https://www.forestnavigator.eu/index.html
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ForestNavigator (H2020)
ForestNavigator aims at assessing the climate mitigation potential of European forests and forest-based sectors through modelling of policy pathways, consistent with the best standards of LULUCF reporting, and informing the public authorities on the most suitable approach to forest policy and bioeconomy. To reach its ambitious objectives, ForestNavigator will i) harmonize, integrate and continuously update existing datasets by, including national inventories with new remote sensing data and models ii) start from complex forest and climate models and through emulators build them into operational policy modelling tools, iii) integrate biophysical and socio-economic information, iv) consider EU forests and forest bioeconomy in the broader context of other land use and economic sectors, v) rely on input from policy makers and other stakeholders.
ForestNavigator mira a valutare il potenziale di mitigazione climatica delle foreste e dei settori forestali europei attraverso la modellazione di percorsi politici, coerenti con i migliori standard di rendicontazione LULUCF, e a informare le autorità pubbliche sull'approccio più adatto alla politica forestale e alla bioeconomia. Nell'ambito della modellazione forestale multiscala, il Laboratorio di Modellistica Forestale del CNR è responsabile della simulazione della crescita dinamica delle foreste mediterranee, in presenza di cambiamenti ambientali e di scenari gestionali, mediante il modello forestale 3D-CMCC-FEM.
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Dott. Alessio Collalti
075 5014541
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OptForEU (H2020)
The project OPTimising FORest management decisions for a low-carbon, climate resilient future in Europe (OptFor-EU) will build a Decision Support System (DSS) to provide forest stakeholders and citizens with tailored options for optimising decarbonisation and other Forest Ecosystem Services (FES) across Europe. Based on exploitation of existing data sources, use of novel Essential Forest Decarbonisation Variables and relationships between climate drivers, forest responses and ecosystem services, OptFor-EU has five specific objectives: (1) Provide an improved characterisation of the forest-climate nexus and FES; (2) Utilise end-user focussed process modelling; (3) Empower forest end-users to make informed decisions to enhance forest resilience and decarbonisation; (4) Provide a novel DSS service; and (5) Achieve measurable gains towards the European Green Deal objectives.
Il progetto OPTimising FORest management decisions for a low-carbon, climate resilient future in Europe (OptFor-EU) ha come scopo quello di costruire un sistema di supporto alle decisioni (DSS) per fornire agli stakeholder forestali e ai cittadini, opzioni personalizzate per ottimizzare la decarbonizzazione e altri servizi ecosistemici forestali (FES) in Europa. Il Laboratorio di Modellistica Forestale è responsabile, per il CNR, del WP2 che mira a utilizzare una combinazione di modelli forestali, di superficie terrestre e climatici per quantificare le interazioni foresta-clima e sviluppare una migliore rappresentazione delle pratiche di gestione forestale all'interno dei modelli di superficie terrestre e climatici.
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Dott. Alessio Collalti
075 5014541
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Real time smart irrigation management at multiple stakeholders’ levels (SMARTIES) - PRIMA S2 2019
Duration: March 2020 – February 2023
The project aims to improve farm and irrigation district water use efficiency and farm profitability by developing an operational management system (Web-Gis System) for irrigation scheduling, water allocation and economic water productivity. The SMARTIES system is designed to be used: i) in real time mode, during the irrigation season, to support irrigation strategy for weekly and seasonal forecast; ii) in an off line mode, before the irrigation season, as in interactive simulator of irrigation and crop yield strategy under seasonal forecast conditions, supporting crop and irrigation decision strategy and the irrigation water policies impact.
The WG System is sustained by several tools designed pixel-wise as: numerical soil moisture energy - water balance models, crop model, assimilation of satellite data, estimation in real time of present and future soil water content with daily to seasonal forecast horizons.
The system is being tested in six case studies across Southern Europe and North Africa including Italy, Spain, Morocco, Tunisia and Egypt. The project is carried out by 13 partners (8 from European Union and 5 from North Africa).
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Dott.ssa Francesca De Lorenzi
06 499327560
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HERISH ERASMUS + Project No. 2019 1 IT01 KA202 007440
Cultural and Natural Heritage Integrated System: a multidisciplinary approach to promote sustainable tourism
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0984 841402
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SUPERSCIENCEME – Research is your Re-generation
Notte Europea della Ricerca 2021 - Green Deal
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0984 841423
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0984 841427
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SUPERSCIENCEME – Research is your Re-generation
Notte Europea della Ricerca in Italia - 2022
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0984 841423
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0984 841427
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INNOMED - Innovative options for water resources management in the Mediterranean
Implementazione e utilizzazione di avanzate tecniche di modellazione per quantificare gli effetti fisici ed economici di alternative opzioni di gestione del territorio sul ciclo dell'acqua.
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This email address is being protected from spambots. You need JavaScript enabled to view it.
0984 841464
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SISAS - Studio Integrato per la Sostenibilità Ambientale dei Suoli
Monitoraggio della qualità geochimica dei suoli e delle colyure su di esse insistenti
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This email address is being protected from spambots. You need JavaScript enabled to view it.
0984 841427
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LIFE+ ManFor C.BD. 2010-2015. “Managing Forests for multiple purposes: Carbon, BioDiversity and socio-economic well-being”
Gestioni delle foreste con obiettivi multipli: carbonio, biodiversità e benessere socio-economico
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Development of Integrated Web-Based Land Decision Support System Aiming Towards the Implementation of Policies for Agriculture and Environment
The LANDSUPPORT project aims at developing a web-based completely free, open-access GeoSpatial Decision Support System (S-DSS) devoted to: Support sustainable agriculture and forestry Evaluate trade-off between land uses
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This email address is being protected from spambots. You need JavaScript enabled to view it.
06 499327564
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Towards climate-smart sustainable management of agricultural soils
The objectives are to develop knowledge, tools and an integrated research community to foster climate-smart sustainable agricultural soil management that:allows sustainable food production;sustains soil biodiversity
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0984 841466
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Modelling soil functions and soil threats for mapping soil functions and ecosystem services
Assess, analyze and map soil ecosystem services bundles across European agricultural landscapes, highlighting how soil threats affects the supply of services bundles through adoption of a set of site-specific reference thresholds.
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06 499327564
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Efficient, Eco-Friendly, Sustainable Mediterranean Greenhouse Integrated with Artificial Intelligence, Hi-Tech Automation and Control System - acronym SUSMEDHOUSE
The aim of SusMedHouse is to develop a sustainable greenhouse system to enhance the productivity and decrease consumption of resources through self-learning artificial intelligence (AI) with innovative greenhouse applications. To achieve this aim, following objectives will be realized: (1) understanding growers’ needs and common greenhouse crop requirements; (2) designing necessary conceptual system and sensor network; (3) developing the AI software; (4) developing user interface; (5) developing a decision support system (DSS); (6) developing innovative biodegradable growth media for cultivation; (7) developing new eco-friendly methods to fight pest and pathogens; (8) demonstrating the system integrity and compatibility on a medium scale greenhouse with AI; (9) optimising solar energy via developing Low-E and solar control coatings; (10) controlling nutrient leakage to prevent eutrophication; (11) testing the established smart greenhouse system on an aquaponic and hydroponic setup. To actualise these objectives, a 2000 m2 greenhouse will be built in Turkey with the following novel technologies carrying out experiments on lettuce, tomatoes and pepper cultivation. Machine learning AI will include greenhouse specialised optimization mechanisms and sensory network; DSS providing real time data and expected outcomes for actions, pest and pathogen monitoring, early warning system, condition optimiser algorithms, grid and market connected cost calculator; integrated pest and pathogen management owing to image processing and robotic tools. SusMedHouse will also include sunlight and lighting optimisation with the solar control coatings and agroPV panels, real time biosensor and biodegradable growth media development from circular waste streams to diminish the resources used and boost the efficiency. All these systems will be developed by SusMedHouse Consortium with multidisciplinary approach by an experienced team, which is an adept combination of academics, R&D companies and an end-user. The SusMedHouse Consortium is composed by 7 partners from 6 different countries across Europe and the Mediterranean, grouping the entities (CNR, AR&TeCS as coordinator, Antalya Tarım, WOLA, AVIPE, Fraunhofer ISE, and PROTEUS) who focus exactly on those innovative approaches needed in the development and implementation of SusMedHouse Greenhouse Technologies. Thus, the consortium combines the highest expertise from experienced research organizations and SMEs in the field of development and implementation of innovative technologies applied in the Agriculture field and Greenhouse environment. The idea is to combine the best theoretical and practical expertise available in the field in Europe and the Mediterranean region to achieve optimal outcomes in the project. WEBSITE ADDRESS: https://susmedhouse.eu/
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This email address is being protected from spambots. You need JavaScript enabled to view it.
075 5014540
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