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Digital Analytics and Robotics for Sustainable Forestry

Description du projet

Des robots et l’intelligence artificielle pour la surveillance des forêts

Les forêts sont essentielles à la lutte contre le changement climatique et à la préservation de notre planète. Les exploitants et les organisations forestières de suivi des forêts contribuent à leur croissance, à leur rendement en bois et à leur entretien. Malheureusement, la surveillance de grandes étendues de forêt peut s’avérer difficile et imprécise, ce qui met en péril notre capacité à maintenir la bonne santé des écosystèmes forestiers. Le projet DIGIFOREST, financé par l’UE, présente une solution innovante: l’amélioration de la surveillance des forêts et de la gestion des données grâce à des robots et à l’intelligence artificielle. En utilisant différents robots pour collecter des données spatiales en 3D sur les forêts et sur chaque arbre individuellement, puis en les documentant et en les représentant grâce à l’intelligence artificielle, le projet entend apporter aux exploitants forestiers et aux décideurs un outil sans équivalent.

Objectif

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

Coordinateur

TECHNISCHE UNIVERSITAET MUENCHEN
Contribution nette de l'UE
€ 655 276,23
Adresse
Arcisstrasse 21
80333 Muenchen
Allemagne

Voir sur la carte

Région
Bayern Oberbayern München, Kreisfreie Stadt
Type d’activité
Higher or Secondary Education Establishments
Liens
Autres sources de financement
€ 0,00

Participants (4)

Partenaires (4)