Two sets of grid data, aster GDEM data with a resolution of 30 meters and SRTM data with a resolution of 90 meters provided by the data management center of Heihe project, as well as point data from multiple sources, are used. By using the HASM scaling algorithm, the grid data of different sources and different precision are fused with the elevation point data to obtain the high precision slope data of Heihe River Basin. First of all, the accuracy of two groups of grid data is verified by using various point data. According to the results of accuracy verification, different grid data are used as the trend surface of data fusion in different regions. The residuals of various point data and trend surface are calculated, and the residual surface is obtained by interpolation with HASM algorithm, and the trend surface and residual surface are superposed to obtain the final slope surface. The spatial resolution is 500 meters.
2020-03-28
Two sets of grid data, aster GDEM data with a resolution of 30 meters and SRTM data with a resolution of 90 meters provided by the data management center of Heihe project, as well as point data from multiple sources, are used. By using the HASM scaling up algorithm, the grid data of different sources and different precision are fused with the elevation point data to obtain the high precision slope direction data of Heihe River Basin. First of all, the accuracy of two groups of grid data is verified by using various point data. According to the results of accuracy verification, different grid data are used as the trend surface of data fusion in different regions. The residuals of various point data and trend surface are calculated, and the residual surface is obtained by interpolation with HASM algorithm, and the trend surface and residual surface are superposed to obtain the final slope surface. The spatial resolution is 500 meters.
2020-03-28
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; Spatial resolution: 100M; Data format: TIFF;
2020-03-27
Using digital soil mapping method to produce soil surface pH spatial distribution data products. 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).
2020-03-27
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
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
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
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
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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