| Proj No. | A2098-251 |
| Title | Drone Photogrammetry with Machine Learning for Tree Species Classification in Forest Recovery |
| Summary | This project investigates the use of drone photogrammetry and machine learning to classify tree species in regenerating forests. High-resolution orthomosaics will be generated from drone imagery, followed by crown-level patch extraction and statistical reprojection for improved species separability. Deep learning and clustering methods will then be applied to identify and group species, with outputs visualised in QGIS to assess coverage and classification accuracy. This project offers students an opportunity to integrate remote sensing, computer vision, and ecological monitoring into a practical workflow for biodiversity assessment and forest recovery studies. |
| Supervisor | Dr Ji-Jon Sit (Loc:S2 > S2 B2A > S2 B2A 31, Ext: +65 67904437) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | Project (Loc: S2-B4a-01/02) |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: |