Descrizione del progetto
Telerilevamento e IA per la gestione delle foreste
Gli inventari forestali contano sulla mappatura precisa delle specie arboree, sul volume di legno e sulla valutazione della biomassa. Tuttavia, le metodologie esistenti dipendono dai dati sul campo, un metodo costoso che richiede molto lavoro e fornisce informazioni limitate. Modelli accurati che combinano dati di telerilevamento con l’uso di tecniche di IA forniscono informazioni precise e in tempo reale sulle foreste. Il progetto forecast finanziato dall’UE propone una soluzione per i gestori delle foreste e per le industrie del legno, della cellulosa e della carta che si basa su dati geospaziali e di telerilevamento ottimizzando il supporto decisionale alla loro fornitura di risorse forestali. I sistemi di calibrazione proprietari sono centrali nella soluzione, che si basa su algoritmi avanzati di IA. Il progetto contribuirà a ridurre al minimo le parcelle di campo e a mantenere uno standard elevato di informazioni.
Obiettivo
Accurate mapping of tree species and estimation of wood volume and biomass are important assignments of any forest inventory. However, forestry operations currently rely heavily on field data as a basis for estimating its attributes. This labour-intensive approach provides limited information and has become a costly bottleneck in completing operations. Today, remote sensing data plays a key role to characterize forests. Generation of accurate models combining a huge bunch of data requires the use of advance AI techniques that provides real time information about woods and its resources.
fora has pioneered high-resolution and timely forest inventory services which combine state-of-the-art remote sensing technologies and deep learning to produce operational forest inventories that help improving the efficiency of forest management activities. Whether LiDAR, RADAR, and/or optical imagery, airborne or satellite, these sensors able to cover a large area for intensive sampling without the disadvantages inherent to labour-intensive ground sampling schemes done by field crews. However, each remote sensing solution has its own pros and cons, mainly to operate as stand-alone service.
FORECAST is at the forefront of how geospatial and remote-sensing data can be harnessed to optimize safety, efficiency and productivity of forest operations. Key to FORECAST innovation is the fora proprietary calibration systems based on a double application of AI algorithms.
FORECAST is the solution for forest managers and wood and paper companies, reducing the field plots to a minimum, while maintaining a high quality of information about the state of the forest at the (local) scale of individual plantations. Whether an organisation is concerned with timber, access to mills, recreation or conservation, achieving long term sustainability with an optimal return is of paramount importance for the design and implementation of effective sustainable forest management plans and forest-related policie
Campo scientifico
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- agricultural sciencesagriculture, forestry, and fisheriesforestrysilviculture
- engineering and technologyenvironmental engineeringremote sensing
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradar
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
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Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SMEInst-2018-2020-1
Meccanismo di finanziamento
SME-1 - SME instrument phase 1Coordinatore
42004 Soria
Spagna
L’organizzazione si è definita una PMI (piccola e media impresa) al momento della firma dell’accordo di sovvenzione.