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Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data

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Innovations for Community Services (I4CS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1876))

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Abstract

Climate crisis and correlating prolonged, more intense periods of drought threaten tree health in cities and forests. In consequence, arborists and foresters suffer from increasing workloads and, in the best case, a consistent but often declining workforce. To optimise workflows and increase productivity, we propose a novel open-source end-to-end approach that generates helpful information and improves task planning of those who care for trees in and around cities. Our approach is based on RGB and multispectral UAV data, which is used to create tree inventories of city parks and forests and to deduce tree vitality assessments through statistical indices and Deep Learning. Due to EU restrictions regarding flying drones in urban areas, we will also use multispectral satellite data and fifteen soil moisture sensors to extend our tree vitality-related basis of data. Furthermore, Bamberg already has a georeferenced tree cadastre of around 15,000 solitary trees in the city area, which is also used to generate helpful information. All mentioned data is then joined and visualised in an interactive web application allowing arborists and foresters to generate individual and flexible evaluations, thereby improving daily task planning.

Special thanks to our cooperation partner Smart City Bamberg. The project BaKIM is supported by Kommunal? Digital! funding of the Bavarian Ministry for Digital Affairs. Project funding period: 01.01.2022 - 31.03.2024.

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Notes

  1. 1.

    https://github.com/OpenDroneMap/WebODM.

  2. 2.

    https://www.agisoft.com/.

  3. 3.

    https://dash.plotly.com/.

  4. 4.

    https://geopandas.org/en/stable/.

  5. 5.

    https://plotly.com/python/.

  6. 6.

    https://github.com/consbio/mbtileserver.

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Authors and Affiliations

  1. University of Bamberg, Cognitive Systems Group, 96049, Bamberg, Germany

    Jonas Troles, Richard Nieding & Ute Schmid

  2. TU Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany

    Sonia Simons

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  1. Jonas Troles
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  2. Richard Nieding
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  4. Ute Schmid
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Correspondence to Jonas Troles .

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Editors and Affiliations

  1. University of Bamberg, Bamberg, Germany

    Udo R. Krieger

  2. Deutsche Telekom Technology and Innovation, Darmstadt, Germany

    Gerald Eichler

  3. University of Applied Sciences Jena, Jena, Germany

    Christian Erfurth

  4. University of Hagen, Hagen, Germany

    Günter Fahrnberger

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Troles, J., Nieding, R., Simons, S., Schmid, U. (2023). Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data. In: Krieger, U.R., Eichler, G., Erfurth, C., Fahrnberger, G. (eds) Innovations for Community Services. I4CS 2023. Communications in Computer and Information Science, vol 1876. Springer, Cham. https://doi.org/10.1007/978-3-031-40852-6_6

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  • DOI: https://doi.org/10.1007/978-3-031-40852-6_6

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