September 12, 2025Earth Surface Processes and Landforms

Enhanced river planform analysis using deep learning and medial axis transform with Sentinel 1A imagery

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Authors

PTPawan ThapaUniversity of Alabama LDLisa DavisUniversity of Alabama AAAmobichukwu Chukwudi AmanambuUniversity of Alabama

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Implication

This approach detects river centrelines and water widths using deep learning and SAR imagery, suggesting new methodologies for planform geometry measurement.

Key Points

The method achieves high accuracy for extracting river centrelines and estimating water surface widths.
DeepLabV3 demonstrated a 0.933 F1-score for water mask extraction, showcasing its effectiveness in analysis.
Errors were observed primarily in complex braided river sections, especially the Mississippi River.
The integration of SAR imagery allows for data acquisition independent of weather conditions.

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Thapa et al. (2025) studied this question.

synapsesocial.com/papers/68d41da8713b0b5dfea66e48 https://doi.org/10.1002/esp.70158

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Implication

This approach detects river centrelines and water widths using deep learning and SAR imagery, suggesting new methodologies for planform geometry measurement.

Enhanced river planform analysis using deep learning and medial axis transform with Sentinel 1A imagery

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Enhanced river planform analysis using deep learning and medial axis transform with Sentinel 1A imagery

Discussion

Member takes

Implication

Key Points

Cite This Study

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