9 citations · 9 across the 3 of their papers we have counts for
5 papers · 1 filter
FORMSpoT: Revealing Fine-Scale Forest Disturbances from Nation-Wide 1.5 m Forest Canopy Height Time Series
Martin Schwartz, Fajwel Fogel, Nikola Besic +9
Current large-scale satellite-based forest disturbance monitoring systems operate at 10-30~m resolution, too coarse to detect changes at the scale of individual trees and resulting…
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications
Ibrahim Fayad, Max Zimmer, Martin Schwartz +6
Significant efforts have been directed towards adapting self-supervised multimodal learning for Earth observation applications. However, most current methods produce coarse patch-s…
Open-Canopy: Towards Very High Resolution Forest Monitoring
Fajwel Fogel, Yohann Perron, Nikola Besic +8
Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications. However,…
Vision Transformers, a new approach for high-resolution and large-scale mapping of canopy heights
Ibrahim Fayad, Philippe Ciais, Martin Schwartz +8
Accurate and timely monitoring of forest canopy heights is critical for assessing forest dynamics, biodiversity, carbon sequestration as well as forest degradation and deforestatio…
Detecting Methane Plumes using PRISMA: Deep Learning Model and Data Augmentation
Alexis Groshenry, Clement Giron, Thomas Lauvaux +2
The new generation of hyperspectral imagers, such as PRISMA, has improved significantly our detection capability of methane (CH4) plumes from space at high spatial resolution (30m)…