Open-Earth-Monitor Global Workshop 2026

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.

Research technician at the Centre for Ecological Research and Forestry Applications (CREAF). The research presented here was developed as part of previous work at Ubotica Technologies.

Am a PhD student at the University of Saarland ,working on reforestation and carbon offset monitoring

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.

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

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.

Hi! I'm Carlos, a Biologist and Data Engineer with experience spanning genomics, microscopy and satellite multidimensional image analysis, cellular biology modelling, and web development. I currently work as a Senior Data Engineer at the Swiss Data Science Center at EPFL, where I focus on building tools and pipelines for scientific data. I'm passionate about learning across disciplines and am a frequent hackathon participant; there's nothing better than building something unexpected with extraordinary people in 48 hours.

Check out my GH -> github.com/caviri

​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​

Chunsheng Wang is a Ph.D. candidate at the International Institute for Earth System Science, Nanjing University, China. His research primarily focuses on the intersection of Earth Observation, GeoAI, and global biogeochemical cycles.
Specifically, he leverages multi-source remote sensing data and machine learning algorithms to map large-scale forest ecosystem functioning, monitor litterfall dynamics, and model soil respiration. His goal is to reduce uncertainties in traditional meteorological proxies and provide scalable data infrastructure for next-generation Earth System Models. His most recent breakthrough in evaluating global forest litterfall dynamics and its biogeochemical coupling has been published in the prestigious journal Remote Sensing of Environment.

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.

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.

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.

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.

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.

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.

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.

TODO

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.

I am a Phd student in the University of Barcelona. My research focus is about applying the deep learning algorithms and remote sensing data to conduct the crop yield prediction. I really hope that I could have a tremendous communication with you excellent scholars.

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.

Research technician at the Centre for Ecological Research and Forestry Applications (CREAF) in the research group of Remote Sensing and Geographic Information Systems (GRUMETS).

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.

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.

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.

Research Group Methods and Applications in Remote Sensing and Geographic Information Systems (GRUMETS) at CREAF

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.

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.

A Ph.D. candidate in Forest Management, focusing on forest restoration and ecosystem services in vulnerable regions, as well as extreme climate events and their interrelationships. Committed to providing useful recommendations to government policymakers.

https://www.irpi.cnr.it/en/persona/brocca-luca/

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.

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.

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.

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.

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, Bluesky and LinkedIn handle is "maawoo". I'm happy to connect and open to new opportunities!

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.

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.

Fourth-year PhD candidate specializing in Artificial Intelligence, Computer Vision, and Data Science applied to Smart Agriculture and Precision Farming. Experienced in developing AI-driven preprocessing and modeling pipelines for early disease and pest detection using drone and proximal sensing data.

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 |

Junior Researcher at National Research and Innovation Agency of Republic of Indonesia specializing in Remote Sensing applications

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https://www.linkedin.com/in/natalia-kolecka-76b18b168/

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

PhD student at the University of Coimbra, Portugal. I am a geospatial scientist specializing in advanced Earth Observation with a core focus on Synthetic Aperture Radar (SAR) applications. I am the author of the novel Normalized Radar Burn Ratio (NRBR) index, a significant contribution to SAR-based burned area mapping. My research extensively leverages multi-sensor data fusion, integrating SAR and optical time series with machine and deep learning for detecting burned areas, deforestation, forest degradation, and other land cover changes. A skilled developer of open-source software and proficient in geocomputation with Python, R, and Google Earth Engine.

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.