Refining Water Body Extraction by Remote Sensing With Deep Learning Models: Exploring Different Band Combinations

Refining Water Body Extraction by Remote Sensing With Deep Learning Models: Exploring Different Band Combinations

Satellite-based remote sensing is essential for monitoring water resources and supporting ecological conservation and sustainable development. However, complex scenarios, such as cloud shadows and ice–snow misclassification, challenge traditional methods, such as spectral indices and thre...

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Bibliographic Details
Main Authors: Ziheng Feng, Fei Zhang, Xu Ma, Chi Yung Jim, Di Wu, Dong Liu, Saheed Adeyinka Oke, Weiwei Wang, Lifei Wei, Songlin Nie, Zhihui Li, Haowei Xu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Arid region
band combinations
deep learning
semantic segmentation
Sentinel-2 satellite
transformer model
Online Access:https://ieeexplore.ieee.org/document/11072927/
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https://ieeexplore.ieee.org/document/11072927/

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