32 citations · 85 across the 5 of their papers we have counts for
6 papers
Super-Resolved Canopy Height Mapping from Sentinel-2 Time Series Using Airborne LiDAR HD Reference Data across Metropolitan France
Ekaterina Kalinicheva, Florian Helen, Stéphane Mermoz +2
Fine-scale forest monitoring is essential for understanding canopy structure and its dynamics, which are key indicators of carbon stocks, biodiversity, and forest health. Deep lear…
Tree species classification at the pixel-level using deep learning and multispectral time series in an imbalanced context
Florian Mouret, David Morin, Milena Planells +1
This paper investigates tree species classification using Sentinel-2 multispectral satellite image time-series. Despite their critical importance for many applications, such maps a…
Estimation of forest height and biomass from open-access multi-sensor satellite imagery and GEDI Lidar data: high-resolution maps of metropolitan France
David Morin, Milena Planells, Stéphane Mermoz +1
Mapping forest resources and carbon is important for improving forest management and meeting the objectives of storing carbon and preserving the environment. Spaceborne remote sens…
A Robust and Flexible EM Algorithm for Mixtures of Elliptical Distributions with Missing Data
Florian Mouret, Alexandre Hippert-Ferrer, Frédéric Pascal +1
This paper tackles the problem of missing data imputation for noisy and non-Gaussian data. A classical imputation method, the Expectation Maximization (EM) algorithm for Gaussian m…
Reconstruction of Sentinel-2 Time Series Using Robust Gaussian Mixture Models -- Application to the Detection of Anomalous Crop Development in wheat and rapeseed crops
Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit +3
Missing data is a recurrent problem in remote sensing, mainly due to cloud coverage for multispectral images and acquisition problems. This can be a critical issue for crop monitor…
Outlier detection at the parcel-level in wheat and rapeseed crops using multispectral and SAR time series
Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit +3
This paper studies the detection of anomalous crop development at the parcel-level based on an unsupervised outlier detection technique. The experimental validation is conducted on…