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Project

Study on the use of UAVs in forest monitoring



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Study on the use of UAVs in forest monitoring

The use of UAV for forest monitoring is of great interest to various forestry-related research institutes on an international level. Due to the high costs and limited resolution of aerial imagery derived from satellite and manned-aircraft platforms as well as costly Laser Scanning acquisition methods, UAV photogrammetry provides a cost-effective alternative and enables institutions to acquire data at a high spatial and temporal data entirely in-house. Although cost-effective, the process of acquiring and processing data, in particular for the production of high quality photogrammetric points and multispectral imagery still requires further research especially when a low-cost system (< 30,000 EUR) is implemented.

Background and Objective

Potential outcomes of study:

  • Tree Geometries (e.g. individual tree height)
  • Automatic Tree stem positioning
  • Tree top position and stem position comparison
  • Gap coverage
  • Cost-effective data acquisition workflow competitive to field methods (also large scale)
  • Enhanced possibilities for long term monitoring (all data sets can be processed in the same way retroactively)
  • Automized workflow for large scale acquisition
  • Field Manual

Approach

At the Lysimeter station in Britz different options of UAV use is tested and the results are compared with terrestrial assessments.

Involved external Thünen-Partners

  • Hochschule für nachhaltige Entwicklung Eberswalde (HNEE)
    (Eberswalde, Deutschland)

Duration

10.2017 - 10.2020

More Information

Project status: finished

Publications

  1. 0

    Krause S, Sanders TGM (2024) European beech spring phenological phase prediction with UAV-derived multispectral indices and machine learning regression. Sci Rep 14:15862, DOI:10.1038/s41598-024-66338-w

    https://literatur.thuenen.de/digbib_extern/dn068474.pdf

  2. 1

    Reder S, Mund J-P, Albert N, Stadelmann C, Miranda L, Waßermann L (2021) Detektion von windgeworfenen Baumstämmen auf UAV-Orthomosaiken mit Hilfe von Neuronalen Netzen. In: FowiTa : Forstwissenschaftliche Tagung - Wald: Wie weiter? ; Book of abstracts, 13. bis 15. September 2021. p 220

  3. 2

    Krause S (2019) Aerial and terrestrial photogrammetric point cloud fusion for intensive forest monitoring. GI Forum 7(2):60-72, DOI:10.1553/giscience2019_02_s60

  4. 3

    Krause S, Strer M, Mund J-P, Sanders TGM (2019) UAV remote sensing data handling: A transition from testing to long-term data acquisition for intensive forest monitoring. J Photogramm Remote Sensing Geoinf Sci 28(39):167-174

  5. 4

    Krause S, Sanders TGM, Mund J-P, Greve K (2019) UAV-based photogrammetric tree height measurement for intensive forest monitoring. Remote Sensing 11(7):758, DOI:10.3390/rs11070758

    https://literatur.thuenen.de/digbib_extern/dn060940.pdf

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