This dataset is the distribution data of soil moisture in the root zone of the Genhe River Basin in the Erguna area on the western slope of the Greater Khingan Range, combined with soil moisture measurement data obtained through mechanical/manual drilling and exploration pits; The environmental factor data comes from spatial datasets such as climate, soil, terrain, vegetation types, etc., and the model is constructed using machine learning methods (Extra Trees). The data format is GeoTIFF, with a spatial resolution of approximately 30m and a projection of WGS1984_ Albers.
Raw data: The sample points are based on soil moisture measurement data obtained through mechanical/manual drilling and exploration pits;
The environmental factor data comes from spatial datasets such as climate, soil, terrain, vegetation types, etc.
Use Python and ArcGIS tools to process environmental factor data, and use the Extra Trees model for 10 layer soil moisture spatial prediction.
This data is modeled using machine learning methods and validated using an independent validation set. The results show that the model has high consistency.
| # | number | name | type |
| 1 | 2022FY100700 | Survey of Permafrost Conditions and Freeze-Thaw Damage in the High-Latitude Regions of Northeast China | Basic Resource Survey Project |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.NIEER.DB7255.2026
10.12072/ncdc.nieer.db7255.2026
