DeepBioFusion: Multi-modal deep learning based above ground biomass estimation using SAR and optical satellite images
Accurate estimation of forest above-ground biomass (AGB) is essential for ecosystem conservation, sustainable forest management, and mitigating climate change and wildfire risks. Traditional methods, such as manual field surveys, are labor-intensive and limited in scope. This study presents DeepBioF...
Saved in:
Main Authors: | Abdul Hanan, Mehak Khan, Nieves Fernandez-Anez, Reza Arghandeh |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-12-01
|
Series: | Ecological Informatics |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125002869 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass
by: Yongjie Ji, et al.
Published: (2025-03-01) -
Estimation of Tree Diameter at Breast Height (DBH) and Biomass from Allometric Models Using LiDAR Data: A Case of the Lake Broadwater Forest in Southeast Queensland, Australia
by: Zibonele Mhlaba Bhebhe, et al.
Published: (2025-07-01) -
Local Information-Driven Hierarchical Fusion of SAR and Visible Images via Refined Modal Salient Features
by: Yunzhong Yan, et al.
Published: (2025-07-01) -
Few-Shot SAR Target Recognition via Causal Inference and Deep Metric Learning
by: Ke Wang, et al.
Published: (2025-01-01) -
Sub-hectare resolution forest biomass mapping from Copernicus DEM with low-dimensional models
by: Maciej J. Soja, et al.
Published: (2025-12-01)