Alexander Jacob is the Vice-Head of the Institute for Earth Observation at Eurac Research in Italy and coordinator of the research group Advanced Computing. He is passionate about geographic data and software development since his times as a student of geodesy and geoinformatics in Darmstadt, Germany and Stockholm, Sweden. He is an Italian representative towards the Group on Earth Observation (GEO) for the Data & Knowledge working group as well as one of the co-chairs of the Open Geospatial Consortium (OGC) GeoDataCubes Standards Working Group. He has served as an advisor for the European Space Agency (ESA) and the Joined Research Centre (JRC) of the European Commission (EC) in questions of Earth Observation Data Management and Computing.
- openEO from an idea in a whitepaper to a community standard in the geospatial data processing.
- Regional Earth Observation Foundational Models: Improving Representation of Domain-Specific Patterns
Anne Fouilloux is Chief Technology Officer at LifeWatch ERIC. She has over 20 years of experience in high-performance computing and Earth system science, with her career spanning data-intensive computing and optimisation at CNRS-IDRIS (France), software development at the European Centre for Medium-Range Weather Forecasts (ECMWF, UK), research software engineering at the University of Oslo (Norway), and project leadership at the Nordic e-Infrastructure Collaboration (NeIC). Anne is an active contributor to the Pangeo community and has been championing open-source tools for big data geoscience, particularly efforts to grow and sustain this ecosystem in Europe. She focuses on building scalable, open, and sustainable digital infrastructures, and advocates for approaches such as Discrete Global Grid Systems and cloud-optimised formats like Zarr that remove technical barriers and enable meaningful reuse of environmental data. Her work is driven by the conviction that research infrastructures must serve society and remain accessible to all.
- Pangeo: Openness for Sovereignty, Innovation, and Sustainable Communities
Postdoc at Earth Systems and Global Change, Wageningen University & Research and Global Land Monitoring of Remote Sensing and Geoinformatics of GFZ German Research Centre for Geosciences
- Bridging Data, Methods and User-Uptake in Global Biomass Mapping: An Open Framework for Validation, Estimation and Inter-Comparison
- Understanding the 3D Signatures of Forests Across the Planet with Open EO
Biel is a scientist at Vizzuality dedicated to advancing projects that both mitigate and deepen understanding of environmental and climate crises. He leverages his expertise in Python to acquire, clean, and assess datasets for quality, supporting the successful delivery of Vizzuality’s initiatives. With a strong academic background in environmental science, data science, remote sensing, and GIS from the University of Barcelona, he also brings practical experience from his work in software development at an agrotech company focused on regenerative agriculture.
- Reproducible geospatial data pipelines with Kedro (Python framework)
Carlos Rodriguez-Pardo is a postdoctoral researcher at Politecnico di Milano and the RFF-CMCC European Institute on Economics and the Environment, where he works on deep learning for climate change mitigation as part of the ERC-funded EUNICE project. His current research focuses on foundation models for coupled human–Earth system modeling, multimodal geospatial data harmonisation, and neural methods for climate-economic decision making under uncertainty. He has published in Nature, Nature Scientific Data, Nature Climate Change, TMLR, CVPR, Eurographics, and ACM Transactions on Graphics, among others. He holds a PhD in Computer Science from Universidad Rey Juan Carlos and an MSc in Artificial Intelligence from the University of Edinburgh. He has received the SCIE–Fundación BBVA Young Researcher Award, the CEIG Best PhD Thesis Award, and multiple outstanding reviewer recognitions at CVPR, NeurIPS, ECCV, and AISTATS. He co-convenes the EGU 2026 session on machine learning for carbon cycle science and co-organised the first CMCC AI for Carbon Workshop.
- WorldTensor and TerraNova: Open Data and Foundation Models for the Coupled Human–Earth System
AI mapping of smallholder crop data – Scientific Data Research Highlight (2025).
doi: https://doi.org/10.1038/d44148-025-00280-5
Asamoah Oppong, Z. (2022). AI‑Driven Crop Yield Prediction Models for Smallholder Farmers in Sub‑Saharan Africa. Iconic Research and Engineering Journals, Volume 5 Issue 9.
Becker‑Reshef, I., et al. (2023). Strengthening food security monitoring through satellite‑based crop type and yield estimation. Remote Sensing Environment, 292, 113577.
Geyman et al. (2025). An Africa‑wide agricultural production database to support policy and satellite‑based measurement systems. Scientific Data (Nature).
Gokool, S., Mahomed, M., Brewer, K., Naiken, V., Clulowa, A., Sibanda, M., Mabhaudhi, T. (2024). Crop mapping in smallholder farms using unmanned aerial vehicle imagery and geospatial cloud computing infrastructure. Heliyon, 10 (2024) e26913.
Guo, Z. (2024). From Space to Soil: Advancing Crop Mapping and Ecosystem Insights for Smallholder Agriculture.
Jayne, T.S., Muyanga, M., Wineman, A., et al. (2019). Are medium-scale farms driving agricultural transformation in sub-Saharan Africa? Agricultural Economics, 50:75–95.
https://doi.org/10.1111/agec.12535
Kerner, H., Chaudhari, S., Ghosh, A., Robinson, C., Ahmad, A., Choi, E., Jacobs, N. et al. (2024). Fields of The World: A Machine Learning Benchmark Dataset for Global Agricultural Field Boundary Segmentation. arXiv preprint arXiv:2409.16252.
Lida, K., Rahim, S., Hutber, C., Grau, G., Moss, C., & Douglas, O. (2026). Government AI Readiness Index 2025. Oxford Insights.
Musoni, M., & Adeniyi, D. (2025). How AI can benefit smallholder farmers in Africa: Opportunities for EU‑Africa. ECDPM Discussion Paper No. 396.
Nakalembe, C., et al. (2025). Challenges and opportunities for crop type mapping in smallholder systems of sub‑Saharan Africa. Remote Sensing, 17(2), 412.
Omotoso, A.B., & Omotayo, A.O. (2024). The interplay between agriculture, greenhouse gases, and climate change in Sub-Saharan Africa. Regional Environmental Change, 24, 1 (2024).
https://doi.org/10.1007/s10113-023-02159-3
Potapov, P., Turubanova, S., Hansen, M.C. et al. (2022). Global maps of cropland extent and change show accelerated cropland expansion in the twenty‑first century. Nature Food 3, 19–28 (2022).
https://doi.org/10.1038/s43016-021-00429-z
Rahman, A.N., Kotu, B.H., Tetteh, F.M., Karikari, B., Akinseye, F.M., Ansah, T., Mutungi, C., & Kizito, F. (2024). Editorial: Sustainable intensification of smallholder farming systems in Sub‑Saharan Africa and South Asia. Frontiers in Sustainable Food Systems, 8:1399430.
doi: 10.3389/fsufs.2024.1399430
United Nations Department of Economic and Social Affairs. (2024). World population projections.
UNFCCC (2025, November 15). Ethiopia: Press Briefing on hosting COP 32 in Ethiopia. Belém, Brazil.
Wang, S., Waldner, F., & Lobell, D.B. (2022). Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision. Remote Sensing 14 (22): 5738. doi:10.3390/rs14225738.
WRI Africa (2026). AI Mapping for Small-Scale Farm Transformation.
https://africa.wri.org/initiatives/ai-mapping-small-scale-farm-transformation
- Democratizing Field Boundary Delineation in the Global South with AI.
Clemens Mosig is a researcher at Leipzig University working at the intersection of remote sensing, computer vision, and vegetation mapping. He has co-created the deadtrees.earth initiative. Clemens is a strong advocate of open data, science, and idea sharing. He holds a Bachelor and Master's degree in Computer Science from Freie University Berlin.
- deadtrees.earth - Crowdsourced Drone Data for Global Tree Mortality Maps
- Open Data Under Pressure
Codrina Ilie is a technical geographer, an open source GIS/RS power user, actively working as a project officer to support geospatial data services development at Terrasigna. In her 13 years of activity, Codrina has essentially focused on using open source GIS and RS solutions for data management, processing and visualization. Since 2013, Codrina has been a Charter Member and today serves the community as an Open Source for Geospatial Foundation Board of Directors elected member, within her forth term.
- Leveraging OpenEarthMonitor Cyberinfrastructure data to assess insurance vulnerability in a changing climate
I'm a postdoctoral researcher at the Max Planck Institute for Biogeochemistry in Jena, Germany. Originally coming from a bioinformatics background, I now work on software and data formats making geospatial data like satellite imagery less distorted.
- From Sentinel-2 STAC to DGGS Native Data Cubes with DGGS.jl
Dr. Uta Heiden brings over 20 years of expertise in airborne and spaceborne imaging spectroscopy. Her current work centers on using imaging spectroscopy and multispectral data archives to extract information on soils and soil–vegetation cover, with applications ranging from soil erosion assessment to soil property mapping. A key focus of her research is exploring sensor synergies — especially the integration of imaging spectroscopy — to enable large-scale, frequent monitoring of soil systems. She is a senior scientist at the Remote Sensing Technology Institute of the German Aerospace Center (DLR), and she also serves as Science Coordinator for the hyperspectral DESIS mission and as a member of the EnMAP Science Advisory Group. In recognition of her longstanding contributions to the community, she has been honored with, for example, the prestigious IEEE Senior Member status and she holds the senior scientist status of the German Aerospace Center.
- Opportunities and challenges of mapping soils with EO for large areas
Eirini Trypidaki is a predoctoral Researcher at CREAF and member of the Methods and Applications in Remote Sensing and Geographic Information Systems (GRUMETS) research group.
Her work focuses on the development and refinement of methodologies for high-resolution drought monitoring, with an emphasis on advancing the operational use of environmental data.
This research is closely aligned with the objectives of the Open Earth Monitor (OEMP) project and highlights the practical applications of high-resolution Earth observation in sectors such as agriculture, insurance, and reinsurance.
- Understanding Vegetation–Climate Relationships Using GeoAI: A Spatiotemporal Analysis in the Ebro River Basin
Erin Glen is a GIS Research Associate with Land & Carbon Lab at the World Resources Institute, where she develops and applies geospatial data, remote sensing, and spatial analysis to support forest carbon monitoring, land use, and natural climate solutions. Her work focuses on improving monitoring and decision-support tools for land managers and advancing global analyses of land sector greenhouse gas emissions.
- Global organic soil disturbance and emissions: leveraging Earth observation–based geospatial data within an IPCC framework
Estefania Blanch is the Earth Observation Manager at the Area for the Promotion of the Space Sector of Catalonia (APEC) at the Institute of Space Studies of Catalonia (IEEC), where she supports the implementation of Catalonia’s Space Strategy. Her work focuses on promoting the use of satellite data to address real-world challenges such as water management, agriculture, natural hazards, and environmental monitoring. At the IEEC’s Office for Industrial Services and Promotion, she coordinates activities related to Earth observation, helps define satellite-based services, and fosters collaboration between public institutions, industry, and research. With a background in geophysics (PhD) and space studies (MSc), she works to bring the benefits of space technology closer to society and to strengthen the space sector in Catalonia.
- The role of small satellites in strengthening innovative use caes within the framework of the Catalonia Space Strategy
- Regional Earth Observation Foundational Models: Improving Representation of Domain-Specific Patterns
Felipe S. Campos is a postdoctoral researcher at CREAF working at the interface of biodiversity, ecosystem services and ecological economics. His research uses GIS and remote sensing to investigate spatial patterns of biodiversity and ecosystem services, with a particular focus on indicators, monitoring and the ecological foundations of nature-based solutions. He develops spatial approaches that help link ecological knowledge with conservation research and practice.
- From Earth Observation to Ecosystem Service Indicators: Integrating Biodiversity, Spatial Modelling and Nature-Based Solutions Across Scales
- Regional Earth Observation Foundational Models: Improving Representation of Domain-Specific Patterns
TODO
- S2BIOPHYS: A Global Annual 20 m Dataset of Vegetation Biophysical Properties from Sentinel-2
- Unraveling patterns and drivers of global forest restoration success using remote sensing
Fred Stolle is Deputy Director of Global Nature Watch and Global Forest Watch at the World Resources Institute (WRI), where he has worked since 2003. He is an internationally recognized expert in the use of geospatial data to understand land-use dynamics and their implications for climate change, ecosystems, and sustainable development. His work focuses on quantifying environmental drivers and translating complex spatial data into actionable insights for policymakers, practitioners, and decision-makers worldwide.
Trained in Geographic Information Systems (GIS) and remote sensing, Fred has lived and worked across Latin America, Africa, Asia, Europe, and the United States, bringing a global perspective to environmental monitoring and policy-relevant analysis. His professional experience includes roles with UNEP in Nairobi and collaborations with UNESCO, the World Agroforestry Centre (ICRAF), and the Center for International Forestry Research (CIFOR) in Indonesia. He has also served as an adjunct professor at Johns Hopkins University’s School of Advanced International Studies (SAIS), as lead technical assessor for forest carbon monitoring systems for the World Bank’s BioCarbon Fund, and as a contributor to multiple international working groups on spatial data and environmental monitoring. Fred is based in Washington, DC, and holds an MSc in Biology and a PhD in Geography.
- From Data to information and Policy to Implementation
- Regional Earth Observation Foundational Models: Improving Representation of Domain-Specific Patterns
Gregory Duveiller holds a PhD in agronomical science and biological engineering from the Université catholique of Louvain (UCLouvain), Belgium. After his PhD, he spent 10 years working at the European Commission Joint Research Centre (JRC), in Ispra, Italy. He has specialized in developing methods to combine different satellite remote sensing data streams to better monitor and understand land processes, including crop yield monitoring, land cover change and land-atmosphere interactions. Since 2021 he is a project group leader at the Max Planck Institute for Biogeochemistry in Jena, Germany. His main research aims at improving our understanding of the role of terrestrial ecosystems in the Earth System by using data-driven yet process-based thinking applied to satellite Earth Observation data. A key focus is on exploring the complexity and diversity of terrestrial ecosystems, and how their specific functional properties affect land-atmosphere interactions. Topics explored under this umbrella include: (i) improving estimations of carbon, water and energy fluxes; (ii) studying the role of biodiversity (specifically functional diversity) to improve ecosystem resilience; (iii) exploring the biophysical effects of land use and land management on climate.
- Planet health index: A framework to investigate relationships between the atmosphere, biosphere and sociosphere
- Getting SIF closer to GPP: developing tools towards reaching such goal
- Assessing how changing local forest cover affects diurnal surface temperature across Europe and Africa
- AI for Climate Resilience: From Data to Decisions that Matter
Imane Serbouti received the M.S. degree in GIS and Remote Sensing for Geosciences and Environment and the Ph.D. degree in Geospatial Big Data and Geosciences, both with excellence, from Hassan II University, Casablanca, Morocco. She is currently a researcher at the National Research Council of Italy (CNR). She was previously a postdoctoral researcher at Mohammed VI Polytechnic University (UM6P), where she worked on geospatial urban big data. Her main research interests lie in remote sensing, satellite Earth observation, geospatial data analysis, and GeoAI for applications in environmental monitoring, disaster risk assessment, climate resilience, and sustainable land and water systems.
- Soil-Moisture Memory as a Regulator of Hydrologic Response in the Po River Basin (Italy)
Research technician at the Centre for Ecological Research and Forestry Applications (CREAF) in the research group of Remote Sensing and Geographic Information Systems (GRUMETS).
- How FAIR Is Geospatial Data? An Assessment of OEMC Datasets
- Key biophysical variables for forest monitoring in Catalonia
I am a PhD researcher in geoinformatics at the University of Tartu, focusing on the use of remote sensing and machine learning to monitor landscape processes and support ecosystem conservation and restoration.
- Monitoring herbaceous biomass and restoration of semi-natural grasslands using machine learning on Sentinel-1 and Sentinel-2 imagery
Jaime Gaona was born in Burgos, Spain in 1986. Jaime has a background specialized in hydrology during his Civil Engineering studies from the University of Burgos (2013) and his M.Sc. in Hydraulics and Environment from the Polytechnic University of Valencia (2015).
Jaime holds a PhD supported by an Erasmus Mundus Joint Doctorate scholarship in river Sciences (2019) from Freie Universität Berlin and Universitá Degli Studi di Trento, associated with the Leibniz Institute of Freshwater Ecology (Berlin IGB), focused on characterizing and modeling the groundwater-surface water interactions (hyporheic exchange) using innovative measurement techniques such as FO-DTS and hydrogeophysics directed by Jörg Lewandowski and Alberto Bellin.
He started as postdoc in 2019 to study soil moisture and evaporation in the Spanish National Science Project HUMID devoted to the analysis of Iberian drought based on remote sensing and land surface modelling at Ebro Observatory with Pere Quintana-Seguí, while helping to lecture hydraulics and irrigation systems at the Polytechnic University of Barcelona (2020).
Jaime was from 2021 JCYL-supported researcher at the University of Salamanca, Spain, group of Water Resources led by José Martínez Fernández at the Research Institute of Agrobiotechnology (CIALE), working on the analysis of soil moisture relevance to vegetation responses.
Jaime is currently researcher working in soil moisture analysis at the Hydrology group led by Luca Brocca of the Research Institute for Geo-Hydrological Protection IRPI of the Italian National Research Council in Perugia, Italia. The group focus on evaluation of remote sensing tools for hydrology and related fields, with special attention to soil moisture as key variable mediating the water, matter and energy exchanges in the critical zone.
- Limitations of current operational systems based on remote sensing and models for the characterization fo extreme hydrometeorological events
Joana is a data engineer with a strong background in geospatial tech. Her pursuit to make geospatial information F.A.I.R. has led her to the board of GSDI and to OGC, where she leads relations with the developer community. Committed to advancing the open-source geospatial ecosystem, Joana is a OSGeo board member and project contributor.
Joana is the founder of ByteRoad, a boutique company in the field of Spatial Data Infrastructures. She is also a reviewer for the European Commission, and has been involved in education, teaching the next generation of full-stack developers and data analysts.
- To be FAIR, we're Open! How open Standards can power Earth Observation
Research Group Methods and Applications in Remote Sensing and Geographic Information Systems (GRUMETS) at CREAF
- Key biophysical variables for forest monitoring in Catalonia
Leandro Parente is a senior researcher at OpenGeoHub Foundation with more than 15 years of experience in processing Earth Observation (EO) data and developing Machine Learning (ML) pipelines for producing continental and global maps.
- Accessing global multi-decade Landsat cloud-free time-series in CDSE
- Global monitoring of grassland and livestock: Current status, challenges and next steps
Linda Luck is a researcher at GFZ Helmholtz Centre for Geosciences, specialising in forest structure analysis using terrestrial laser scanning (TLS) and unmanned laser scanning (ULS). Her work focuses on integrating field-based forest inventory with remote sensing data to enable robust, scalable, and transferable forest metrics. She currently works on standardising processing workflows to support cross-site comparability and data sharing. Her work is informed by a multidisciplinary background in environmental and biological sciences.
- Standardising Terrestrial and ULS Laser Scanning Processing for Cross-Site Data Sharing and Applications
- Towards FAIR IoT forest data: from static delivery to a continuous and interoperable data infrastructure
https://www.irpi.cnr.it/en/persona/brocca-luca/
- The 1-km illusion in remote sensing for hydrology
Engineer and data geek. Technologist @ Fondazione Edmund Mach
- Towards FAIR IoT forest data: from static delivery to a continuous and interoperable data infrastructure
I am a Pre-doctoral student in terrestrial ecology at the Autonomous University of Barcelona through the Centre for Ecological Research and Forestry Applications (CREAF) and work within the Remote Sensing and Geographic Information Systems (GRUMETS) research group.
- Ecosystem Functionality of Catalonian Landscapes: Change Assessment of Ecosystem Functional Types (EFTs) Using Sentinel-2 Derived NDVI
Marc Rußwurm is a Junior Research Group Leader of the MEO-lab at the University of Bonn. He was previously Assistant Professor of Machine Learning and Remote Sensing at Wageningen University. His background is in Geodesy and Geoinformation, and he obtained a Ph.D. in Remote Sensing Technology at TU Munich. During his Ph.D., he visited the European Space Agency and the University of Oxford as a participant in the Frontier Development Lab (2018), and conducted research stays at the Obelix Laboratory in Vannes and the Lobell Lab at Stanford. As a postdoctoral researcher, he joined the Environmental Computational Science and Earth Observation Laboratory at EPFL, Switzerland. His research focuses on modern machine learning for Earth observation, with an emphasis on geospatial representation learning and Earth Embeddings. He develops methods that enable robust, transferable analysis of geospatial data and applies them to challenges such as agriculture, species mapping, and marine litter monitoring, with a particular interest in domain shifts and transfer learning in geographic settings.
- Earth Embeddings: Learning “Mental Maps” for Open, Interoperable GeoAI
Dr. Marcin Kluczek is a cloud computing and GeoAI expert serving as the Tech Lead for the EO Algorithms Team at CloudFerro S.A. He specializes in architecting scalable solutions for processing massive satellite constellations, focusing on AI-driven embeddings and foundational models. Marcin combines deep technical leadership with an academic background to push the boundaries of how we analyze Earth Observation data at scale, ensuring that complex algorithms run efficiently in cloud-native environments.
- Satellite-Based Anomaly Detection using GeoAI Embeddings: A Scalable Workflow
Marco Girardello is interested in understanding how Earth's ecosystems are structured and how they are changing across space and time. He uses spaceborne LiDAR and multi-source Earth observation data to map ecosystem-level diversity at global scale, with a focus on translating dense EO data streams into ecologically meaningful products.
- Foundation-model embeddings predict global variation in forest structural diversity
I am a PhD candidate at the Department for Earth Observation, Friedrich Schiller University Jena (Germany). My current research focuses on savanna vegetation structure monitoring using synthetic aperture radar, with particular interests in open-source tools and reproducible research practices. My GitHub, Fosstodon and Bluesky handle is "maawoo". I'm happy to connect and open to new opportunities!
- Comparing Foundation Model Embeddings and Phenology-Informed Feature Engineering for Temporally Consistent Mapping of Savanna Vegetation Structure
Environmental data analyst and geospatial scientist with experience in large-scale datasets, spatial
modelling and Earth Observation. Strong background on EU research projects handling multi-source
data integration, processing and automation of analytical workflows (skilled in Phyton, R and Google
Earth Engine), and producing decision-suport outputs (maps, visual graphs, presentations) for policy
makers, technical groups and general stakeholders.
I am currently working for CREAF as Research Technician in the SEACURE Project, addressing nutrient pollution in Mediterranean river basins through the integration of environmental datasets across multiple administrative and ecological levels. More specifically, my work involves developing terrestrial nutrient budgets at the river basin scale to identify critical pollution hotspots and nutrient flux pathways, as well as producing high-resolution cartographic outputs to support evidence-based decision-making.
I did my master in the University of Córdoba focusing on geomatics and remote sensing techniques applied to forest management, and this work that I am presenting here belongs to the final thesis developed for my masters.
- The impact of adaptive silviculture on the spectral response and drought resilience of Mediterranean pine forests in Spain
- From Earth Observation to Earth System insights
- Bridging Data, Methods and User-Uptake in Global Biomass Mapping: An Open Framework for Validation, Estimation and Inter-Comparison
- Towards a Future-Proof Copernicus Data and Services Landscape?
Dr. Maurizio Santoro received the M.S. degree in Aerospace Engineering from the University "Federico II", Naples, Italy, in 1998, the Lic. Eng. degree from Chalmers University of Technology, Gothenburg, Sweden, in 2001, and the Ph.D. degree from Friedrich Schiller University, Jena, Germany, in 2003. He was a postdoctoral researcher at the Friedrich-Schiller-University, Jena, in 2004 and 2005. Since 2006 he is Senior Scientist at GAMMA Remote Sensing. He is involved as PI and Co-I in several international projects on the use of Earth observation data to characterize land surface parameters at local, regional and global scales. He led the technical development of ESA's BIOMASAR (2008-2012), GlobBiomass (2015-2018) and CCI Biomass (2018-ongoing) AGB mapping algorithms based on Synthetic Aperture Radar (SAR) and Light Detection and Ranging (LiDAR) data. He is the main responsible for the AGB map products of the projects, including their distribution (e.g., through the CCI data portal) and user support. He is a member of Japan Aerospace Exploration Agency (JAXA) Kyoto & Carbon Initiative Science Team.
- Satellite LiDAR Data in Support of Forest Biomass Mapping
Mike Harfoot is an interdisciplinary ecological scientist with over 15 years of experience building models that try to make sense of life on Earth, from individual organisms up to entire ecosystems. He is best known for co-developing the Madingley General Ecosystem Model, one of the first mechanistic models to simulate the full complexity of terrestrial and marine ecosystems, and has contributed to major international biodiversity frameworks including IPBES. He works as a Scientist at Vizzuality and is an Adjunct Professor at Dalhousie University. His recent work includes a high-profile review of AI for nature and a climate risk index for marine biodiversity.
Alongside his research, Mike is the Founder and Chair of OpenNature, a growing coalition of over 20 organisations working to improve how biodiversity knowledge is created and shared. Prior to joining Vizzuality he led ecology and biodiversity modelling projects at UNEP-WCMC.
- Working with and visualizing GeoFoundational AI embeddings
Milutin Milenković is a research scholar in the Novel Data Ecosystems for Sustainability Research Group of the IIASA Advancing Systems Analysis Program. His current research focuses on combining Earth Observation and Citizen Science for monitoring environmental change. He is also a guest lecturer at the Vienna University of Technology, Austria.
- Satellite LiDAR Data in Support of Forest Biomass Mapping
As an engineer, modeler, and data analyst, I have 8+ years of experience in geoinformatics and Earth observation applications for environmental systems. My research focuses on integrating GIS, remote sensing, and data driven modelling approaches to understand hydrological processes, climate variability, and water resource dynamics. Experienced in ArcGIS, QGIS, Python, and R for spatial analysis, geostatistics, and environmental modelling.
Research Interests:
Hydrologic modelling | Geoinformatics & GIS | Climate Dynamics | Earth Observation Hydrology | Flood and Drought Risk Assessment | Machine Learning |
- Satellite Gravity Observations for Scalable Global Precipitation Monitoring
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- High-Resolution Grassland GPP Estimation with Landsat and Sentinel-2
- How FAIR Is Geospatial Data? An Assessment of OEMC Datasets
- From Land Cover Change to Greenhouse Gases: An Open Geospatial Monitoring Framework
https://www.linkedin.com/in/natalia-kolecka-76b18b168/
- From EO Data to Urban Woody Vegetation Structure: A Reproducible Workflow for National-Scale Tree and Shrub Mapping
- Optimizing Representations at Test Time
Pontus Lurcock is a software engineer at Brockmann Consult GmbH., with a strong focus on geodatacubes and analysis-ready earth observation data. He has extensive experience of working at the interface between informatics and geosciences, and holds an MSc in Computer Science and a PhD in Geology.
- EO processes and workflows with xcube
Geoinformation Scientist leveraging AI and satellite technology to map our planet's changing landscape. I transform petabytes of satellite data into actionable insights on agricultural expansion, deforestation, and biodiversity, bridging the gap between advanced algorithms and environmental policy.
My work focuses on developing scalable deep learning models to monitor commodity crops (e.g., oil palm, cocoa, coffee, soy) and assess their environmental impacts, using a combination of radar, optical imagery, and cloud computing.
- High-Resolution Global Maps of Coffee Farms Extent
- Biomazon: A Multimodal Benchmark for Full Vertical Structure and Biomass Modeling in the Amazon Basin
- Regional Earth Observation Foundational Models: Improving Representation of Domain-Specific Patterns
Sajed Sarabandi is a software engineer and junior researcher specializing in remote sensing at the OpenGeoHub Foundation. He holds a Master’s degree in Computer Science from Leiden University.
- Landsat monthly cloud-free complete consistent mosaics 2000-2025
- A Multi-Layer Gap-Filling Pipeline for Continuous Monthly Landsat Data (1997–2025)
Sayan Mandal received his B.Tech. in Computer Science from University of Petroleum and Energy Studies, India, in 2017 and M.Sc. in Computer Science (major: Machine Learning, minor: Visual Computing), with distinction, from Technische Universität Graz, Austria, in 2024. Before joining Masters, he worked in the field of Computer Vision for over 4 years with two leading startups in India. For his M.Sc. thesis, he worked as a Student Project Assistant in FutureWoods Project at ICG, TU Graz, Austria, funded by FFG - Austrian Research Promotion Agency and the Vienna Scientific Cluster supercomputer. He is currently pursuing his Ph.D. degree in Electrical and Computer Engineering from University of Iceland in conjunction with the “AI and ML for Remote Sensing” Simulation and Data Lab, JSC, Forschungszentrum Jülich, Germany. His main research interests include developing robust deep learning models for remote sensing applications, foundation models and exploring AI efficiency, using HPC systems.
- Biomazon: A Multimodal Benchmark for Full Vertical Structure and Biomass Modeling in the Amazon Basin
Sergio Estella is a designer and entrepreneur with over 25 years of experience working at the intersection of data, technology, and environmental impact. He is the co-founder of Vizzuality, a European company that designs digital platforms to make complex scientific data accessible and actionable.
His work focuses on translating Earth Observation data, environmental models, and large-scale datasets into tools that support decision-making across climate, nature, and sustainability challenges. Sergio has led the design of platforms that help detect forest loss, monitor supply chains, map illegal fishing, and explore climate futures.
He has collaborated with organisations such as the United Nations, the World Resources Institute, the World Bank, the European Space Agency, and leading academic institutions, including Cambridge, Stanford, and Yale, helping turn scientific knowledge into operational tools with real-world impact.
- From earth observation to farm decisions: Designing platforms for decision making
Simone Sabbatini has a PhD in Forest Ecology, obtained in 2014 at the DIBAF department of the University of Tuscia, Viterbo, Italy. His background consists in a BSC in Forestry and Environmental Science, and a MSC in Management of Forestry Systems, both held at the University of Florence, Italy. Currently he is a Researcher at the Euro-Mediterranean Center on Climate Change (CMCC), where he is involved in the activities of the ICOS Ecosystem Thematic Center (ETC), dealing with giving support to the ICOS stations concerning eddy covariance measurements, meteorological data collection, data and metadata file submission, as well as contributing to the implementation of new variables for CAL/VAL activities at ICOS stations. He coordinates the processing of FLUXNET sites from China, Japan and South Korea in the FLUXNET Data System Initiative. In addition, he is also supervising the activities of PhD students at the DIBAF.
- The FLUXNET Shuttle: Enabling Access to Globally Distributed Flux Tower Data
Senior Researcher in the Global Land Monitoring group of the section Remote Sensing and GeoInformatics. Research interests: Land Use and Land Cover mapping; Forest monitoring across scales;
Software, methods and tools for reference data collection; Data science and artificial Intelligence; Satellite embeddings and hyperspectral imagery; Instrumentation for in situ forest monitoring. Profile: https://www.gfz.de/en/staff/timothee.stassin/sec14
- FLUM 2024: a global 10 m Forest and other Land Uses Map aligned with FAO definitions
Steffen Fritz is a Principal Research Scholar in the Novel Data Ecosystems for Sustainability (NODES) research group at IIASA. He spearheaded the development of the Geo-Wiki visualization and data collection platform, widely used in global and regional projects addressing land cover, land use, cropland distribution, forest management, and drivers of deforestation, integrating contributions from experts and citizen scientists. Fritz has extensive expertise in geospatial analysis, harmonization, and integration of spatial datasets, including uncertainty analysis, crop type mapping, spatial allocation, and biofuel-related data. He has led numerous high-profile initiatives with budgets exceeding €5 million, including ERC-funded projects and Horizon 2020 initiatives. His research interests include Earth observation, machine learning, artificial intelligence, crowdsourcing, volunteered geographic information, and the application of space and geospatial data to food security, vegetation monitoring, and sustainable land-use practices. He holds an MSc in Geographical Information for Development (University of Durham, UK) and a PhD (University of Leeds, UK), and has authored over 160 peer-reviewed publications.
- Has pasture already peaked in 2000? The first independent global statistical assessment of grassland, livestock association, and change
Tom has more than 25 years of experience as an environmental modeler, data scientist and spatial analyst. Tom has a background in soil mapping and geo-information science (PhD at Wageningen University / ITC). He continuously runs hands-on-R training courses to promote use of Open Source software for spatial analysis / spatial modeling purposes. He is currently the project leader of the Open-Earth-Monitor project (https://doi.org/10.3030/101059548) and Director at the OpenGeoHub foundation. Tom is recipient of the Clarivate Highly Cited Researchers for 2021, 2022, 2023, 2024 and 2025. Several of his paper have received the best paper awards including the "Finding the right pixel size" (https://doi.org/10.1016/j.cageo.2005.11.008), "Soil property and class maps of the conterminous USA" (https://doi.org/10.2136/sssaj2017.04.0122), his articles published in PeerJ are among top 10 most cited of all time; his PLOS One paper (https://doi.org/10.1371/journal.pone.0169748) is listed among the most cited in the field.
- Landsat monthly cloud-free complete consistent mosaics 2000-2025
- Quantification of temporal changes in Earth-Observation-based estimates: examples with soil carbon & above ground biomass
Tristan Grupp is an Agricultural Data Scientist in the Food, Land, and Water Program and Data Lab at the World Resources Institute. He collaborates closely with Land and Carbon Lab. His current research focuses on applying remote sensing and machine learning to monitor deforestation and natural land conversion driven by agricultural supply chains, supporting commodity traceability and corporate sustainability compliance, including under the EU Deforestation Regulation (EUDR). His work spans forest change monitoring, climate adaptation, and the intersections of food systems and natural landscapes. Beyond WRI, Grupp has contributed to research on climate change adaptation tracking in support of national adaptation planning under the UNFCCC, protected area policy evaluation in the EU, and tropical forest dynamics in the Peruvian Amazon. He has presented his work at international venues including AGU, COP, and the UN National Adaptation Planning Conference.
- Democratizing Field Boundary Delineation in the Global South with AI.
Dr. Vaibhav Kumar is a Postdoctoral Research Fellow at CNR-IRPI, Italy, working under the supervision of Dr. Luca Brocca. His research focuses on the integration of satellite observations, reanalysis, and hydrological model data for environmental monitoring, with particular emphasis on flash drought detection, soil moisture dynamics, and hydroclimatic extremes. He received his Ph.D. in Geomatics engineering from National Cheng Kung University, Taiwan. His expertise includes multi-sensor Earth observation, geospatial data harmonization, uncertainty analysis, and machine learning for large-scale environmental applications. His work supports engineering-oriented monitoring frameworks for hazard assessment, early warning, and climate resilience.
- From Surface Drying to Hydrological Response: An Integrated Diagnosis of Flash Droughts across Europe
- From Surface Drying to Hydrological Response: An Integrated Diagnosis of Flash Droughts across Europe
Valentina Premier received in 2022 her Ph.D. degree in Information Engineering and Computer Science at the University of Trento, Trento, Italy, within the Remote Sensing Laboratory and with Eurac Research, Bolzano, Italy, within the Institute for Earth Observation. Previously, she held a Master's in Environmental Engineering in 2016. Her activities focus on snow cover and snow water equivalent retrieval using remote sensing data. She is currently involved in different projects of the group for Mountain Cryosphere, such as SNOWCOP, Snowtinel and Open Earth Monitor.
- Large-scale snow monitoring: multi-mission data integration and scalable processing strategies
Vasile Craciunescu is a researcher with more than 24 years experience, working for the Romanian National Meteorological Administration and Terrasigna, being in charge with the scientific and operational activities related to GIS database design and implementation, deployment of standardized web services, spatial enabled web interfaces, ETL, EO data processing, project management. He received his diploma in cartography and physical geography in 2001. He has a good experience in working and leading national, EU and ESA research projects. In 2006 Vasile started geo-spatial.org (http://geo-spatial.org), a collaborative effort by and for the Romanian community to facilitate the sharing of geospatial knowledge and the discovery and publishing of free geographic datasets and maps. Since 2011 he is the Romanian delegate in the Copernicus User Forum at the European Commission and the technical representative of Meteo Romania at Open Geospatial Consortium. In August 2014 he was elected to the Open Source Geospatial Foundation board of directors. For the last 14 years he has been teaching FOSS4G-based techniques at the Faculty of Geography - University of Bucharest in the first Romanian ICA-OSGeo Lab. Vasile was the chair of the 2019 FOSS4G international conference. From February 2021 he is the Romanian delegate in the Destination Earth Coordination Group and recently was appointed as national expert in the EEA EIONET Land Technical Group.
- Leveraging OpenEarthMonitor Cyberinfrastructure data to assess insurance vulnerability in a changing climate
- Are We Monitoring an Open Earth for a Community, or for a 'Big Bang'?
At OpenGeoHub, Yu Feng supports current and future European Commission-funded and other international and local projects where there is a need to develop solutions for geocomputing with Remote Sensing data, optimize and automate modeling frameworks and deliver scientific outputs.
- Satellite LiDAR Data in Support of Forest Biomass Mapping
Zhengpeng (Frank) Feng is a second-year Ph.D. candidate in the Energy and Environment Group, Department of Computer Science and Technology, at the University of Cambridge. His research interests lie at the intersection of machine learning and earth sciences, with a particular focus on developing self-supervised learning methods in remote sensing.
- TESSERA: A Foundation Model for Label-Efficient and Multi-Modal Earth Observation at Scale
- Working with and visualizing GeoFoundational AI embeddings