no code implementations • 22 Apr 2023 • Ibrahim Fayad, Philippe Ciais, Martin Schwartz, Jean-Pierre Wigneron, Nicolas Baghdadi, Aurélien de Truchis, Alexandre d'Aspremont, Frederic Frappart, Sassan Saatchi, Agnes Pellissier-Tanon, Hassan Bazzi
This model achieves better accuracy than previously used convolutional based approaches (ConvNets) optimized with only a continuous loss function.
no code implementations • 20 Dec 2022 • Martin Schwartz, Philippe Ciais, Catherine Ottlé, Aurelien De Truchis, Cedric Vega, Ibrahim Fayad, Martin Brandt, Rasmus Fensholt, Nicolas Baghdadi, François Morneau, David Morin, Dominique Guyon, Sylvia Dayau, Jean-Pierre Wigneron
In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy height.
no code implementations • 14 Oct 2016 • Ibrahim Fayad, Nicolas Baghdadi, Stéphane Guitet, Jean-Stéphane Bailly, Bruno Hérault, Valéry Gond, Mahmoud Hajj, Dinh Ho Tong Minh
We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics.