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https://doi.org/10.5194/egusphere-2025-4979
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-4979
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
24 Oct 2025
| 24 Oct 2025
Status: this preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).
The ECOSENSE forest: A distributed sensor and data management system for real-time monitoring of ecosystem processes and stresses
Abstract. Forests provide crucial ecosystem services, but are vulnerable to climate-related physical and biological stresses, such as droughts, pests and pathogens. The rapid climate change currently observed increases the pressure on forest ecosystems, with already drastic consequences, e.g., widespread tree mortality across Central Europe. However, we fall short of understanding underlying process dynamics and their impacts on the Earth system. To better understand and predict forest ecosystem dynamics and the associated energy, carbon and water fluxes, detailed knowledge of ecosystem structure, processes and functioning under constantly varying conditions and across different spatial and temporal scales is needed. The ECOSENSE project brings together engineers, environmental and data scientists to establish novel environmental monitoring approaches and to capture distributed forest carbon and water flux dynamics in space and time with a wide range of established measurement technologies and newly developed sensors. Here, we describe the required infrastructure – called ECOSENSE forest – with regard to physical structures, power supply, communication network and data management, that supports such novel environmental sensor networks. We established a comprehensive monitoring system in this ECOSENSE forest, spanning from below-ground to above-canopy with three large scaffold-towers in different plots. More than 670 commercial and 430 self-built sensors monitor over 90 distinct parameters, fluxes, or processes generating upwards of 4,500 time series that capture soil, tree and atmosphere processes with high spatial and temporal resolution. In particular, our design objective is to provide a stable, flexible and secure forest research infrastructure with power, communication and data management using low-cost and commercially available components that meet the needs of various research disciplines. Our considerations and experiences provide impulses and practical solutions for establishing robust, low-cost distributed field research infrastructures and thus increase data continuity and resilience to disruptions at remote locations. The ECOSENSE forest may thus serve as a blueprint for future projects with similar goals and challenges.
How to cite. Tesch, J., Kühnhammer, K., Wagner, D., Christen, A., Dormann, C., Frey, J., Grote, R., Kattenborn, T., Sulzer, M., Wallrabe, U., Weiler, M., Werner, C., Baghbani, S., Brzozon, J., Comella, L. M., Dedden, L., Dumberger, S., Frey, Y., Gassilloud, M., Gerach, T., Göritz, A., Haberstroh, S., Klüppel, J., Kremer, L., Kreuzwieser, J., Lee, H., Maack, J., Müller, J., Prucker, O., Rajak, S. K., Rühe, J., Rupitsch, S. J., Schack-Kirchner, H., Scharinger, C., Shinde, U., Steinmann, T., Stock, C., and Strack, J.: The ECOSENSE forest: A distributed sensor and data management system for real-time monitoring of ecosystem processes and stresses, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4979, 2025.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Jasmin Tesch
CORRESPONDING AUTHOR
Chair of Hydrology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Kathrin Kühnhammer
CORRESPONDING AUTHOR
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Delon Wagner
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Andreas Christen
Chair of Environmental Meteorology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Carsten Dormann
Chair of Biometry and Environmental System Analysis, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Julian Frey
Chair of Forest Growth and Dendroecology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Rüdiger Grote
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, 82467, Germany
Teja Kattenborn
Chair of Sensor-based Geoinformatics (geosense), Institute of Earth and Environmental Sciences, University of Freiburg, Germany
Markus Sulzer
Chair of Environmental Meteorology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Ulrike Wallrabe
Laboratory for Microactuators, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Markus Weiler
Chair of Hydrology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Christiane Werner
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Samaneh Baghbani
Laboratory for Electrical Instrumentation and Embedded Systems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Julian Brzozon
Chair of Soil Ecology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Laura Maria Comella
Institute of Energy Efficient Mobility, Karlsruhe University of Applied Sciences, Karlsruhe, 76133, Germany
Lea Dedden
Chair of Hydrology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Stefanie Dumberger
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Yasmina Frey
Laboratory for Microactuators, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Matthias Gassilloud
Chair of Sensor-based Geoinformatics (geosense), Institute of Earth and Environmental Sciences, University of Freiburg, Germany
Timo Gerach
Laboratory for the Design of Microsystems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Anna Göritz
Chair of Sensor-based Geoinformatics (geosense), Institute of Earth and Environmental Sciences, University of Freiburg, Germany
Simon Haberstroh
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Johannes Klüppel
Laboratory for the Design of Microsystems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Luis Kremer
Chair of Sensor-based Geoinformatics (geosense), Institute of Earth and Environmental Sciences, University of Freiburg, Germany
Jürgen Kreuzwieser
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Hojin Lee
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Joachim Maack
Chair of Sensor-based Geoinformatics (geosense), Institute of Earth and Environmental Sciences, University of Freiburg, Germany
Julian Müller
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Oswald Prucker
Laboratory for Chemistry & Physics of Interfaces, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Sanam Kumari Rajak
Laboratory for Chemistry & Physics of Interfaces, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Jürgen Rühe
Laboratory for Chemistry & Physics of Interfaces, Department of Microsystems Engineering - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Stefan J. Rupitsch
Laboratory for Electrical Instrumentation and Embedded Systems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Helmer Schack-Kirchner
Chair of Soil Ecology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Christian Scharinger
XR Future Forests Lab, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Uttunga Shinde
Laboratory for the Design of Microsystems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Till Steinmann
Laboratory for Electrical Instrumentation and Embedded Systems - IMTEK, University of Freiburg, Freiburg, 79104, Germany
Clara Stock
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Josef Strack
Chair of Ecosystem Physiology, Institute of Earth and Environmental Sciences, University of Freiburg, Freiburg, 79104, Germany
Short summary
In the ECOSENSE forest, we developed a robust infrastructure for distributed forest sensing. Reliable power supply, stable network connection, and smart data collection systems enable the operation of hundreds of sensors under challenging conditions. By detailing the infrastructure design and implementation, we provide a transferable blueprint for building complex monitoring sites that support high-resolution, long-term ecosystem observations.
In the ECOSENSE forest, we developed a robust infrastructure for distributed forest sensing....
The authors present the design and instrumentation of ECOSENSE forest, a large-scale environmental monitoring infrastructure that aims at studying forest ecosystem dynamics under climate change. The monitoring system incorporates more than 1100 sensors, generating many data to be processed. Such data may be used for archiving, thus enabling the forest state measurements evolution through time. The main contribution is the implementation of a practical framework for using distributed environmental sensor networks that consists of physical structures, dedicated power supply, communication networks and a data management system. This ECOSENSE forest shows the possibility of monitoring large-scale environments with reliability and resilience.
General comments
The authors are first thanked for their contribution. The manuscript is well written, clear, and comprehensive. The instrumentation presented is particularly impressive, both in terms of the number of deployed sensors and the overall system architecture.
While the main contribution of the article is to present the ECOSENSE infrastructure as a blueprint for similar deployments, the conclusion would benefit from further discussion of the actual use of the collected data. In particular, providing examples of scientific analyses, preliminary results, or research questions already addressed (e.g. part 4) using the dataset would strengthen the paper and better illustrate the value of the proposed infrastructure.
Furthermore, I have minor remarks and questions:
1. Data heterogeneity management
The monitoring system integrates a large number of sensors measuring different variables, likely with different acquisition frequencies, units, and possibly data dimensionality. The manuscript would benefit from a clearer explanation of how this data heterogeneity is handled. In particular:
- How are different acquisition frequencies managed or synchronized?
- How are measurement units standardized across sensors?
- Are there procedures for harmonizing data structures before storage or distribution?
2. Data format specification
The manuscript refers to a "standardised format" (L.132) and mentions file access (L.380), but the actual data format used for storage and distribution is not clearly specified, if I am not mistaken. Providing details about the file format (e.g., HDF5, CSV, Zarr, etc.) and the general structure of the datasets would improve reproducibility and usability.
3. Integration of external data sources
External data sources are briefly mentioned, such as LiDAR scans (L.281). Is there other external data sources integrated into the datasets ? If so:
- How are these external datasets incorporated?
- How are they synchronized with in-situ measurements?
- Are they stored within the same data structure?
4. Security considerations
Section 2.5 discusses security measures against potential network attacks.
- Is there any protections against local access threats, from Wi-Fi access points, or LoRaWAN gateways (L.245)?
5. Architecture terminology (Figures 4 and 6)
Figure 4 provides a useful overview of the system architecture, and the consistent color and naming scheme with Figure 6 helps readability.
However, some terminology may be imprecise, it is a difficult task to formalize accurately the overall process.
- The term "2. Detection" may not be fully appropriate. In many contexts, detection refers to extracting information from raw or processed data, whereas this stage appears to correspond to data measurement. The term "Measurement" may therefore be more accurate.
- Some labels are not immediately clear. For instance, examples "Selection, Formats" under "7. Processing" could be clarified. At least those single words are not obvious.
- The association of "Broadcast" with VPN is somewhat confusing (see also L.376). A VPN generally provides a secure point-to-point communication channel rather than a broadcast mechanism. Conceptually, this functionality might fit better under "10. Access."
Specific comments
- Figure 3 should be placed after 2.5 because the network infrastructure (right part) is presented in 2.5 and illustrated in Figure 3.
- Figure 4 "8. Broadcast" is not readable (white font color on light gray background)
- L.373: "NodeRed" instead of "NoteRed" (I think)
- L.234: "prevent" instead of "protect" would be more accurate.
- L.396: "ECOSENSE" instead of "EOCSENSE"