idw – Informationsdienst Wissenschaft

Nachrichten, Termine, Experten

Grafik: idw-Logo
Thema Corona

Science Video Project

Share on: 
11/04/2020 11:33

TreeSatAI - Artificial Intelligence with Earth Observation and Multi-Source Geodata

Udo Urban DFKI Kaiserslautern
Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, DFKI

    The goal of the TreeSatAI project is the development of artificial intelligence methods for the monitoring of forests and tree populations at local, regional and global level. The project is funded by the German Federal Ministry of Education and Research (BMBF). Using freely accessible geodata from different sources (remote sensing data, administrative information, social media, mobile apps, monitoring libraries, open image databases) prototypes for deep learning based extraction and classification of tree and stand features for four different use cases in the fields of forest, nature conservation and infrastructure monitoring are developed.

    Remote sensing data from various satellite missions of ESA and NASA, aerial image data as well as geodata on the state of the environment are increasingly available free of charge and in large quantities. At the same time, texts, photos and videos from social media platforms such as Flickr, Twitter or Open Street Map provide access to further information about our environment. However, a manual evaluation of the resulting huge amounts of data would be too time-consuming and labor-intensive.

    The Deep Learning Competence Center of DFKI and the research area Smart Data and Knowledge Services have been developing AI procedures for the analysis of aerial and satellite images for some time now, which enable both local evaluation and global analysis. In TreeSatAI, the scientists intend to use CNNs (Convolutional Neural Networks) as well as specialized LSTM models (Long Short-Term Memory) from the field of Deep Learning to enable the automated temporal analysis of forest areas over a large area and thus support environmental and forest experts. One of the major challenges is the acquisition of sufficient, high-quality training data to train the algorithms and the evaluation of the resulting models by experts from the forest and environmental sector. Therefore, the project will use and combine the different competences of the project partners to meet the numerous challenges of this ambitious project.

    • TU Berlin: Geoinformation in Environmental Planning (Consortium management)
    • TU Berlin: Remote Sensing Image Analysis Group
    • LiveEO GmbH
    • LUP GmbH
    • Vision Impulse GmbH

    01.06.2020 - 31.05.2022

    Funding reference: BMBF 01IS20014D

    Press Contact:
    Christian Heyer
    Head of Corporate Communications DFKI Kaiserslautern
    Phone: +49 631 20575 1710

    Contact for scientific information:

    Dr. Jörn Hees
    Smart Data & Knowledge Services
    Competence Center Deep Learning
    Phone: +49 631 20575 1180

    Criteria of this press release:
    Information technology, Zoology / agricultural and forest sciences
    transregional, national
    Research projects

    A drone ready to take off for field tests

    For download


    Forested areas in the Harz Mountains damaged by drought stress and bark beetles

    For download



    Search / advanced search of the idw archives
    Combination of search terms

    You can combine search terms with and, or and/or not, e.g. Philo not logy.


    You can use brackets to separate combinations from each other, e.g. (Philo not logy) or (Psycho and logy).


    Coherent groups of words will be located as complete phrases if you put them into quotation marks, e.g. “Federal Republic of Germany”.

    Selection criteria

    You can also use the advanced search without entering search terms. It will then follow the criteria you have selected (e.g. country or subject area).

    If you have not selected any criteria in a given category, the entire category will be searched (e.g. all subject areas or all countries).