Comparative analysis of deep learning approaches for forest stand type classification: insights from the new VHRTreeSpecies benchmark dataset
Remotely sensed data are widely used for forest stand type classification; however, traditional classification methods are time consuming and mostly implemented for spatially limited areas and species, restricting the transferability of these models to other locations and diverse species. With the i...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2522394 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|