6 papers
Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates
Kelsey Doerksen, Yuliya Marchetti, Kevin Bowman +5
Air pollution is the world's largest environmental risk factor for human disease and premature death, resulting in more than 6 million permature deaths in 2019. Currently, there is…
Uncertainty Quantification for Surface Ozone Emulators using Deep Learning
Kelsey Doerksen, Yuliya Marchetti, Steven Lu +5
Air pollution is a global hazard, and as of 2023, 94\% of the world's population is exposed to unsafe pollution levels. Surface Ozone (O3), an important pollutant, and the drivers…
Open High-Resolution Satellite Imagery: The WorldStrat Dataset -- With Application to Super-Resolution
Julien Cornebise, Ivan OrÅ¡oliÄ, Freddie Kalaitzis
Analyzing the planet at scale with satellite imagery and machine learning is a dream that has been constantly hindered by the cost of difficult-to-access highly-representative high…
Dargana: fine-tuning EarthPT for dynamic tree canopy mapping from space
Michael J. Smith, Luke Fleming, James E. Geach +3
We present Dargana, a fine-tuned variant of the EarthPT time-series foundation model that achieves specialisation using <3% of its pre-training data volume and 5% of its pre-traini…
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data
Matthew J Allen, Francisco Dorr, Joseph Alejandro Gallego Mejia +4
Satellite-based remote sensing has revolutionised the way we address global challenges. Huge quantities of Earth Observation (EO) data are generated by satellite sensors daily, but…
Large Scale Masked Autoencoding for Reducing Label Requirements on SAR Data
Matt Allen, Francisco Dorr, Joseph A. Gallego-Mejia +4
Satellite-based remote sensing is instrumental in the monitoring and mitigation of the effects of anthropogenic climate change. Large scale, high resolution data derived from these…