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Digital Analytics and Robotics for Sustainable Forestry

Objective

What if we could create a revolution in spatial data acquisition, organization and analysis and give forestry operators and enterprises up-to-date, tangible information about the status of their forests down to the individual tree? We believe this would improve their oversight by allowing more accurate growth modelling of forest stands and precise predictions of timber yields. It would remove the uncertainty of when thinning operations are needed or where there are trees which are ready for harvest. It could also enable operators to automatically plan where their staff or equipment should be deployed. With capable (semi-)autonomous harvesting, operators eventually automating the full process.

It could also better quantify a forest's carbon sequestration - with low uncertainty per-tree carbon estimates. Precise measures of crown volume and tree diameters would improve the granularity of carbon credit schemes. This could inform national governments and policy makers when deciding policy on initiatives such as carbon offsets and carbon farming.

In DIGIFOREST we propose to create such an ecosystem by developing a team of heterogeneous robots to collect and update this raw 3D spatial representations, building large scale forest maps and feeding them to machine learning and spatial AI to semantically segment and label the trees and also the terrain. Our robot team will be diverse: we will use both rugged field robots as well as more experimental vehicles. Most ambitious of all is the intention to (semi-)automate a lightweight harvester for sustainable selective logging.

Progress in this project will be demonstrated with an ambitious series of field trials. With the clear engagement of forestry and industrial companies, commercial pathways are readily available.

A 1:15 video summarizing the overall project ambitions and consortium can be viewed here:
https://tinyurl.com/digiforest

Coordinator

TECHNISCHE UNIVERSITAET MUENCHEN
Net EU contribution
€ 655 276,23
Address
Arcisstrasse 21
80333 Muenchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Non-EU contribution
€ 0,00

Participants (4)

NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU
Norway
Net EU contribution
€ 463 163,75
Address
Hogskoleringen 1
7491 Trondheim

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Region
Norge Trøndelag Trøndelag
Activity type
Higher or Secondary Education Establishments
Non-EU contribution
€ 0,00
RHEINISCHE FRIEDRICH-WILHELMS-UNIVERSITAT BONN
Germany
Net EU contribution
€ 507 955,00
Address
Regina Pacis Weg 3
53113 Bonn

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Region
Nordrhein-Westfalen Köln Bonn, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
Non-EU contribution
€ 0,00
PREFOR OY
Finland
Net EU contribution
€ 621 304,25
Address
Pieni Roobertinkatu 9
00130 Helsinki

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Manner-Suomi Helsinki-Uusimaa Helsinki-Uusimaa
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Non-EU contribution
€ 266 273,25
MOOG BV
Netherlands
Net EU contribution
€ 151 375,00
Address
Pesetaweg 53
2153PJ Nieuw Vennep

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Region
West-Nederland Noord-Holland Groot-Amsterdam
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Non-EU contribution
€ 64 875,00