5 papers
From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps
Ghjulia Sialelli, Robin Young, Yuchang Jiang +9
Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by advances in machine learning (…
deadtrees.earth-aerial: A Multi-Resolution Aerial Image Dataset for Tree Cover and Mortality Detection
Ayushi Sharma, Clemens Mosig, Lukas Drees +9
Forests worldwide are increasingly threatened by climate change and disturbances such as fire, pests, and pathogens, creating an urgent need for scalable monitoring of tree cover a…
FORMSpoT: A Decade of Tree-Level, Country-Scale Forest Monitoring
Martin Schwartz, Fajwel Fogel, Nikola Besic +9
The recent decline of the European forest carbon sink highlights the need for spatially explicit and frequently updated forest monitoring tools. Yet, existing satellite-based distu…
Context-Aware Multimodal Representation Learning for Spatio-Temporally Explicit Environmental Modelling
Julia Peters, Karin Mora, Miguel D. Mahecha +4
Earth observation (EO) foundation models have emerged as an effective approach to derive latent representations of the Earth system from various remote sensing sensors. These model…
Transformers vs. Recurrent Models for Estimating Forest Gross Primary Production
David Montero, Miguel D. Mahecha, Francesco Martinuzzi +6
Monitoring the spatiotemporal dynamics of forest CO uptake (Gross Primary Production, GPP), remains a central challenge in terrestrial ecosystem research. While Eddy Covariance…