Open-Earth-Monitor Cyberinfrastructure

Food, Bioeconomy & Natural ResourcesHORIZON-IAID: 101059548
EC Contribution
€127,200
Consortium Size
23 orgs
Start Year
2022
Summary

The Open-Earth-Monitor Cyberinfrastructure will increase European capability to generate timely, accurate, disaggregated, people-centred, accessible (GSM-compatible) and user-friendly environmental information based on Earth Observation data. We will achieve this by building a cyberinfrastructure anchored in FAIR data principles, leveraging and improving our existing platforms OpenEO.org, Geopedia.world, GlobalEarthMonitor.eu, EarthSystemDataLab.net, OpenLandMap.org, OpenDataScience.eu, LifeWatch.eu, XCUBE and EuroDataCube.com. We do this in 3 phases:a) implementation of the computing engine and in-situ O&M data services;b) direct application of the Open-Earth-Monitor to support EU Green Deal and other strategic actions;c) dissemination and engagement of stakeholders & target users through series of open workshops, then revise the tools and adjust them to better fit their objectives and limitations. We specifically target contributing to:operational planning for planting 3 billion trees over the EU by 2030; achieving climate-neutrality by 2035 in the land sector; building back a net-zero GHG emission economy by 2050; achieving UN’s SDGs’; monitoring essential biodiversity indicators; compiling natural capital accounts for private / public sectors; enabling businesses to leverage competitive advantage through the EU Green Deal; increasing the quality of life for European Citizens. We will innovate: 1) implementation of original cloud-based solutions to seamlessly integrate in-situ (point, site) & EO data so that we can produce environmental information at analysis- and decision-ready levels;2) implementation of fully-scalable Automated Mapping / AutoML frameworks;3) user-experience-designed data provision and Apps possibly reaching millions of users across EU and globally;4) financial assessment tools allowing users to directly quantify ecosystem services (SEEA methodology), to identify optimal environmental and climate solutions, & to build business solutions.

Consortium (23)

Project Results (60)

Source: CORDIS, the EU research results database.

Publications (44)
PeerJ
PeerJ· 2025DOI
Ho Y, Grohmann CH, Lindsay J, Reuter HI, Parente L, Witjes M, Hengl T.
A pre-whitening with block-bootstrap cross-correlation procedure for temporal alignment of data sampled by eddy covariance systems
Environmental and Ecological Statistics· 2024DOI
Vitale Domenico, Fratini Gerardo, Helfter Carol, Hortnagl Lukas, Kohonen Kukka-Maaria, Mammarella Ivan, Nemitz Eiko, Nicolini Giacomo, Rebmann Corinna, Sabbatini Simone & Papale Dario
Environmental Research Letters
Environmental Research Letters· 2024DOI
Johannes Reiche Johannes Balling, Amy Hudson Pickens, Robert N Masolele, Anika Berger, Mikaela J Weisse, Daniel Mannarino, Yaqing Gou, Bart Slagter, Gennadii Donchyts
Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution
PeerJ Inc.· 2024DOI
Hackländer, J., Parente, L., Ho, Y.-F., Hengl, T., Simoes, R., Consoli, D., Şahin, M., Tian, X., Herold, M., Jung, M., Duveiller, G., Weynants, M., Wheeler, I., (2023?) “Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-serie
Multi-decadal trend analysis and forest disturbance assessment of European tree species: concerning signs of a subtle shift
Forest Ecology and Management· 2024DOI
Carmelo Bonannella, Leandro Parente, Sytze de Bruin, Martin Herold
OpenEOcubes; an open-source and lightweight R-based RESTful web service for analyzing earth observation data cubes
Earth Science Informatics· 2024DOI
Brian Pondi, Marius Appel, Edzer Pebesma
"A widely-used eddy covariance gap-filling method creates systematic bias in carbon balance estimates"
Scientific Report· 2023DOI
Henriikka Vekuri, Juha-Pekka Tuovinen, Liisa Kulmala, Dario Papale, Pasi Kolari, Mika Aurela, Tuomas Laurila, Jari Liski & Annalea Lohila
"Impact of land tenure on deforestation control and forest restoration in Brazilian Amazonia"
Environmental Research Letters· 2023DOI
Gilberto Camara4, Rolf Simoes, Heloisa M Ruivo, Pedro R Andrade, Aline C Soterroni, Fernando M Ramos, Rafael G Ramos, Marluce Scarabello, Claudio Almeida, Ieda Sanches
A harmonized Landsat Sentinel-2 (HLS) dataset for benchmarking time series reconstruction methods of vegetation indices
WAGENINGEN UNIVERSITY AND RESEARCH· 2023DOI
Consoli, D., Leal Parente, L., Witjes, M., & Hengl, T. (2023). A harmonized Landsat Sentinel-2 (HLS) dataset for benchmarking time series reconstruction methods of vegetation indices (Version 1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8119407
A Simply Updatable Cloud-based Ensemble Digital Terrain Model
GEOMORPHOMETRY IASI ROMANIA· 2023DOI
Yu-Feng HO; Tomislav Hengl; Leandro Parente
AI technology: what it is and what it’s not, and how it can (potentially) help us solve the climate crisis
· 2023DOI
Hengl, T., Consoli, D., Bagić, M., Brocca, L., & Herold, M. (2023). “AI technology: what it is and what it’s not, and how it can (potentially) help us solve the climate crisis” (v0.1). OpenGeoHub foundation. Published in MLearning.ai;
AmeriFlux BASE data pipeline to support network growth and data sharing
Scientific Data· 2023DOI
Housen Chu, Danielle S. Christianson, You-Wei Cheah, Gilberto Pastorello, Fianna O’Brien, Joshua Geden, Sy-Toan Ngo, Rachel Hollowgrass, Karla Leibowitz, Norman F. Beekwilder, Megha Sandesh, Sigrid Dengel, Stephen W. Chan, André Santos, Kyle Delwiche, Koo
Annual time series of global VIIRS nighttime lights for 2000-2021 at 500-m spatial resolution extrapolated using logistic regression
Open-Earth-Monitor Cyberinfrastructure project· 2023DOI
Tom Hengl
Biomes of the world under climate change scenarios: increasing aridity and higher temperatures lead to significant shifts in natural vegetation
PeerJ· 2023DOI
Carmelo Bonannella​, Tomislav Hengl, Leandro Parente, Sytze de Bruin
Building a community-based open harmonised reference data repository for global crop mapping
PLOS ONE· 2023DOI
Hendrik Boogaard; Arun Kumar Pratihast; Juan Carlos Laso Bayas; Santosh Karanam; Steffen Fritz; Kristof Van Tricht; Jeroen Degerickx; Sven Gilliams
Comparing ground below-canopy and satellite spectral data for an improved and integrated forest phenology monitoring system
Ecological Indicators· 2023DOI
Vaglio Laurin, G., Cotrina-Sanchez, A., Belelli-Marchesini, L., Tomelleri, E., Battipaglia, G., Cocozza, C., Niccoli, F., Kabala, J. P., Gianelle, D., Vescovo, L., Da Ros, L., & Valentini, R. (2024). Comparing ground below-canopy and satellite spectral da
Crop-Type Recognition in Street-level Images with Convolutional Neural Networks
· 2023DOI
Fernando Orduna-cabrera , Marcial Sandoval-Gastelum , Ian MCCALLUM , Linda SEE, Steffen Fritz , Santosh Karanam , Tobias Sturn , Valeria Javalera-Rincon , F. Fernando González-Navarro
Deep learning and automatic reference label harvesting for Sentinel-1 SAR-based rapid tropical dry forest disturbance mapping
Remote Sensing of Environment· 2023DOI
Adugna Mullissa, Johannes Reiche, Martin Herold
EcoDataCube.eu: Analysis-ready open environmental data cube for Europe
RESEARCH SQUARE· 2023DOI
Witjes, M., Parente, L. L., Krizan, J., Antonic, L., & Hengl, T. (2022). EcoDataCube. eu: Analysis-ready open environmental data cube for Europe. PeerJ, in review.
Forest restoration challenges in Brazilian Amazonia
NO· 2023DOI
Camara; Simoes; Ruivo; Andrade; Soterroni; Ramos; Ramos; Scarabello; Almeida; Sanches; Maurano; Coutinho; Esquerdo; Antunes; Venturieri; Adami
G-reqs, a New Model Proposal for Capturing and Managing In Situ Data Requirements: First Results in the Context of the Group on Earth Observations
Remote Sensing· 2023DOI
Joan Maso, Alba Brobia, Marie-Francoise Voidrot, Alaitz Zabala and Ivette Serral
High-precision datasets from monitoring stations based on eddy covariance measurements: what six years of quality evaluation process of ICOS ecosystem stations have to tell
EGU General Assembly 2023, Vienna, Austria· 2023DOI
Sabbatini, S., Nicolini, G., Gielen, B., Op de Beeck, M., Michilsens, F., Iserbyt, A., Loustau, D., Lafont, S., Loubet, B., Canfora, E., Polidori, D., Ribeca, A., and Papale, D.
How textural features can improve SAR-based tropical forest disturbance mapping
International Journal of Applied Earth Observation and Geoinformation· 2023DOI
Balling, J., Herold, M., Reiche, J.
Integrated global assessment of the natural forest carbon potential
Nature· 2023DOI
Lidong Mo, Constantin M Zohner, Peter B Reich, Jingjing Liang, Sergio De Miguel, Gert-Jan Nabuurs, Susanne S Renner, Johan van den Hoogen, Arnan Araza, Martin Herold, et al.
Investigating the Use of Street-Level Imagery and Deep Learning to Produce In-Situ Crop Type Information
Geographies· 2023DOI
Fernando Orduna-cabrera , Marcial Sandoval-Gastelum , Ian MCCALLUM , Linda SEE, Steffen Fritz , Santosh Karanam , Tobias Sturn , Valeria Javalera-Rincon , F. Fernando González-Navarro
Monitoring direct drivers of small-scale tropical forest disturbance in near real-time with Sentinel-1 and -2 data
Remote Sensing of Environment· 2023DOI
Bart Slagter, Johannes Reiche, Diego Marcos, Adugna Mullissa, Etse Lossou, Marielos Peña-Claros, Martin Herold
Open-Earth-Monitor: a cyberinfrastructure bringing together key open source developers in Europe
Open-Earth-Monitor· 2023DOI
Hengl, Tomislav
Paddy rice methane emissions across Monsoon Asia
Remote Sensing of Environment· 2023DOI
Zutao Ouyang, Robert B. Jackson, Gavin McNicol, Etienne Fluet-Chouinard, Benjamin R.K. Runkle, Dario Papale, Sara H. Knox, Sarah Cooley, Kyle B. Delwiche, Sarah Feron, Jeremy Andrew Irvin, Avni Malhotra, Muhammad Muddasir, Simone Sabbatini, Ma. Carmelita
Past decade above-ground biomass change comparisons from four multi-temporal global maps
Remote Sensing of Environment· 2023DOI
Arnan Araza, Martin Herold, Sytze de Bruin, Philippe Ciais, David A. Gibbs, Nancy Harris, Maurizio Santoro, Jean-Pierre Wigneron, Hui Yang, Natalia Mála, Karimon Nesha, Pedro Rodriguez-Veiga, Olga Brovkina, Hugh C.A. Brow
SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies
Scientific Data· 2023DOI
Hamidreza Mosaffa, Paolo Filippucci, Christian Massari, Luca Ciabatta, Luca Brocca
Spatial predictions and uncertainties of forest carbon fluxes for carbon accounting
Scientific Reports· 2023DOI
Arnan Araza, Sytze de Bruin, Lars Hein & Martin Herold
Storm Daniel revealed the fragility of the Mediterranean region
The Innovation Geoscience· 2023DOI
Junliang Qiu, Wei Zhao, Luca Brocca, Paolo Tarolli
StrucNet: a global network for automated vegetation structure monitoring
Remote Sensing in Ecology and Conservation· 2023DOI
Kim Calders, Benjamin Brede, Glenn Newnham, Darius Culvenor, John Armston, Harm Bartholomeus, Anne Griebel, Jodie Hayward, Samuli Junttila, Alvaro Lau, Shaun Levick, Rosalinda Morrone, Niall Origo, Marion Pfeifer, Jan Verbesselt, Martin Herold
The contributions of citizen science to the United Nations sustainable development goals and other international agreements and frameworks
Citizen Science: Theory and Practice· 2023DOI
Fraisl, Dilek, See, Linda, Campbell, Jillian, Danielsen, Finn and Andrianandrasana, Herizo T.
A Downsampling Method Addressing the Modifiable Areal Unit Problem in Remote Sensing
Remote Sensing 14 (2022) 21· 2022DOI
Andrei Mîrț; Johannes Reiche; Jan Verbesselt; Martin Herold
Challenges to Achieving the Commitments of Brazil’s NDC in the Amazon Biome
CEBRI Journal· 2022DOI
Câmara, G., Simões, R., M. Ruivo, H., R. Andrade, P., Scarabello, M. ., Costa, W. ., Ramos, R., Ramos, F., Almeida, . C., Sanches, I., Adami, M., Maurano, L., Soterroni, A., Coutinho, A., Esquerdo, J., Antunes, J., & Venturieri, A.
Earth Observation and Machine Learning as the key technologies to track implementation of the Green Deal: 10 main takeaways
OPEN EARTH MONITOR· 2022DOI
Hengl, T.; Ross, C.; Delconte, V.
Exploring characteristics of national forest inventories for integration with global space-based forest biomass data
Science of the total Environment· 2022DOI
Karimon Nesha; Martin Herold; Veronique De Sy; Sytze de Bruin; Arnan Araza; Natalia Málaga; Javier G.P. Gamarra; Kristell Hergoualc'h; Anssi Pekkarinen; Carla Ramirez; David Morales-Hidalgo; Rebecca Tavani
High frequency land cover classification method for supporting global monitoring
· 2022DOI
Dainius Masiliūnas, Diego Marcos, Nandin-Erdene Tsendbazar, Martin Herold, Jan Verbesselt
Innovative governance, environmental observations and digital solutions in support of the European Green Deal - Open-Earth-Monitor public workshop 2022
Innovative governance, environmental observations and digital solutions in support of the European Green Deal - Open-Earth-Monitor public workshop 2022· 2022DOI
OpenGeoHub
Precision of subnational forest AGB estimates within the Peruvian Amazonia using a global biomass map
International Journal of Applied Earth Observation and Geoinformation 115 (2022)· 2022DOI
Natalia Málaga; Sytze de Bruin; Ronald E. McRoberts; Alexs Arana Olivos; Ricardo de la Cruz Paiva; Patricia Durán Montesinos; Daniela Requena Suarez; Martin Herold
Toward a forest biomass reference measurement system for remote sensing applications
Global Change Biology· 2022DOI
Nicolas Labrière, Stuart J. Davies, Mathias I. Disney, Laura I. Duncanson, Martin Herold, Simon L. Lewis, Oliver L. Phillips, Shaun Quegan, Sassan S. Saatchi, Dmitry G. Schepaschenko, Klaus Scipal, Plinio Sist, Jérôme Chave
Using high-resolution imagery and deep learning to classify land-use following deforestation: a case study in Ethiopia
GIScience & Remote Sensing· 2022DOI
Robert N. Masolele; Veronique De Sy; Diego Marcos; Jan Verbesselt; Fabian Gieseke; Kalkidan Ayele Mulatu; Yitebitu Moges; Heiru Sebrala; Christopher Martius; Martin Herold
Ways forward for Machine Learning to make useful global environmental datasets from legacy observations and measurements
NATURE COMMUNICATIONS· 2022DOI
Nature Communications
Deliverables (15)
Other Results (1)
Periodic Reporting for period 2 - OEMC (Open-Earth-Monitor Cyberinfrastructure)