DEVINE: Smart Monitoring & Decision Support for Vineyard-Forest Integration
Summary
This solution presents a scalable, data-driven system that seamlessly integrates environmental monitoring, biodiversity assessments, and digital analytics to evaluate and optimize the ecological benefits of vineyard-forest alternation. By leveraging a combination of in-field sensors, remote sensing technologies, and advanced digital platforms, this approach aims to provide actionable insights into vineyard health. The ultimate goal is to enhance climate resilience, promote biodiversity, and improve pest resistance.
This solution introduces a scalable, data-driven system that integrates environmental monitoring, biodiversity assessments, and digital analytics to evaluate and optimize the ecological benefits of vineyard-forest alternation. By leveraging a combination of in-field sensors, remote sensing, and digital platforms, the approach aims to deliver actionable insights on vineyard health, to enhance climate resilience, biodiversity, and pest resistance
This solution introduces a scalable, data-driven system that integrates environmental monitoring, biodiversity assessments, and digital analytics to evaluate and optimize the ecological benefits of vineyard-forest alternation. By leveraging a combination of in-field sensors, remote sensing, and digital platforms, the approach aims to deliver actionable insights on vineyard health, to enhance climate resilience, biodiversity, and pest resistance
Foreseen impact
The primary benefit of this solution is its provision of robust scientific evidence on the ecological and agronomic value of integrating forests and vineyards in coastal Mediterranean regions. Through continuous environmental monitoring and systematic assessments of biodiversity, soil health, and pest dynamics, it offers quantitative insights into the conditions under which vineyard-forest alternation provides significant advantages—and where its impact may be limited. This data-driven approach empowers local vineyard managers to make informed, site-specific decisions, fostering the development of resilient and sustainable agro-ecosystems. Additionally, the evidence generated will serve as a baseline for future research in other climatic zones and with different crop types, thereby broadening the approach's applicability.
Ultimately, this project enhances our understanding of agro-ecological dynamics and supports EU objectives related to climate adaptation, biodiversity conservation, carbon farming, and sustainable land use.
Other Impact Area: Expected Outcome:
1. Climate change adaptation: Temperature buffering up to 1–2°C in forest-edge plots, mitigating
vine stress
2. Disease prevention: Lower risk of powdery mildew and fungal outbreaks through early
micro-climate alerts
3. Biodiversity support: Biodiversity indicators (insects, birds) correlated with vineyard
health
4. Water & soil management: Insights into forest impact on soil moisture retention and erosion
risks
5. Agro-ecological transition: Scalable model for digital monitoring of forest-vineyard agro-
ecology across the MED region
6. Capacity-building: Transferable tools, co-creation workshops, and guides for other
wineries or cooperatives
7. Sustainability agriculture: Reduced chemical input through targeted interventions based on
real-time data
Ultimately, this project enhances our understanding of agro-ecological dynamics and supports EU objectives related to climate adaptation, biodiversity conservation, carbon farming, and sustainable land use.
Other Impact Area: Expected Outcome:
1. Climate change adaptation: Temperature buffering up to 1–2°C in forest-edge plots, mitigating
vine stress
2. Disease prevention: Lower risk of powdery mildew and fungal outbreaks through early
micro-climate alerts
3. Biodiversity support: Biodiversity indicators (insects, birds) correlated with vineyard
health
4. Water & soil management: Insights into forest impact on soil moisture retention and erosion
risks
5. Agro-ecological transition: Scalable model for digital monitoring of forest-vineyard agro-
ecology across the MED region
6. Capacity-building: Transferable tools, co-creation workshops, and guides for other
wineries or cooperatives
7. Sustainability agriculture: Reduced chemical input through targeted interventions based on
real-time data
About the solver
Eurecat (www.eurecat.org) is the leading technology centre in Catalonia and the second largest private R&D organization in Southern Europe. With over 800 professionals and 160 R&D projects ongoing, Eurecat serves more than 1,600 companies across Europe in sectors such as industry, health, mobility, and agriculture.
This proposal will be led by the Applied Artificial Intelligence Unit, specialised in predictive modelling and decisison support tools, sensor data fusion and time-series forecasting, Earth Observation analytics, and AI for sustainable agriculture and climate resilience.
Eurecat has coordinated the Horizon 2020 project VITIGEOSS, which focused on improving vineyard management through the integration of diverse data sources such as remote sensing, in-field sensors, expert assessments, and historical records. VITIGEOSS addressed key challenges including water management, phenology and yield prediction, crop status, erosion risk, disease pressure, and the multi-objective optimization of sustainability outcomes. Eurecat is also actively involved in carbon farming initiatives, particularly those using Earth Observation (EO) tools to assess soil carbon stocks, fluxes, and moisture dynamics. The extensive experience and technical capabilities gained through these projects will be leveraged in this new initiative to build a novel, evidence-based framework for evaluating and optimizing vineyard-forest synergies.
References:
https://doi.org/10.3390/microorganisms11010073
https://doi.org/10.3233/faia240447
This proposal will be led by the Applied Artificial Intelligence Unit, specialised in predictive modelling and decisison support tools, sensor data fusion and time-series forecasting, Earth Observation analytics, and AI for sustainable agriculture and climate resilience.
Eurecat has coordinated the Horizon 2020 project VITIGEOSS, which focused on improving vineyard management through the integration of diverse data sources such as remote sensing, in-field sensors, expert assessments, and historical records. VITIGEOSS addressed key challenges including water management, phenology and yield prediction, crop status, erosion risk, disease pressure, and the multi-objective optimization of sustainability outcomes. Eurecat is also actively involved in carbon farming initiatives, particularly those using Earth Observation (EO) tools to assess soil carbon stocks, fluxes, and moisture dynamics. The extensive experience and technical capabilities gained through these projects will be leveraged in this new initiative to build a novel, evidence-based framework for evaluating and optimizing vineyard-forest synergies.
References:
https://doi.org/10.3390/microorganisms11010073
https://doi.org/10.3233/faia240447
Indicative budget/Phases
Phase 1: Co-design and planning (M0–M6) – €30,000
Site assessment, baseline surveys, requirements gathering, stakeholder workshops, indicators framework, pilot zone mapping.
Phase 2: System Deployment and data acquisition (M6–M18) – €100,000
Sensor network installation, biodiversity and soil monitoring setup, development of the MVP digital platform.
Phase 3: Data analysis, AI and dashboard development & Optimization (M18–M30) – €50,000
Data fusion, ML model training, continuous environmental and ecological monitoring, data integration, and adaptive management trials.
Phase 4: Validation, Scale-Up & Dissemination (M30–M36) – €30,000
Evaluation, expansion to additional plots, stakeholder training, dissemination of results and lessons learned.
Total estimated budget: €210,000
Site assessment, baseline surveys, requirements gathering, stakeholder workshops, indicators framework, pilot zone mapping.
Phase 2: System Deployment and data acquisition (M6–M18) – €100,000
Sensor network installation, biodiversity and soil monitoring setup, development of the MVP digital platform.
Phase 3: Data analysis, AI and dashboard development & Optimization (M18–M30) – €50,000
Data fusion, ML model training, continuous environmental and ecological monitoring, data integration, and adaptive management trials.
Phase 4: Validation, Scale-Up & Dissemination (M30–M36) – €30,000
Evaluation, expansion to additional plots, stakeholder training, dissemination of results and lessons learned.
Total estimated budget: €210,000