Xingji Jin
Biographic Data
| ID | 10162928 |
|---|---|
| NAME | Xingji Jin |
| GIVEN NAMES | Xingji |
| FAMILY NAME | Jin |
| SIGNATURE | JIN X |
| AFFILIATIONS | Northeast Forestry University |
| ORCID | 0000-0003-2971-2709 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 1 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Evaluating kNN and regression methods for predicting tree and stand variables from LiDAR data in plantation forests
LiDAR scanning offers the possibility of reducing fieldwork in forest inventories. Growing stock variables can be derived from LiDAR data using k-nearest neighbor (kNN) data imputation or regression modeling. The inventory data needed for forest planning consist of either tree- or stand-level variables, depending on the type of model used for growth prediction. This study compared LiDAR-based regressions with kNN data imputation to obtain forest …
No prominent works on this page.
Evaluating kNN and regression methods for predicting tree and stand variables from LiDAR data in plantation forests
LiDAR scanning offers the possibility of reducing fieldwork in forest inventories. Growing stock variables can be derived from LiDAR data using k-nearest neighbor (kNN) data imputation or regression modeling. The inventory data needed for forest planning consist of either tree- or stand-level variables, depending on the type of model used for growth prediction. This study compared LiDAR-based regressions with kNN data imputation to obtain forest …
Forest Ecology and Biodiversity Studies (1 works) · Forest ecology and management (1 works) · Lidar (1 works) · Linear regression (1 works) · Regression (1 works) · Regression analysis (1 works) · Remote Sensing and LiDAR Applications (1 works) · Tree (set theory) (1 works)