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MultiEarth 2023 -- Multimodal Learning for Earth and Environment Workshop and Challenge
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The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) is the second annual CVPR workshop aimed at the monitoring and analysis of the health of Earth ecosystems by leveraging the vast amount of remote sensing data that is continuously being collected. The primary objective of this workshop is to bring together the Earth and environmental science communities as well as the multimodal representation learning communities to explore new ways of harnessing technological advancements in support of environmental monitoring. The MultiEarth Workshop also seeks to provide a common benchmark for processing multimodal remote sensing information by organizing public challenges focused on monitoring the Amazon rainforest. These challenges include estimating deforestation, detecting forest fires, translating synthetic aperture radar (SAR) images to the visible domain, and projecting environmental trends. This paper presents the challenge guidelines, datasets, and evaluation metrics. Our challenge website is available at https://sites.google.com/view/rainforest-challenge/multiearth-2023.
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TiMo: Spatiotemporal Foundation Model for Satellite Image Time Series
TiMo, a hierarchical transformer pretrained on one million Sentinel-2 images with a space-time gyroscope attention, reports state-of-the-art accuracy on deforestation, land cover, crop type, and flood mapping tasks.
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