Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks

Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks

Mangrove ecosystems are vital blue carbon habitats, and their accurate mapping and ongoing monitoring are essential for conserving their unique ecological and environmental benefits. This study employed a weakly supervised deep learning framework for semantic segmentation of the ecosystem by integra...

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Bibliographic Details
Main Authors: Arsalan Ghorbanian, Ardalan Ghorbanian, Seyed Ali Ahmadi, Ali Mohammadzadeh, Amin Naboureh
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep convolutional neural network (CNN)
mangrove
semantic segmentation
Sentinel-1
synthetic aperture radar (SAR)
U-Net
Online Access:https://ieeexplore.ieee.org/document/11072052/
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https://ieeexplore.ieee.org/document/11072052/

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