Digital soil mapping dataset of soil texture (soil particle-size fractions) in the Heihe river basin (2012-2016)

Select the soil mechanical composition data of 0-20cm depth of soil surface, select the optimal spatial prediction mapping method of soil composition data, and make the spatial distribution data product of soil texture (particle size composition). The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil sampling data integrated by the data center of cold and dry areas and the major research plan integration project of Heihe River Basin (spatial interpolation and dynamic simulation analysis of vegetation and environmental elements in the upper reaches of Heihe River basin / approval No. 91325204).

2020-03-27

Digital soil mapping dataset of soil depth in the Heihe River Basin (2012-2014)

The data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). The prediction method is mainly based on the soil landscape model. The basic theory of the model is the classic soil genesis theory. The model regards the soil as the product of the comprehensive effects of climate, topography, parent material, biology and time. Scope: Heihe River Basin; Projection: Albers ﹣ conic ﹣ equal ﹣ area; Spatial resolution: 90m; Data format: ArcGIS grid; Data content: spatial distribution of soil thickness Prediction method: enhanced regression tree Environmental variables: main soil forming factors

2020-03-27

Digital soil mapping dataset of soil texture in the Heihe river basin (2012-2014)

The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). The prediction method is mainly based on the soil landscape model. The basic theory of the model is the classic soil genesis theory. The model regards the soil as the product of the comprehensive effects of climate, topography, parent material, biology and time. Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF; Data content: spatial distribution of soil clay, silt and sand content Prediction method: enhanced regression tree Environmental variables: main soil forming factors

2020-03-27

Digital soil mapping dataset of hydrological parameters in the Heihe River Basin (2012)

According to the principle of soil landscape model, the key hydrological parameters spatial distribution map data products are made by digital soil mapping method. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). Scope: Heihe River Basin; Projection: WGS · 1984 · Albers / Albers · conic · equal · area; Spatial resolution: 90m; Data format: TIFF; Data content: spatial distribution of saturated water content, field water capacity, wilting water content and saturated conductivity Prediction method: enhanced regression tree Environmental variables: main soil forming factors Dataset content: Pr_0kpsm.tif: saturated water content (unit:%) Pr_33kp SM. TIF: field capacity (unit:%) X1500kp sm.tif: wilting water content (unit:%) SHC sm.tif: saturated hydraulic conductivity (unit: KS / (mm · min-1))

2020-03-27

Digital soil mapping dataset of soil organic carbon content in the Heihe river basin (2012)

According to the global soil map. Net standard, the 0-1m soil depth is divided into 5 layers: 0-5cm, 5-15cm, 15-30cm, 30-60cm and 60-100cm. According to the principle of soil landscape model, the spatial distribution data products of soil organic carbon content in different layers are produced by using the digital soil mapping method. The prediction method is mainly based on the soil landscape model. The basic theory of the model is the classic soil genesis theory. The model regards the soil as the product of the comprehensive effects of climate, topography, parent material, biology and time. This data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation, 91325301). Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF; Data content: spatial distribution of soil organic carbon content Prediction method: enhanced regression tree Environmental variables: main soil forming factors

2020-03-27

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2020-03-27

Guangxi Province 1:100000 landuse dataset (1985)

This data comes from "China's 1:100000 land use data". China's 1:100000 land use data is constructed in three years based on LANDSAT MSS, TM and ETM Remote sensing data by means of satellite remote sensing, organized by 19 research institutes affiliated to the Chinese Academy of Sciences under the national macro survey and dynamic research on remote sensing of resources and environment, a major application project of the eighth five year plan of the Chinese Academy of Sciences. Using a hierarchical land cover classification system, this data divides the whole country into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class categories. This is the most accurate land use data product in China, which has played an important role in the national land resource survey, hydrological and ecological research.

2020-03-26

Landuse/Landcover data of the Heihe river basin (2000)

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.

2020-03-15

Heihe 30m FAPAR production (2012)

Image format: tif Image size: about 925M per scene Time range: may-october 2012 Time resolution: month Spatial resolution: 30m The algorithm firstly adopts the canopy BRDF model and presents the canopy reflectivity as a function of a series of parameters such as FAPAR, wavelength, reflectance of soil and leaves, aggregation index, incidence and observation Angle.The parameter table is established for several key parameters as the input of inversion.Then input the pre-processed surface reflectance data and land cover data, and invert LAI/FAPAR products by look-up table (LUT) method. See references for detailed algorithm.

2020-03-15

The annual ecological investigation data of desert vegetation with different desert types in Heihe River basin (2011)

At the end of September and the beginning of October, 2011, a year-end ecological survey was carried out in heihe river basin for plants of different desert types to stop growing. There are altogether 8 survey and observation fields, which are: piedmont desert, piedmont gobi, middle reaches desert, middle reaches gobi, middle reaches desert, lower reaches desert, lower reaches gobi and lower reaches desert, with a size of 40m×40m. Three 20m×20m large quadrats were fixed in each observation field, named S1, S2 and S3, and regular shrub surveys were conducted.Each large quadrat was fixed with 4 5m x 5m small quadrats, named A, B, C, D, for the herbal survey.

2020-03-15