Hanjie Ni
Biographic Data
| ID | 9673117 |
|---|---|
| NAME | Hanjie Ni |
| GIVEN NAMES | Hanjie |
| FAMILY NAME | Ni |
| SIGNATURE | NI H |
| AFFILIATIONS | Department of Land Resource Management, School of Public Administration Jiangxi University of Finance and Economics Nanchang China |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Comparison of Machine Learning and Geostatistical Methods on Mapping Soil Organic Carbon Density in Regional Croplands and Visualizing Its Location‐Specific Dominators via Interpretable Model
High‐precision soil organic carbon density (SOCD) map is significant for understanding ecosystem carbon cycles and estimating soil organic carbon storage. However, the current mapping methods are difficult to balance accuracy and interpretability, which brings great challenges to the mapping of SOCD. In the present research, a total of 6223 soil samples were collected, along with data pertaining to 30 environmental covariates, from agricultural l…
Mapping soil organic matter and identifying potential controls in the farmland of Southern China
Soil organic matter (SOM) plays a critical role in terrestrial ecosystem functioning and is closely related to many global issues like soil fertility, soil health and climate regulation. Therefore, obtaining accurate information on the spatial distribution of SOM and its potential controlling factors is of global interest. However, this remains a great challenge since SOM is affected by numerous natural and anthropogenic factors and usually showe…
No prominent works on this page.
Mapping soil organic matter and identifying potential controls in the farmland of Southern China
Soil organic matter (SOM) plays a critical role in terrestrial ecosystem functioning and is closely related to many global issues like soil fertility, soil health and climate regulation. Therefore, obtaining accurate information on the spatial distribution of SOM and its potential controlling factors is of global interest. However, this remains a great challenge since SOM is affected by numerous natural and anthropogenic factors and usually showe…
Comparison of Machine Learning and Geostatistical Methods on Mapping Soil Organic Carbon Density in Regional Croplands and Visualizing Its Location‐Specific Dominators via Interpretable Model
High‐precision soil organic carbon density (SOCD) map is significant for understanding ecosystem carbon cycles and estimating soil organic carbon storage. However, the current mapping methods are difficult to balance accuracy and interpretability, which brings great challenges to the mapping of SOCD. In the present research, a total of 6223 soil samples were collected, along with data pertaining to 30 environmental covariates, from agricultural l…
Environmental Science (2 works) · Geostatistics (2 works) · Mathematics (2 works) · Soil carbon (2 works) · Soil Geostatistics and Mapping (2 works) · Soil Science (2 works) · Soil water (2 works) · Spatial variability (2 works) · Statistics (2 works) · Agronomy (1 works)