DOAJ Open Access 2025

Deep learning based individual tree crown delineation from panchromatic aerial imagery

J. Tian J. Tian D. Panangian W. Fan B. Siegmann +1 lainnya

Abstrak

Accurate delineation of individual tree crowns (ITC) enables a better understanding of tree-level growth dynamics and evaluating tree vitality. In recent year, researches have introduced deep learning techniques in this field. However, the precise segmentation relies on high quality annotated dataset and test images with limited domain gaps between the training data. Under the framework of the Helmholtz project, panchromatic airborne images are captured over a mixed European forest. In this research, we adopt a UAV benchmark dataset as training data. To close the domain gaps, a deep learning based colorization step is added, for which two deep learning frameworks are compared to achieve an improved ITC delineation result in a dense forest area.

Topik & Kata Kunci

Technology Engineering (General). Civil engineering (General) Applied optics. Photonics

Penulis (6)

J. Tian

D. Panangian

W. Fan

B. Siegmann

X. Yuan

Format Sitasi

APA MLA BibTeX

Tian, J., Tian, J., Panangian, D., Fan, W., Siegmann, B., Yuan, X. (2025). Deep learning based individual tree crown delineation from panchromatic aerial imagery. https://doi.org/10.5194/isprs-annals-X-G-2025-885-2025

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber doi.org/10.5194/isprs-annals-X-G-2025-885-2025

Informasi Jurnal

Tahun Terbit: 2025
Sumber Database: DOAJ
DOI: 10.5194/isprs-annals-X-G-2025-885-2025
Akses: Open Access ✓