Supervised Classification For Analysis Of Cryospheric Zones Using SAR Statistical Timeseries - 2020-2026, Edytem Équipe Morphodynamiques Access content directly
Conference Papers Year : 2024

Supervised Classification For Analysis Of Cryospheric Zones Using SAR Statistical Timeseries

Abstract

This study explores machine learning for classifying X-band Synthetic Aperture Radar (SAR) monovariate time-series from four cryospheric zones in the Mont-Blanc massif. We aim to classify ablation zones, accumulation zones, hanging glaciers, and ice aprons using log-cumulants and Dynamic Time Warping Barycentric Averaging. Our approach evaluates distances between time series and estimated reference centroids, employing HH and HV polarimetric channels. We propose an extension to this method by aggregating class membership probabilities from selected polarimetric combinations. Results are compared across polarimetric, revealing insights into classification performance.
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Dates and versions

hal-04628785 , version 1 (28-06-2024)

Identifiers

  • HAL Id : hal-04628785 , version 1

Cite

Christophe Lin-Kwong-Chon, Matthieu Gallet, Suvrat Kaushik, Emmanuel Trouvé. Supervised Classification For Analysis Of Cryospheric Zones Using SAR Statistical Timeseries. International Geoscience and Remote Sensing Symposium (IGARSS 2023), Jul 2024, Athens, Greece. ⟨hal-04628785⟩
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