location, glacier code, glacier name, glacier area, glacier length, glacier thickness, glacier stocks, glacier type, glacier orientation, etc. 4.Data projection: Projection: Polyconic Ellipsoid: Everest (India 1956) Datum: Indian (India, Nepal) False easting: 2,743,196.4 False northing: 914,398.80 Central meridian: 90°0'00'' E Central parallel: 26°0'00' N Scale factor: 0.998786 For a detailed description of the data, please refer to the data file and report.
0 2020-06-04
The field experiments of water consumption and irrigation water productivity of corn and cotton were arranged in 2012 and 2013, and the field experiments of irrigation water productivity of corn and sunflower under different mulching and cultivation methods were arranged in 2014. The characteristics of water consumption and irrigation water demand of three crops under different soil conditions, as well as the relationship between key soil properties and crop yield and irrigation water productivity were obtained.
0 2020-03-07
Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The data set is the administrative boundary vector map of Shule River Basin, with a scale of 250000. The data includes spatial data and attribute data. The attribute fields are name (county boundary name) and code (administrative code). Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
0 2020-03-30
The 5-day Lai synthesis results in 2015 are provided by the 1 km / 5-day Lai data set of Heihe River Basin. The data set is constructed by using the data of Terra / MODIS, Aqua / MODIS, as well as the domestic satellites fy3a / MERSI and fy3b / MERSI to construct the multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. Multi-source remote sensing data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm first classifies the quality of multi-source data sets, which can be divided into first level data, second level data and third level data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. The purpose of quality evaluation and classification is to provide the basis for the selection of the optimal data set and the design of inversion algorithm flow. Leaf area index product inversion algorithm is designed to distinguish mountain land and vegetation type, using different neural network inversion model. Based on global DEM map and surface classification map, PROSAIL model is used for continuous vegetation such as grassland and crops, and gost model is used for forest and mountain vegetation. Using the reference map generated by the measured ground data of the forests in the upper reaches of Heihe River and the oasis in the middle reaches, and scaling up the corresponding high-resolution reference map to 1km resolution, compared with the Lai product, the product has a good correlation between the farmland and the forest area and the reference value, and the overall accuracy basically meets the accuracy threshold of 0.5%, 20% specified by GCOS. By cross comparing this product with Lais products such as MODIS, geov1 and glass, the accuracy of this Lai product is better than that of similar products compared with reference value. In a word, the synthetic Lai data set of 1km / 5 days in Heihe River Basin comprehensively uses multi-source remote sensing data to improve the estimation accuracy and time resolution of Lai parameter products, so as to better serve the application of remote sensing data products.
0 2020-03-13
This dataset is TM remote sensing data covers western China, around the 1980s. Data attributes: Pixel Size: 30-meter reflective: Bands 1-5 and 7 60-meter thermal: Band 6 Output Format: GeoTIFF Resampling method: cubic convolution (CC) Map Projection: UTM – WGS 84 Polar Stereographic for the continent of Antarctica. Image Orientation: Map (North Up) The data was partially downloaded from the USGS http://eros.usgs.gov/ website, and partly collected from various projects. The data folder is named the row and column number where the image is located. The folder contains TM 7 bands images (* .tif), header files (* .met, * .hdr) and thumbnails (jpg). The naming format of image files is row and column number _TM image mark (5t), and image acquisition time _ band number.
0 2020-03-27
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, 2016 to December 31, 2016.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 1.5m, 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. 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:C), soil moisture (Ms_0cm, Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: %), upward and downward photosynthetically active radiation (PAR_U_up, PAR_U_down) (unit: micromole/sq.s), mean soil temperature (TCAV) (unit: Celsius). 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;2016.1.01-1.29 due to collector problems, 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: 2016-6-10-10:30;(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
The dataset covers western China. MSS remote sensing images Dataset properties: Pixel Size: 60m Reflective bands 4-7 (Landsat 1-3) and Bands 1-4 (Landsat 4-5) Output Format: GeoTIFF Resampling method: cubic convolution (CC) Map Projection: UTM – WGS 84 Polar Stereographic for the continent of Antarctica. Image Orientation: Map (North Up) Data sources were partially downloaded from http://eros.usgs.gov/ and some were collected from various projects. The data folder is named the row and column number where the image is located. The folder contains the MSS 4 band images (* .tif), header files (* .met, * .hdr), and thumbnails (jpg). The naming format of image files is row and column number_TM image mark (2m), and image acquisition time_band number. It is mainly used for thematic analysis and compilation of different scale thematic maps on agriculture, forestry, water, soil, geology, geography, geography, surveying and mapping, regional planning, and environmental monitoring.
0 2020-03-30
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).
0 2020-10-13
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