CSTR:11738.11.ncdc.nieer.db2735.2023
10.12072/ncdc.nieer.db2735.2023
This data includes 1 km of 20 cm and 100 cm of the surface layer of Qilian Mountain National Park from 2000 to 2015 × Annual spatial distribution map of soil organic carbon density with 1 km resolution and 1 km of surface 20 cm and 100 cm in 2016-2100 under three climate scenarios (RCP2.6/4.5/8.5) × The spatial distribution map of soil organic carbon density with 1 km resolution is predicted year by year.
A data-driven model based on ground measured samples was used to simulate soil organic carbon at regional scale.
Use Python language to process spatiotemporal data, and build a soil organic carbon spatial inversion model based on the "scikit-learn" database to simulate the spatial distribution of soil organic carbon at different depths. The future climate data will be calibrated and scaled down using the delta spatial scaling method.
1. The original data is from published documents and databases, and its accuracy is fully verified and controlled by the author of the original document;
2. The model construction process is completely carried out in accordance with the standard construction scheme of data-driven model, and the method is standardized, and the robustness and robustness of the model are fully verified by the cross-validation method;
3. The quality of the simulation results was fully compared and verified by using multi-source data such as observation data and mainstream soil organic carbon spatial distribution data, which proved the accuracy and reliability of the simulation results of this study.
| # | number | name | type |
| 1 | 2019YFC0507400 | National key R & D plan |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
