HackerPapers

arXiv:2110.01919cs.CV

RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning

Giovanni Marchisio, Patrick Helber, Benjamin Bischke, Timothy Davis, Caglar Senaras, Daniele Zanaga, Ruben Van De Kerchove, Annett Wania

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

Under the sponsorship of the European Union Horizon 2020 program, RapidAI4EO will establish the foundations for the next generation of Copernicus Land Monitoring Service (CLMS) products. The project aims to provide intensified monitoring of Land Use (LU), Land Cover (LC), and LU change at a much higher level of detail and temporal cadence than it is possible today. Focus is on disentangling phenology from structural change and in providing critical training data to drive advancement in the Copernicus community and ecosystem well beyond the lifetime of this project. To this end we are creating the densest spatiotemporal training sets ever by fusing open satellite data with Planet imagery at as many as 500,000 patch locations over Europe and delivering high resolution daily time series at all locations. We plan to open source these datasets for the benefit of the entire remote sensing community.

arXiv comments
Published in the IEEE 2021 International Geoscience & Remote Sensing Symposium (IGARSS 2021)
Journal reference
DOI
Subjects
cs.CVComputer Vision and Pattern Recognition

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Oct 2021 to Oct 2021. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.