DEAL Cluster
Data for Environmental Analysis and Learning
Welcome to the DEAL cluster, an initiative focused on advancing environmental monitoring and data analysis. Our mission is to foster collaboration, knowledge sharing, and the development of integrated solutions to address pressing environmental challenges. The DEAL cluster was formed in March 2025, and currently includes projects: CiROCCO, EULIAA, UAWOS, MISO, TEMBO Africa and RemoTrees.
The Projects
Aims to establish an end-to-end sensing system comprising a distributed network of cost-effective sensing nodes. These nodes, coupled with advanced data fusion remote sensing and assimilation modeling techniques, are designed to enhance ground observation in desert areas. The project focuses on installing and operating low-cost, stand-alone electronic sensing nodes in under-sampled desert ecosystems in Egypt, Serbia, and Spain. The data collected will support climate change models, dust particle movement studies, renewable energy planning, and ecosystem management services.
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Developing a lidar array capable of autonomously measuring atmospheric wind and temperature from 5 km up to 50 km altitude on a continuous 24/7 basis, over extended periods exceeding one year without maintenance. These compact, efficient, and easily transportable lidar units are powered by wind turbines or solar panels. The data collected will fill existing gaps in atmospheric measurements, enhancing climate models and weather forecasts, and will be integrated into European databases like Copernicus and GEOSS.
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Focuses on developing airborne, contactless hydrometric sensing technology to inform climate change adaptation, flood risk assessment, and management of extreme hydrologic events in remote, hard-to-reach, and poorly monitored rivers. The project aims to establish unmanned aerial system (UAS) hydrometry as a cost-effective alternative to traditional in-situ monitoring, offering high spatial resolution and accuracy. The technology will be demonstrated in various use cases across alpine, Arctic, and tropical regions.
Aims to close Africa’s environmental in situ data gap by deploying low-cost, innovative sensor networks that measure key hydrological variables: rainfall, soil moisture, river flow, and bathymetry at under 10% of current costs. By linking these sensors to value-creating climate services and integrating in situ and satellite data into models, the initiative supports applications in geo-hazards, water management, and agriculture, while ensuring long-term financial sustainability and data sharing through Global Earth Observation System of Systems (GEOSS).
Aims to develop an innovative in-situ forest monitoring system using Internet of Things technology, designed for remote and hard-to-reach areas, with satellite-based data transmission to an interoperable platform. The project will combine novel and existing Earth Observation data with on-the-ground measurements of Essential Climate Variables and other key indicators, exploring interoperability with GEOSS and improving understanding of climate variability impacts on forests. By addressing the scarcity of in-situ data in remote forests, RemoTrees seeks to complement Earth Observation efforts, enhancing monitoring of how climate extremes affect forests, critical ecosystems that absorb significant CO2 (>7 Gt in the last decade) through advanced technological solutions capable of operating under challenging logistical and climatic conditions.
MISO develops an autonomous observation system for monitoring of emissions of CO2 and Methane, the two most important greenhouse gases. The system is modular and is suited for use in hard-to-reach areas such as the Arctic or wetlands. It combines three observing platforms (a static tower-Gas ambient monitor , a static gas flux chamber and a UAV-based observatory using NDIR sensing technologies ) with a cloud platform. The system can be operated remotely , with minimum on-site intervention.
The MISO team has expanded existing technologies: we have improved detection limit and accuracy of an NDIR GHG sensor integrated in the platforms. The static platforms and the drone base are powered by a unique geothermal device. The communication between the three observing platforms and a data cloud uses a combination of Peer2Peer, G4/G5/LTE, LORAWAN and wifi technologies.
To ensure consistent measurements, the observing platforms are optimized for energy efficient autonomous operation. This includes on-platform detection of faults through an optimized Machine Learning calibration. The cloud platform stores model updates and fault detection information together with the raw measurements.
The system is co-developed with stakeholders from academia, monitoring and measurement systems, industry and policy. It is thoroughly documented and has been demonstrated in the Arctic and in Wetland .
The overall goal of SYLVA is to achieve a radical improvement and fill gaps in temporal resolution, timeliness, coverage, and availability of information about aeroallergens and other bioaerosols, which are important indicators and modulators of climate change, affect human and plant health, and play a vital role in ecosystems. SYLVA technological innovations will be accompanied with new infrastructure, distribution and exploitation pathways, and links with stakeholders to ensure technology uptake and sustainability beyond the lifetime of the project.
Join Us in Making a Difference
The DEAL cluster aims to enhance data accessibility and interoperability while promoting the development of innovative environmental monitoring technologies. By combining expertise and resources from CiROCCO, EULIAA, and UAWOS, we are committed to accelerating the translation of research findings into practical applications that support informed decision-making for environmental policy and management.
For more information about our projects or to get involved,
please contact us at kate.zouroufidouiccs.gr