Search Results for author: Martin Béland

Found 1 papers, 1 papers with code

Evaluating deep learning methods applied to Landsat time series subsequences to detect and classify boreal forest disturbances events: The challenge of partial and progressive disturbances

1 code implementation Remote Sensing of Environment 2024 Pauline Perbet, Luc Guindon, Jean-François Côté, Martin Béland

The goal of this paper is to explore the use of a subset of Landsat time series and deep learning models to identify both the type and the year of disturbances, including low-severity and gradual disturbances, in the boreal forest of eastern Canada at the pixel level.

Time Series

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