Summary
The ECO-MOSAIC (Ecosystem Monitoring and Scaling for Climate Change Impacts) project develops an open, scalable framework to monitor how climate change alters terrestrial ecosystems across Europe. Building on ESA Climate Change Initiative datasets and other satellite Earth Observation products, the project links Essential Biodiversity Variables and Essential Climate Variables with in-situ monitoring networks and advanced AI models to understand the impact of the climate change extreme event on species distribution. ECO-MOSAIC will generate spatially explicit indicators of ecosystem condition, resilience, exposure, and change at multiple spatial and temporal scales, supporting conservation planning and ambitious climate adaptation policies. The project will co-produce methods and open-source tools for users, ensuring interoperability, transparency, and uptake in policy and practice. Ultimately, ECO-MOSAIC aims to deliver transferable workflow and decision-ready information for scientists, land managers, policy makers worldwide, and other users of ecosystem information across Europe and beyond.
Project Background
ECO-MOSAIC responds to urgent policy and scientific needs at the climate–biodiversity nexus. Policymakers must implement the EU Biodiversity Strategy for 2030 (https://environment.ec.europa.eu/strategy/biodiversity-strategy-2030_en ), the Nature Restoration Law, the European Green Deal, and the Kunming–Montreal Global Biodiversity Framework (https://www.cbd.int/gbf ), all of which require consistent, spatially explicit evidence on ecosystem condition, resilience, and change. However, existing monitoring systems are fragmented, heavily reliant on sparse field data, and often fail to capture rapid, climate-driven shifts in ecosystems across large regions.
Scientifically, it remains challenging to translate heterogeneous data streams – satellite Earth Observation, climate reanalysis, and in-situ biodiversity observations – into robust indicators that can be compared across biomes and time. Key gaps include scalable methods to link Essential Biodiversity Variables and Essential Climate Variables, rigorous uncertainty quantification, and tools to distinguish between natural variability and human- and climate-driven change.
ECO-MOSAIC addresses these challenges by co-developing an open, scalable framework that fuses multi-sensor Earth Observation data, process-based modelling, and advanced AI. The project will generate harmonised, policy-relevant indicators of Species populations, and disturbance, and make them available through interoperable, open-source services. In doing so, ECO-MOSAIC helps bridge the science gap, enabling governments, research agencies, and end users to monitor biodiversity and track progress towards international targets and design more effective climate adaptation and biodiversity conservation strategies across Europe and beyond.
Project aims and objectives
This project is dedicated to advancing the integration of satellite Earth Observation data within situ biodiversity observations to enhance our understanding of climate change impacts on terrestrial species and ecosystems. This project will focus on the technical objectives outlined in the Statement of Work, emphasising using ESA-climate Change Initiative (CCI) datasets and other Earth Observation products to assess the impact of climate change on biodiversity, develop innovative methodological frameworks, and support policy-driven research. Achieving these goals requires a multidisciplinary approach integrating Earth Observation and in situ data, ecosystem modelling, and climate science. A key component of this project is to establish robust methodologies for analysing biodiversity responses through assessing dynamics of Essential Biodiversity Variables to climate variability while ensuring the seamless integration of Earth Observation -derived Essential Climate Variables with biodiversity indicators (e.g., Species distribution). This will involve refining data processing techniques, assessing uncertainties, and improving predictive models
to enhance decision-making. Specifically, this project will leverage key ESA-CCI datasets, including Land Cover, Biomass, Soil Moisture, and Fire, to assess ecosystem responses to climate change extreme events. The project will focus on monitoring the
short-term and medium-term impacts of environmental calamities, such as bark beetle outbreaks and forest fires, on biodiversity as well as long-term responses of the drought resilient species such as Mediterranean pines, depict to persistent pressures i.e. successive dry year. The research will consider both negative consequences and potential adaptive responses within ecosystems. To achieve this, the approach will combine Earth Observation-based analysis with terrestrial monitoring, incorporating citizen science contributions to collect in-situ data. This will enable a more comprehensive understanding of biodiversity shifts in response to historical and ongoing environmental disturbances.
Project plan
ECO-MOSAIC is organised into five tightly connected work packages (WPs) that move from scoping and data preparation to scientific analysis, evaluation, and outreach. The project starts with WP1 Science Requirement Analysis, which identifies knowledge gaps at the climate–biodiversity interface and specifies the technical requirements for integrating Essential Climate Variables and Essential Biodiversity Variables.
WP1 delivers a comprehensive Science Requirements Document that guides all subsequent work.
WP2 Development of the Methodology, Data and Tool Preparation builds an open, cloud-based data and tool repository that adheres to FAIR principles and modern standards (e.g. STAC, ARCO). It compiles and harmonises ESA CCI products, Copernicus data, climate reanalyses, biodiversity records (e.g. GBIF, LUCAS, EVA; https://www.gbif.org/), and other ancillary datasets. Within WP2, modelling workflows and analytical tools are developed, tested, and exposed through interoperable interfaces suitable for large-scale climate–biodiversity analyses.
WP3 Main Scientific Analysis applies these tools in three complementary case studies: (1) European temperate forests, focusing on climate variability, bark beetle outbreaks, fires, and their impacts on forest biodiversity; (2) multi-taxa responses in Norwegian communities; and (3) projected range shifts of key tree species in selected Annex I habitats at the northern and southern fringes of Europe. WP3 combines multi-sensor Earth Observation time series, climate data, process-based models, citizen science inputs, and field measurements at reference sites to generate and validate indicators, leading to high-impact scientific publications.
WP4 Evaluation and Roadmap Report assesses the performance, uncertainties, and user relevance of all products and case studies, providing structured feedback to ESA CCI- Essential Climate Variables teams and compiling a five-year scientific roadmap from 2027 onwards, aligned with ESA’s Earth Observation Science Strategy.Finally,
WP5 Management, Outreach, and Communication coordinates the four partner institutions, ensures the timely delivery of milestones, manages risks and data, and leads communication, stakeholder engagement, and dissemination activities, including training materials and guidelines to support the uptake of ECO-MOSAIC workflows and indicators by the wider climate–biodiversity community.
ECO-MOSAIC will provide harmonised climate–biodiversity datasets and derived indicators designed for reuse by scientists, conservation practitioners, and policy users. Core inputs include ESA Climate Change Initiative (CCI) Essential Climate Variable products (e.g. land cover, biomass, soil moisture, fire, land surface temperature, permafrost), multi-mission Earth Observation data (Sentinel-1/2/3, Landsat archive, Earth Observation campaign data, AIRS), and climate reanalyses and projections (Copernicus ERA5 and CMIP6).
Biodiversity and ecosystem data will comprise species occurrence records (e.g., GBIF), vegetation plot information (European Vegetation Archive), and other monitoring datasets, such as LUCAS and EVA, complemented by field plots and citizen science data in the case studies.
Products will span scales from 10–60 m (Sentinel-2 derived variables and high-resolution maps) up to km-scale CCI climate and land products, with temporal coverage from the 1980s (Landsat) to present, and revisit intervals of days to months depending on the sensor. All inputs will be regrided, rescaled, and quality-filtered to a common spatial and temporal reference grid suitable for pan-European analyses.
Data will be delivered in open, analysis-ready formats (e.g. NetCDF, GeoTIFF/Cloud-Optimised GeoTIFF and STAC/ARCO-compliant collections), with rich metadata, versioning and persistent identifiers to support traceability and FAIR use via a cloud-based repository. A “Technical Note on Data Tailoring” and a “How-to-use” user guide will document processing chains, uncertainty treatment and recommended use cases.
Validation is a core component of ECO-MOSAIC. Dedicated product-validation activities will include uncertainty analysis for each dataset, propagation of errors through rescaling and modelling steps, and cross-comparison with independent reference products and field data for the three case studies.
The ECO-MOSAIC project is led by the University of Twente (ITC). Consortium partners include WirelessInfo, the Norwegian University of Science and Technology(NSNT) and SINTEF.
- Science Leader: Dr Elnaz Neinavaz (ITC)
- Project Manager: Dr Haidi Abdullah (ITC)
- ESA Technical Officer: Dr Sophie Hebden (ESA)
University of Twente, The Netherlands – Project Primer and Work Package Lead for WP1, WP3, and WP5
The faculty of Geo-information Science and Earth observation of the university of Twente (ITC) is a leading institution in geoinformation. In the Academic Ranking of World Universities, ITC has consistently ranked among the global top ten for RS for four consecutive years (2017–2020) and currently stands as the third-best RS Faculty in Europe. With a strong focus on applied research, ITC has successfully managed over 1,100 consultancy and research projects across more than 70 countries since 1950. ITC provides high-quality education and training through its academic programs, including MSc and PhD degrees, as well as short courses and tailor-made training programs
WirelessInfo, Czech Republic – Work Package Lead for WP2
WirelessInfo (WRLS) is a private Czech research institute founded in 2003 that focuses on precision farming, soil protection, waste management, landscape management, and ICT for agriculture. WRLS has a very wide field of activities with a big potential for exploitative research, innovation, and implementation in both the Czech market and the international market. WRLS brings together Small and Medium-sized Enterprises, research and industry, directly involving end users in research and development.
Norwegian University of Science and Technology, Norway – Work Package Lead for WP4
Norwegian University of Science and Technology (NTNU) is Norway’s largest university, with almost 9000 employees and over 40,000 students. Its main profile is in science and technology, a variety of professional study programmes, and great academic breadth, including the humanities, social sciences, economics, edicine, health sciences, educational science, architecture, entrepreneurship, art disciplines and artistic activities. It has participated in over 600 EU Framework Programme projects and has been awarded 42 ERC grants. Research is mainly in science and technology and includes winning the 2014 Nobel prize in neuroscience. It also has a strong ecology group, a centre of excellence between 2013 and 2023 and currently holds three ERC grants in the biology and mathematics departments.
SINTEF, Norway – Contributor
SINTEF Digital institute with Department of Sustainable Communication technologies group for Smart Data focuses on Smart Data management with semantic interoperability and AI driven Environmental digital twins. This is supported through a number of European projects under the Destination Earth umbrella, Green Deal and the Mission Ocean including the integration of biodiversity data and socio-ecological data in combination with climate and weather models.
