Project
Title
REGULUS - KI-basierte Verfahren zur Analyse von 4D-Punktwolken zum Aufbau Digitaler Zwillinge am Beispiel von Vegetationsbeständen, Teilprojekt 3
Acronym
TreeDigitalTwins
Start
01.02.2023
End
31.01.2026
Coordinating Institute
Universität Potsdam
Contact
Partner
Universität Potsdam
Hochschule für Nachhaltige Entwicklung Eberswalde
Point Cloud Technology GmbH
Project team ATB
Allocated to research program
Internet
Summary
The aim of the joint project TreeDigitalTwins is to develop innovative AI methods for object recognition and automatic derivation of object parameters in discrete 4D point clouds and to test these methods using the example of relevant inventory parameters for forest, tree and other woody biomass stocks in two real world laboratories (a.k.a. living labs). In a transdisciplinary innovation group, the consortium is developing and testing digital tools in the form of adaptive machine learning algorithms, which can further contribute to the monitoring of Germany’s climate neutrality by 2045, as well as to achieve SDG 13 and 15. The AI methods developed in the project make direct use of the recorded 3D data, which will allow the developed technology, via adaptation of the training data, to be transferred to other applications. The ATBs research goal within the project is, based on the biomass stocks modelled using 4D point clouds by the example of agroforestry systems, to develop methods for balancing the carbon stored in the soil and vegetation and to apply these to the modelling of forests. As part of the transdisciplinary joint project, the ATB takes over the work on the calculation of carbon budgets, divided into above-ground and underground stocks. Based on the monitoring of the examined agroforestry systems over several years, the model will be set up in a way that connections between total carbon, site parameters, vegetation and management can be revealed and analysed in order to allow the development of recommendations for practice. Additionally, the ATB will test the developed system in real world laboratories together with practice partners from the fields of agroforestry and forestry, and supports the improvement of an automatized derivation of economic and ecological management parameters.
Funding
Bundesministerium für Bildung und Forschung (BMBF)
Funding agency
Projektträger Jülich (PtJ)
Grant agreement number
033L305C
Funding framework
BMBF-Fördermaßnahme Regionale Innovationsgruppen für eine klimaschützende Wald- und Holzwirtschaft (REGULUS)