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RapidAI4EO - Advancing the State-of-the-Art for Rapid and Continuous Land Monitoring

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Change Detection Demo (opens in new window)

Demo for Change Detection with interactive heatmap visualizations showing the automatically identified changes in CLC classes

Demo of RapidAI4EO (opens in new window)

Demonstration of high cadence change detection and improved LULC mapping on the ONDA DIAS platform

Tentative POC with VHR imagery other than PlanetScope (opens in new window)

A proof of concept of the RAPIDAI4EO framework with VHR data other than PlanetScope

Packaged Augmented SpatioTemporal Training Corpus for open sourcing (opens in new window)

Package all datasets generated from Tasks 16 in preparation for open sourcing

Packaged SpatioTemporal Training Corpus for open sourcing (opens in new window)

Package all datasets generated to date in preparation for open sourcing

Monthly accuracy of change maps at 3 and 10 m res (opens in new window)

Validation of monthly heat maps of change over Europe

Monthly accuracy of CLC maps at 3 and 10 m res (opens in new window)

Validation of monthly LULC maps for the 3 AOIs

Implementation roadmap (opens in new window)

An assessment of the operationalisation of the demonstrated service in terms of its readiness for an operational deployment in the future in particular its costbenefit calendar and operational feasibility

36 monthly CLC+ Backbone raster layers over the 3AOIs (opens in new window)

Continuous monthly updates of the CLC+ backbone raster classification at 10m and 3m resolution using

Publications

RapidAI4EO: A Corpus for Higher Spatial and Temporal Reasoning (opens in new window)

Author(s): Giovanni Marchisio, Patrick Helber, Benjamin Bischke, Timothy Davis, Caglar Senaras, Daniele Zanaga, Ruben Van De Kerchove, Annett Wania
Published in: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, Page(s) 1161-1164, ISBN 978-1-6654-0369-6
Publisher: IEEE
DOI: 10.1109/igarss47720.2021.9553080

Rapidai4EO: A Multi-Format Dataset For Automated Land Cover Classification And Change Detection (opens in new window)

Author(s): Timothy Davis, Benjamin Bischke, Patrick Helber, Giovanni Marchisio, Caglar Senaras, Daniele Zanaga, Ruben Van de Kerchove, Annett Wania
Published in: Proceedings of the 2021 conference on Big Data from Space, 2021, Page(s) 65-68, ISBN 978-92-76-37661-3
Publisher: Publications Office of the EU
DOI: 10.2760/125905

Rapidai4Eo: Mono-and Multi-Temporal Deep Learning Models for Updating the Corine land Cover Product (opens in new window)

Author(s): P. Bhugra, B. Bischke, C. Werner, R. Syrnicki, C. Packbier, P. Helber, C. Senaras, A. S. Rana, T. Davis, W. De Keersmaecker, D. Zanaga, A. Wania, R. Van de Kerchove, G. Marchisio
Published in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, 2022, ISBN 978-1-6654-2793-7
Publisher: IEEE
DOI: 10.1109/igarss46834.2022.9883198

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