Objective
EFFORTE draws a red line through critical, cost/benefit driving processes, and environmentally concerns of today´s forestry. Starting with efficient fulfilment of various customer demands the red line goes along efficient utilization of Big Data sources, present knowledge and critical new knowledge foreseen as outcomes from this project.
Technical development and mechanization has been a winning concept for high productivity now emphasizing more gentle methods and just in time deliveries to different industry customers. This is possible to reach if new knowledge, improved methods and technical development are combined with better transfer of information and data from different sources (e.g processes, geo data from LiDAR scanning, other conditions such as weather data etc).These Big Data sources have been available for some years, but it is not until recently that hardware, data communication and merging possibilities enable full potential for a revolution of new applications.
In the EFFORTE proposal we have identified three main subjects that have specific importance for efficiency, productivity and environmental concern in forest practice. Two of these implies to increasing crucial knowledge and the third, Big Data applications, combines the new knowledge with high resolution information sources into practice increasing efficiency in forest management and the connected value chains. The main objectives of EFFORTE are: i) To develop scientifically firm and techno-economically feasible methodology to predict trafficability prior to forest operations. ii) To increase forest growth and productivity of tree planting and young stand management iii) To develop, customize and pilot modern ‘Big data’ solutions that will increase productivity and decrease negative environmental impact (e.g. soil, water and reduced fuel consumption). By EFFORTE we expect to make difference in efficiency, productivity and sustainability for a growing Bio-based economy in Europe.
Fields of science
- engineering and technologyenvironmental engineeringecosystem-based managementecological restoration
- natural sciencescomputer and information sciencesdata sciencebig data
- agricultural sciencesagriculture, forestry, and fisheriesforestrysilviculture
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturearboriculture
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
00790 Helsinki
Finland
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Participants (22)
80130 Joensuu
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
77420 Champs Sur Marne
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02020 Metsa
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75183 Uppsala
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01300 Vantaa
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00100 Helsinki
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750 07 Uppsala
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00180 Helsinki
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3003 Bern
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88000 Epinal
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
94704 MAISONS ALFORT CEDEX
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51520 Saint Martin Sur Le Pre
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19104 Brive La Gaillarde
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G66 3UA Glasgow
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
75009 Paris
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851 88 Sundsvall
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114 84 Stockholm
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105 22 Stockholm
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79180 Falun
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FK5 4NQ Larbert
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35189 Vaxjo
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302 31 Halmstad
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.