Project description DEENESFRITPL Remote sensing and AI for forest management Forest inventories count on the precise mapping of tree species, wood volume and biomass assessment. However, existing methodologies depend on field data which is a costly and labour-intensive method providing limited information. Accurate models combining remote sensing data with the use of AI techniques deliver precise and real-time information about forests. The EU-funded forecast project proposes a solution for forest managers, wood, and pulp and paper industries that relies on geospatial and remote sensing data optimising the decision support on their supply of forest resources. The proprietary calibration systems are central in the solution that relies on advanced AI algorithms. The project will help reduce field plots to a minimum and maintain a high standard of information. Show the project objective Hide the project objective Objective 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 Fields of science engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technologyagricultural sciencesagriculture, forestry, and fisheriesforestrysilvicultureengineering and technologyenvironmental engineeringremote sensingengineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradarengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors Programme(s) H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs Main Programme H2020-EU.3. - PRIORITY 'Societal challenges H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies Topic(s) EIC-SMEInst-2018-2020 - SME instrument Call for proposal H2020-EIC-SMEInst-2018-2020 See other projects for this call Sub call H2020-SMEInst-2018-2020-1 Funding Scheme SME-1 - SME instrument phase 1 Coordinator FORA FOREST TECHNOLOGIES SLL Net EU contribution € 50 000,00 Address C/oreste camarca, 4 4b 42004 Soria Spain See on map Region Centro (ES) Castilla y León Soria Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 21 429,00
