6 papers
ECHOSAT: Estimating Canopy Height Over Space And Time
Jan Pauls, Karsten Schrödter, Sven Ligensa +7
Forest monitoring is critical for climate change mitigation. However, existing global tree height maps provide only static snapshots and do not capture temporal forest dynamics, wh…
SERA-H: Super-Resolution of Sentinel Time Series for Fine-Scale Canopy Height Mapping
Thomas Boudras, Martin Schwartz, Rasmus Fensholt +6
High-resolution mapping of canopy height is essential for forest management and biodiversity monitoring. Although recent studies have led to the advent of deep learning methods usi…
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,…
Estimating Canopy Height at Scale
Jan Pauls, Max Zimmer, Una M. Kelly +6
We propose a framework for global-scale canopy height estimation based on satellite data. Our model leverages advanced data preprocessing techniques, resorts to a novel loss functi…