Terrestrial laser scanning (LiDAR) and photogrammetry are a recent innovation in spatial information data acquisition, which allows geological outcrops to be digitally captured with unprecedented resolution and accuracy. With point precisions and spacing of the order of a few centimetres, an enhanced quantitative element can now be added to geological fieldwork and analysis, opening up new lines of investigation at a variety of scales in all areas of field-based geology. Integration with metric imagery allows 3D photorealistic models to be created for interpretation, visualization and education.
The studied pillow lavas belong to the Middle Volcano-Sedimentary Formation in Western Srednogorie magmatic region. More than ten lava flows of this type have been identified.
3D models provide the opportunity to draw conclusions about the conditions of formation of aqueous flows. One of the factors controlling the growth of the pillow lavas is cooling rate. This can be determined through the analysis and measurements of the thickness and distinctiveness of the quenched (peripheral) rims of every individual lava lobes. Well-defined and distinct rims indicate relatively rapid cooling rates. The morphology and size of separate pillows largely depend on the basins slope angle on which the lava flowed. Their morphology is also influenced by the effusion rate and lava viscosity. The formation of large and rounded pillow obes is typical for moderate slope angles.
The application of terrestrial laser scanning (LiDAR) and photogrammetry enables the precise and detailed digital capture of geological outcrops, significantly enhancing field-based geological studies. In the case of pillow lavas from the Middle Volcano-Sedimentary Formation in the western Srednogorie magmatic region, these technologies allow for the creation of 3D photorealistic models, which aid in interpreting the conditions under which the lavas formed. Key factors influencing the growth and morphology of pillow lavas include cooling rates, slope angles, effusion rates, and viscosity. Rapid cooling produces well-defined quenched rims, while moderate slopes favor the development of large, rounded pillow lobes. These insights provide a deeper understanding of the dynamics of subaqueous lava flows and their formation processes.
How to cite: Velev, S.: LiDAR and photogrammetry technology and its application in paleovolcanic reconstructions of pillow lavas. A case study from Western Srednogorie, Bulgaria., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3067, https://doi.org/10.5194/egusphere-egu25-3067, 2025.
The high costs associated with traditional marine research instruments remain a significant barrier to conducting detailed studies, limiting the granularity and availability of oceanographic data. This directly affects the analysis of complex phenomena such as the impacts of human activities and climate change on coastal zones, which are particularly vulnerable to sea level variations, flash floods, and storm surges. These events, capable of causing irreversible damage, demand real-time monitoring with high spatial resolution to understand their evolution and mitigate their impacts. Furthermore, large-scale monitoring of marine species is crucial to better understand their behavior and distribution areas, providing valuable information for the conservation and management of marine ecosystems.
To address these limitations, we propose the development of a low-cost, robust, precise, and easy-to-implement instrumentation, ideal for citizen science projects. Our approach is based on a versatile, low-power data acquisition module built around the STM32L microcontroller. This module includes ports for connecting various sensors, as well as remote data transmission, geolocation, and memory storage capabilities. Its versatile design makes it suitable for a wide range of applications.
This work presents two innovative applications of this technology. The first innovation is a low-cost tide gauge based on ultrasonic sensors, designed to accurately measure water levels in seas and rivers. This device can integrate with early warning systems, facilitating the monitoring of changes in water levels and providing fundamental data to assess the impacts of climate change on marine ecosystems and coastal communities. The second is a new tracking device (TAG) for marine fauna, designed to gather key information about distribution areas, habitat use, and species behavior in relation to the physical and biogeochemical characteristics of the water column. This TAG incorporates, among other features, a multispectral sensor that enables the study of water quality and composition, as well as the monitoring of Photosynthetically Active Radiation (PAR) at different depths.
How to cite: Martinez-Osuna, J. F., Piermattei, V., Valentini, R., Renzi, F., Coppini, G., and Marcelli, M.: Development of Low-Cost Instrumentation for Comprehensive Global Ocean Monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3082, https://doi.org/10.5194/egusphere-egu25-3082, 2025.
The study of climate-relevant processes in the atmosphere using airborne platforms is an important contribution to understanding our environment. The deployment of remote sensing instruments on aircraft or balloons requires powerful computer systems for data acquisition and instrument control. The ongoing trend towards further miniaturisation of instruments, with increasingly complex measurement tasks and higher data rates for use over longer flight durations, requires a new generation of control and processing units. These units must be significantly reduced in mass, volume and power consumption. In addition, a shift in data management from storage and post-processing to real-time data processing is required to reduce the increasing amounts of data and to transmit them to ground stations.
Based on years of experience with the GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) instrument and its current miniaturised version, GLORIA-Lite, a modular and reconfigurable data acquisition and processing platform has been developed. This platform is specifically designed to meet the demanding requirements of future long-duration flights in harsh environments, with significant optimisations in weight, volume and power consumption. Using state-of-the-art multi-processor system-on-chip (MPSoC) modules, the platform enables real-time data processing while significantly reducing the need for data storage or transmission. Redundancy in hardware and software using the multiple processor cores, together with a supervisor circuit, makes the platform ready for harsh environments. Thanks to its compact form factor, the ruggedised and fully reprogrammable hardware is adaptable to a wide range of applications, further enhancing its versatility and potential for use in various scientific and technological missions.
This presentation will show the prototype of the new processing platform, which will be used together with the GLORIA-Lite instrument during an upcoming balloon campaign. First processing steps and performance analysis will be presented.
How to cite: Schardt, G., Neubert, T., Rongen, H., Zimmermann, E., Gulde, T., Kretschmer, E., Maucher, G., Ungermann, J., Preusse, P., Riese, M., and Natour, G.: Next generation modular processing system for miniaturized remote sensing instruments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4350, https://doi.org/10.5194/egusphere-egu25-4350, 2025.
Traditional coastal and marine monitoring methods are often costly and resource-intensive. In order to make observations more affordable and accessible to a wider range of users, the global collaborative initiative ’Solutions for Cost-effective Ocean Observation Platform’ (SCOOP) was designed. SCOOP aims to connect cost-efficient device developers, data managers, data collectors and users (scientists, researchers, citizen scientists…) to encourage collaboration and enhance the collection and sharing of marine data. SCOOP is an open-access web-platform (https://scoop-ocean.org/) providing access to a comprehensive catalogue of low-cost sensors and emerging technologies, and a series of documentation and expertise for users to help them optimize their data collection and management practices. SCOOP wants to ensure that collected data adheres to FAIR (Findability, Accessibility, Interoperability, Reusability) principles, facilitating its integration into global data infrastructures. SCOOP was endorsed by the UN Decade of Ocean Science for Sustainable Development in 2024 and is supported by developments in several European and global initiatives (EMODnet, JERICO, GOOS, Synchro and CoastPredict).
A direct example of the potential is provided by the EU-funded LandSeaLot project running since 2024 until 2028. LandSeaLots main objective is to make big steps in closing observation gaps in the land-sea interface, focusing on river deltas. By integrating in situ, model, and Earth Observation (EO) data, LandSeaLot connects key communities and initiatives such as Copernicus, ESA, EEA, GEOSS, EMODnet, and the European Digital Twin of the Ocean. The project focuses on improving observation capabilities, reducing gaps between models and observations, and enhancing data integration from sensors, satellites, and models. A key component of the project is the deployment of low-cost sensors, guided by citizen scientists through networks like TransEurope Marinas. These sensors will be tested in the LandSeaLot Integration Labs (LILs) across strategically selected regions across Europe which have diverse catchment, tidal, and meteorological conditions. These LILs will integrate improved observation techniques, providing data for tackling societal challenges such as carbon fluxes, plastic transfer, nutrient impacts, eutrophication, biodiversity conservation, and climate change adaptation. To support international data interoperability and make the data FAIR, LandSeaLot will analyse the deployment protocols, as well as data and metadata models, and have close communication with the developers for adjustments at the source. With input from cost-effective devices developers, users and data managers, and with LandSeaLot results, SCOOP will be further implemented to promote and democratise the use of cost-effective sensors and devices in oceanography and beyond.
How to cite: Thijsse, P., Krijger, T., Schaap, D., Breviere, E., Gorringe, P., and Novellino, A.: Closing coastal and marine observation gaps thanks to cost-effective solutions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6061, https://doi.org/10.5194/egusphere-egu25-6061, 2025.
The advancement of low-cost instrumentation is a critical development to ensure the longevity of ocean observing systems and the sustainability of marine environmental studies. This topic represents one of the most innovative trends in contemporary oceanographic research, aligning with the 2030 Agenda and supporting the objectives of the Global Ocean Observing System (GOOS).
These instruments must be developed with a focus on modularity to serve diverse purposes, including vertical profiling, stand-alone systems, and deployment on various platforms such as buoys, Voluntary Observing Ships, and underwater vehicles. The accessibility of affordable technologies enables the establishment of extensive observational networks, facilitating the study of marine physical and biogeochemical processes through an integrated approach combining in situ measurements, predictive modeling, and remote sensing data.
This study introduces newly developed low-cost sensors and probes designed to measure key oceanographic parameters, including temperature, conductivity, chlorophyll a, and Chromophoric Dissolved Organic Matter (CDOM) fluorescence. These developments build upon the electronic redesign of the T-FLAP and subsequent technologies created within the LOSEM framework (e.g., Marcelli et al., 2015; Piermattei et al., 2018; Marcelli et al., 2021). These instruments underwent rigorous testing during multiple oceanographic surveys conducted in the Mediterranean Sea, yielding valuable insights into their performance and potential for large-scale deployment in marine research.
How to cite: Marcelli, M. and Madonia, A.: Development of a modular probe to measure CTD and Chlorophyll a fluorescence for multipurpose oceanographic applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10313, https://doi.org/10.5194/egusphere-egu25-10313, 2025.
Optimizing soil management practices in vineyards is essential for enhancing grapevine resilience under climate change conditions. This study, funded by the Italian PNRR AGRITECH project, exploits low-cost sensors (TreeTalkers) to evaluate the effects of different soil management practices on sap flow density and crop yield across the annual growth cycle, particularly under heat stress conditions, defined as temperatures exceeding 35°C. Real-time sensors allowed monitoring of physiological and environmental parameters in two plots of a controlled vineyard environment, comparing conventional tillage vs no-tillage with spontaneous cover crops used as mulch. Data were analyzed based on temperature thresholds and branch position. Results from the TreeTalkers are presented into a visualization platform and indicate a significant correlation between soil management practices and sap flow density at high temperatures, highlighting the benefits of no-tillage and mulching in mitigating the effects of heat stress and enhancing grapevine resilience against heat waves, an increasingly pressing issue in the Mediterranean region. Furthermore, no significant differences in sap flow density or yield were observed between lower and upper branches, suggesting uniform physiological performance across plant structures. This study highlights the importance of integrating real-time low-cost technologies to promote sustainable viticulture and broader Earth observation applications.
How to cite: Pizzileo, G., Beltramino, S., Nuzzo, A., Scardigno, V., and Chiriacò, M. V.: Soil management and branch position influence wine grape physiology: insights from TreeTalkers data on sap flow, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5591, https://doi.org/10.5194/egusphere-egu25-5591, 2025.
Plant phenology, the study of seasonal events in plants' life cycles such as budburst, flowering onset, leaf-out, fruit ripening, and senescence, is intrinsically linked to climatic conditions and plays a crucial role in ecosystem processes like carbon and nutrient cycling. Due to its ecological importance, many countries have established phenological monitoring networks based on systematic protocols. However, declining volunteer participation in recent decades has raised concerns about the continuity of these invaluable datasets.
Advancements in technology, machine learning, and smartphone accessibility have spurred the development of plant identification apps. These apps enable users to identify plant species without prior botanical knowledge, generating vast datasets of plant occurrences.
This study investigates the potential of applying machine learning to citizen science-derived plant image data for phenological monitoring. By utilizing a pre-trained deep learning model, we extracted relevant image features and classified 39 species-specific phenostages for nine common plant species in Germany using a Support Vector Machine (SVM) classifier. Our model achieved an impressive overall accuracy of 96%, enabling the automated annotation of over 600,000 plant occurrence images from the Flora Incognita app into corresponding phenological stages.
With this approach, not only did we capture additional fine-granular phenostages, such as flower bud and unripe fruit stages, which are less commonly resolved in traditional phenological network datasets, but we also observed the interannual variability of each phenostage across different years. This demonstrates the feasibility of integrating opportunistic citizen science data into phenological monitoring schemes. By addressing the challenges posed by declining volunteer participation, this method significantly enhances the temporal and spatial resolution of phenological datasets, offering innovative opportunities for phenology monitoring and ecological research.
How to cite: Katal, N., Rzanny, M., Tautenhahn, S., Mäder, P., Wittich, H. C., Boho, D., and Wäldchen, J.: Automating Phenological Stage Detection from Citizen Science Images for Plant Phenology Monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9921, https://doi.org/10.5194/egusphere-egu25-9921, 2025.
Efficient monitoring of crop health and growth dynamics is essential for sustainable agricultural practices, particularly in small-scale farming systems. The Crop Talker represents a breakthrough in precision agriculture as a multifunctional, low-cost Internet of Things (IoT) device. Integrating advanced sensing technologies, it provides comprehensive ecophysiological insights.
Key features include a 28-band spectrometer covering the 400–900 nm range for assessing physiological parameters such as nitrogen content, chlorophyll levels, and nutrient deficiencies. Additionally, the Crop Talker incorporates an 8×8-pixel Lidar Time-of-Flight (ToF) sensor to deliver real-time crop height measurements, augmented by RGB imaging from a 2 MP camera for visual assessments. Onboard environmental sensors for air temperature and humidity complement the system, enabling holistic crop monitoring. Data streaming is facilitated through a 4G NB-IoT connection, ensuring seamless integration with remote analytical platforms.
This innovative device is designed to empower smallholder farmers by delivering actionable insights through an affordable and robust monitoring tool. The Crop Talker bridges the gap between traditional farming practices and modern digital agriculture, contributing to enhanced crop management and resource efficiency.
How to cite: Coppola, V., Renzi, F., Tagliacarne, F., and Valentini, R.: Crop Talker: An Innovative IoT Solution for Multispectral and Structural Monitoring in Small-Scale Agriculture, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11464, https://doi.org/10.5194/egusphere-egu25-11464, 2025.
The ability to analyze and visualize (near) real-time data is crucial for addressing the challenges posed by climate change in agriculture. This work presents a data visualization system for TreeTalker sensors, funded by the Italian PNRR AGRITECH project, which monitors sap flow density and environmental parameters in vineyards. By providing user-friendly access to sensor data, the system enhances decision-making in soil management and grapevine physiology studies.
Featuring an intuitive web-based interface, the platform processes raw sensor outputs into interactive dashboards, allowing users to explore the effects of soil management practices, such as conventional tillage versus no-tillage with mulching, on grapevine resilience under heat stress. Key functionalities include dynamic environmental filtering, comparative plot analyses, and the ability to assess branch-specific physiological responses. Additionally, the system supports temporal tracking of sap flow variations across the growing season.
By converting complex datasets into actionable insights, the system enables researchers and/or vineyard managers to adopt data-driven approaches for sustainable viticulture. This tool demonstrates the potential of low-cost, scalable technologies and advanced visualization techniques to promote sustainable practices in agriculture, with broader applicability beyond viticulture.
How to cite: Nuzzo, A., Scardigno, V., Beltramino, S., Chiriacò, M. V., and Pizzileo, G.: A visualization platform for TreeTalkers data: supporting sustainable vineyard practices, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11676, https://doi.org/10.5194/egusphere-egu25-11676, 2025.
The development of efficient and cost-effective instruments for marine monitoring is crucial for advancing the collection of oceanographic data. This paper introduces a novel, low-cost, multipurpose oceanographic drifter-buoy designed to provide reliable, high-resolution data acquisition in both coastal and offshore environments. Engineered to enhance marine observations while maintaining affordability, the drifter achieves an optimal balance between cost and functionality by utilizing readily available components.
The drifter features a spherical body equipped with a solar panel to recharge its battery pack, enabling sustainable and long-term operations. It incorporates water temperature and turbidity sensors, with data acquisition and processing managed by an ARM® Cortex®-M0+ microcontroller. Position tracking is achieved through GNSS technology, ensuring precise geolocation.
To ensure reliable communication, the drifter is equipped with dual systems: LoRa technology for nearshore data transmission via gateways and Globalstar satellite communication for offshore data transmission. Its modular design further allows the integration of additional sensors, supporting a wide range of applications.
The dual communication system guarantees uninterrupted data transmission to the server regardless of the drifter’s position. All acquired data will be visualized and made freely available for download via the European Marine Observation and Data Network (EMODnet). Furthermore, these measurements will support environmental monitoring and the validation of numerical models to simulate coastal physical and biological processes at high spatial and temporal resolution.
With its dual communication system, solar-powered design, robust data acquisition capabilities, and cost-efficiency, this drifter-buoy represents a versatile, accessible, and sustainable tool for oceanographic monitoring and coastal observation systems.
How to cite: Madonia, N., Martinez Osuna, J. F., Renzi, F., Coppola, V., and Marcelli, M.: Dual-Transmission Oceanographic Buoy : A Low-Cost Solution for Accessible Coastal Monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15337, https://doi.org/10.5194/egusphere-egu25-15337, 2025.
Environmental monitoring is essential in enhancing our understanding of natural ecosystems functioning, addressing effective responses to the challenges posed by climate change, pollution and biodiversity loss. The Internet of Things technology (IoT) has significantly improved observing capabilities, enabling continuous and real-time data collection, even from remote locations, thereby extending the spatial and temporal coverage of environmental monitoring systems. A major challenge still lies in acquiring in situ optical data, which are essential for improving assessments of primary production rates as well as of marine food web dynamics, carbon cycling processes and ecosystem resilience.
Featuring high-quality components, modularity and low power consumption, Tetraspec technology, developed by Nature 4.0, is a 28-channels spectrometer that operates over a range of 410 nm to 940 nm and includes measurements of Photosynthetically Active Radiation (PAR) and Near-Infrared (NIR). Tetraspec is a low-cost, portable and accurate system capable of acquiring a great amount of data for remote sensing and numerical models validation, being easily integrated with various acquisition systems.
This work presents the results of the Tetraspec's laboratory and in situ calibration, detailing its optical characteristics, operational capabilities and applications in both terrestrial and marine environments, through the comparison with reference standard instruments.
How to cite: Madonia, A., Marcelli, M., Renzi, F., Coppola, V., and Valentini, R.: Tetraspec: a new low-cost spectrometer for ecosystem monitoring applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15462, https://doi.org/10.5194/egusphere-egu25-15462, 2025.
The need for comprehensive and sustained coastal oceanographic monitoring has grown as climate change, pollution, and human activities increasingly impact marine ecosystems. Traditional monitoring systems, while highly accurate and reliable, are often prohibitively expensive, limiting their accessibility to resource-constrained regions and organizations. Low-cost/open-source (LoCOs) and do-it-yourself (DIY) initiatives have emerged as promising alternatives, leveraging accessible materials, open-source technology, and community engagement to democratize data collection.
In this presentation, we explore the challenges, opportunities and lessons learnt associated with such initiatives through several examples in the Western Mediterranean Sea and Mozambique coastal waters. In those regions, and for the last 10 years, oceanographic field campaigns, coastal monitoring networks and citizen science initiatives have been launched using DIY and LoCos devices measuring waves, sea level, surface velocities, water temperature and bathy-topographies.
The experience gained during this decade has given us enough elements to discuss challenges involved with this type of technology. This includes ensuring data accuracy and standardization, system durability in harsh marine environments, and overcoming technical knowledge barriers among non-specialist users. Also, this technology opens new opportunities, including fostering citizen science, enabling localized and high-resolution monitoring, and promoting capacity-building in underserved regions. Finally, we will discuss up to what extent low-cost/open-source and DIY solutions have the potential to revolutionize coastal monitoring, offering scalable and sustainable pathways for managing and conserving marine environments.
How to cite: Herrada, A., Puigdefàbregas, J., Jordà, G., Loyola, E., Grifoll, M., Calvillo, B., Villalonga, J., and Gomis, D.: Challenges, Opportunities and Lessons learnt of Low-Cost Open-Source and DIY Initiatives in Coastal Oceanography, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15736, https://doi.org/10.5194/egusphere-egu25-15736, 2025.
As the Internet of Things (IoT) continues to grow, efficient and reliable communication methods are essential for enabling widespread connectivity, particularly in remote and resource-constrained environments. LoRa, with its low power consumption and long-range capabilities, has become a cornerstone of IoT communication. The LoRaWAN protocol extends this functionality by enabling devices to transmit data globally through internet-connected gateways. These gateways aggregate data packets from nearby devices and forward them to centralized servers.
However, traditional LoRaWAN gateways face significant limitations. They are often cost-prohibitive, require constant internet connectivity, and lack advanced data processing capabilities, making them unsuitable for deployment in areas with unreliable or no cellular coverage. These limitations hinder the adoption of LoRaWAN in scenarios such as environmental monitoring and rural IoT networks.
To address these challenges, we developed a low-cost, energy-efficient edge-computing LoRaWAN gateway using embedded systems such as Raspberry Pi 0. Unlike conventional gateways, these edge-computing gateways locally process incoming data, enabling intelligent features such as optimized transmission, data buffering during network outages, and adaptive communication strategies. Additionally, these gateways can be configured to operate independently of cellular networks by utilizing satellite connectivity, further enhancing their usability in remote or off-grid applications.
Preliminary testing demonstrates that these gateways consume up to one-third of the power required by traditional gateways while maintaining reliable data transmission. This substantial reduction in power consumption extends operational lifespans and reduces deployment costs. The ability to process and optimize data locally also improves network efficiency, ensuring timely and reliable communication even under challenging conditions.
This innovation provides a scalable, cost-effective solution for IoT connectivity in remote and underserved regions. By addressing the limitations of conventional gateways, these edge-computing gateways enhance the feasibility of deploying IoT networks in scenarios where traditional infrastructure is impractical or unavailable. The broader implications of this work include improved access to IoT technologies for applications such as environmental monitoring and agriculture, ultimately expanding the reach and impact of IoT systems worldwide.
How to cite: Tagliacarne, F., Valentini, R., Renzi, F., and Coppola, V.: Design and Implementation of a Low-Cost Edge-Computing Gateway for LoRaWAN Networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19116, https://doi.org/10.5194/egusphere-egu25-19116, 2025.
Integrated multidisciplinary ocean observations are critical for understanding ocean processes and supporting robust climate- and ocean-related forecasts, which inform sustainable fisheries management, adaptation strategies that reduce risk, and increased coastal resilience. However, subsurface oceanographic and biogeochemical data is scarce in coastal, shelf, and boundary regions due to the challenges of deploying traditional free-drifting ocean observing platforms in these dynamic environments.
Coastal areas are vital for fishing. Therefore, not only do fishing activities coincide with spatio-temporal ocean data gaps, but fishing vessels serve as platforms for a range of oceanographic instruments, and many types of fishing gear already profile the water column. By eliminating the two largest cost components of ocean observing (the platform and deployment of that platform), innovative sensors can gather valuable subsurface data along the ride at a fraction of the cost. An example of this approach is given by the Moana project, in which a cost-effective smart sensor was deployed on fishing gear to automatically download a thermal profile even on vessels with limited power and electronics. Approximately 250 vessels reversed the coastal data gaps created by the Argo program’s success in the open oceans and demonstrated substantial error-reducing capabilities in high-resolution regional ocean models. Similarly, a compact ferrybox-type style flow-through system is used in Portugal to continuously measure temperature, salinity, chlorophyll, Dissolved Oxygen (DO), pH, Oxidation-Reduction Potential (ORP), and turbidity.
This approach is intrinsically inclusive as cost-effective sensors increase accessibility in historically underserved regions and non-traditional stakeholders are empowered to improve sustainability, profitability, and resilience in their own communities. Data from the Environmental Monitors on Lobster Traps and Large Trawlers (eMOLT) Program is used in the American lobster (Homarus americanus) stock assessment and improves forecasts for US Coast Guard search and rescue operations. The Moana Project provided analyses and ocean forecasts of coastal circulation, marine heatwaves, and connectivity to New Zealand’s seafood industry and other stakeholders. The AdriFOOS (Adriatic Fishery and Oceanography Observing System) Program is one of the longest-running programs to use fishing boats for the collection of scientifically-useful datasets. Fishers directly benefit from these data streams as exemplified by the Smart Fisheries Network (SFiN) led by Kyushu University (Japan), which assimilates CTD and ADCP data from over 200 vessels into coastal ocean models that enable participating fishers to operate both more safely and efficiently. Sensors have additionally been installed on a range of artisanal and industrial vessels across Ghana, The Bahamas, Tanzania, the Bering Sea, and Australia.
To maximize these benefits and democratize ocean observation, the Fishing Vessel Ocean Observing Network (FVON) is an emerging network within the Global Ocean Observing System that coordinates common standards for technology and deployment, establishes best practices, standardizes data flows, and facilitates observation uptake across programs. Through these activities, FVON seeks to achieve its mission: to foster collaborative fishing vessel-based observations, improve ocean predictions and forecasting, promote sustainable fishing practices, and facilitate a data-driven blue economy.
How to cite: Gorringe, P., Van Vranken, C., Cusack, C., Piecho-Santos, A. M., Martinelli, M., Castro Muniain, C., Moustahfid, H., Roughan, M., and Jakoboski, J.: Fishing Vessel Ocean Observing Network: An Emerging Collaborative Global Network, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19284, https://doi.org/10.5194/egusphere-egu25-19284, 2025.
Quantifying ecosystem services (ES) is essential for evaluating the sustainability of agricultural systems,
particularly in agroecological contexts where practices such as reduced tillage, cover cropping, and crop
diversification aim to enhance soil health, biodiversity, and carbon storage. However, current methods for ES
assessment often rely on expensive, labor-intensive, or destructive sampling approaches, limiting their
accessibility and scalability across both research and practical land management contexts. To address this
gap, we present a novel, low-cost soil box system designed for real-time, multi-parameter monitoring of
ecosystem services in agricultural soils.
The soil box integrates a network of advanced yet cost-effective sensors capable of capturing physical (e.g.
moisture content, temperature), chemical (e.g. N-P-K, SOC, TOC), and biological indicators (e.g. microbial
activity) in real time. Technologies such as microbial biosensors, CO₂ flux sensors, NIR spectroscopy, and
ATP detectors enable continuous, non-destructive measurements across multiple soil layers. Its modular
design allows for scalable deployment across experimental plots, long-term monitoring trials, and on-farm
applications, making it highly versatile for both scientific research and practical land management for
farmers.
The ability to capture a diverse range of ES indicators in situ also reduces the need for costly external
laboratory analyses, minimizing logistical barriers often associated with large-scale monitoring efforts.
Therefore, the soil box system has the potential to revolutionize how ecosystem services are measured and
understood in agricultural systems. Its real-time, high-resolution data can inform both sustainable
agricultural practices and scientific research, providing robust evidence of agroecological benefits for soil
health, carbon sequestration, and biodiversity conservation. This aligns directly with the objectives of the
European Green Deal and CAP reforms, offering a scalable, evidence-based tool for assessing the impact of
agricultural practices on ecosystem health, climate resilience, and long-term productivity.
Keywords: agroecology, ecosystem services, soil monitoring, low-cost technology, carbon storage, real-time data,
sustainable agriculture, participatory research.
How to cite: Valentini, R., Cecchinato, N., Castaldi, S., Chiriaco, M. V., Coppola, V., and Renzi, F.: Advancing Ecosystem Service Quantification with a Low-Cost Soil Box Technology forAgroecological Systems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19999, https://doi.org/10.5194/egusphere-egu25-19999, 2025.
