Landschaftslabor Demmin

Das Landschaftslabor DEMMIN der Arbeitsgruppe Geoökologie (in Zusammenarbeit mit dem Geoforschungszentrum Potsdam und dem Deutschen Zentrum für Luft- und Raumfahrt in Neustrelitz) im Nordosten von Mecklenburg-Vorpommern im Raum zwischen Demmin, Jarmen und Greifswald dient zunächst der langzeitlichen, automatischen Überwachung von agrarmeteorologischen Umweltparametern in einem landwirtschaftlich intensiv genutzten Untersuchungsgebiet. Vielfältige Fragestellungen werden bearbeitet, z.B.:

  • Flächenhafte Analyse agrarmeteorologischer Größen für landwirtschaftliche Untersuchungen und Modellierungen
  • Aufbau und Pflege eines Open-Data-Portals zur Einbindung in die landwirtschaftliche Praxis
  • Kalibrierung und Validierung von Fernerkundungsdaten durch in-situ Messungen
  • Verknüpfung von Feldmessungen mit Fernerkundungsdaten zum Upscaling und flächenhafter Umweltmodellierung

Aus naturräumlich-geographischer Sicht ist das Testfeld DEMMIN heterogen. Die heutige Oberflächengestalt der mecklenburgisch-vorpommerschen Jungmoränenlandschaft ist hauptsächlich das Ergebnis glazialer Überformung. Heute wird das Gebiet überwiegend ackerbaulich genutzt. Die Niedermoore dienen der Grünlandnutzung. Ein Teil dieser Niedermoorstandorte wurde im Rahmen von Renaturierungsmaßnahmen wiedervernässt. Die Wälder sind größtenteils auf die Moränenstandorte beschränkt. Infolge der hohen Standortvariabilität sind die räumlichen und zeitlichen Verände­rungen auf engem Raum innerhalb der vergleichsweise großen Schläge (>100 ha) bei der Bewirtschaf­tung zu berück­sichtigen, so dass eine teilschlagbezogene Bewirtschaftung erforderlich ist.

Insgesamt werden im Untersuchungsgebiet mehr als 40 Wetterstationen und mehr als 65 Bodenfeuchtemessstellen automatisiert zum Umweltmonitoring betrieben. Seit dem Start von DEMMIN im Jahr 1999 wurde die Datenbasis kontinuierlich erweitert. Einerseits liefern die Landwirte jedes Jahr neue Informationen zur Präzisionslandwirtschaft wie z.B. Ertrags- und Nährstoffkarten. Andererseits wird die Datenbasis durch verschiedene Forschungsaktivitäten erweitert, die von Luftbildaufnahmen und Bodenmessungen begleitet werden (z.B. AgriSens DEMMIN 4.0).

Die bewirtschafteten Flächen der kooperierenden Landwirte umfassen ca. 30.000 ha. Das Gebiet ist für wissenschaftliche Anwendungen der Fernerkundung besonders geeignet, da die Standortheterogenität (z.B. Landschaftstypen, Geologie, Boden, Wasserverhältnisse, Landbedeckung, Landnutzung) bei einer durchschnittlichen Schlaggröße von ca. 80 ha hoch ist. Die angebauten Hauptfruchtarten sind Wintergetreide (z.B. Winterweizen, -gerste, -roggen), die fast 60% der Felder bedecken. Die Fläche für Mais, Zuckerrübe und Kartoffeln beträgt etwa 13%.

Das Landschaftslabor DEMMIN liegt direkt im Orbit von verschiedensten Erdbeobachtungssatelliten (Sentinel-1+2, Landsat 8) und eignet sich somit hervorragend als Kalibrierungs-, Validierungs-, und Umweltupscaling- und –Modellierungsstandort. Im Rahmen von jährlich mehrfach durchgeführten Feld- und Studierendenkampagnen werden im Rahmen von standardisierten Beprobungen verschiedene agrarmeteorologische, phänologische und biophysikalische Parameter erhoben, die sich zur Einbindung in die Bearbeitung landwirtschaftlicher Fragestellungen und zur Analyse von Fernerkundungsdaten eignen (z.B. Blattflächenindex, Chlorophyllgehalt, oberirdische Biomasse).

Partner vor Ort:

  • Daberkower Landhof
  • Bentziner Ackerbaubetrieb
  • Hochschule Neubrandenburg
  • DLR Neustrelitz
2355391 2XDMJIQC LLDEMMIN 1 annals-of-hematology 50 date desc 4343 https://geooeko.geo.uni-halle.de/wp-content/plugins/zotpress/
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Wenzel, J.L., Poehlitz, J., Usman, M., Piernicke, T. and Conrad, C. (2025) Enhancing Irrigation Scheduling by Application Efficiency Estimations and Soil Moisture Simulations. European Journal of Agronomy, 164, 127487. https://doi.org/https://doi.org/10.1016/j.eja.2024.127487.
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Loew, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024, June 20) How Does Phenology Shape Crop- And Orbit-Specific InSAR Coherence And PolSAR-Signatures Of Sentinel-1. Manchester, UK.
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Friedrich, C., Loew, J., Otte, I., Hill, S., Schierghofer, C., Gessner, U., Truckenbrodt, S., Schonert, E., Piernecke, T., Conrad, C. and Thiel, M. (2024, March 21) DataCube Architecture for Integrating, Processing and Presenting Big Geodata to End Users. Berlin.
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Loew, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024) Tracking Crop Phenology across Different Sentinel-1 Orbits by Combining PolSAR Features with Growing Degree Data. Remagen.
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Loew, J., Hill, S., Thiel, M., Ullmann, T. and Conrad, C. (2024, March 15) Tracking Crop Phenology across Different Sentinel-1 Orbits by Combining PolSAR Features with Growing Degree Data. Remagen.
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Friedrich, C., Loew, J., Otte, I., Hill, S., Förtsch, S., Schwalb-Willmann, J., Gessner, U., Schierghofer, C., Piernecke, T., Truckenbrodt, S., Schonert, E., Assmann, D., Böttcher, F., Conrad, C. and Thiel, M. (2024, February 28) A Multi-Talented Datacube: Integrating, Processing and Presenting Big Geodata for the agricultural End User. Stuttgart-Hohenheim.
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Friedrich, C., Loew, J., Otte, I., Hill, S., Förtsch, S., Schwalb-Willmann, J., Gessner, U., Schierghofer, C., Piernecke, T., Truckenbrodt, S., Schonert, E., Assmann, D., Böttcher, F., Conrad, C. and Thiel, M. (2024) A Multi-Talented Datacube: Integrating, Processing and Presenting Big Geodata for the agricultural End User. Informatik in Der Land-, Forstund: Biodiversität Fördern Durch Digitale Landwirtschaft, Stuttgart-Hohenheim.
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Wenzel, J.L., Conrad, C. and Poehlitz, J. (2024) Soil Moisture Simulations for a Sustainable Irrigation Management. C. Hoffmann, A. Stein, E. Gallmann, J. Dörr, C. Krupitzer, H. Floto (Hrsg.) Informatik in Der Land-, Forst- Und Ernährungswirtschaft: Biodiversität Fördern Durch Digitale Landwirtschaft, GI Lecture Notes in Informatics (LNI), Stuttgart-Hohenheim, 449–453.
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Poehlitz, J., Wenzel, J.L., Piernicke, T., Teucher, M., Gerighausen, H., Gessner, U., Thiel, M., Kunz, M. and Conrad, C. (2024, February 27) AgriSens – Demmin 4.0: Digital Solutions for Sustainable Agriculture through Remote Technologies (Phase II). Poster, Stuttgart-Hohenheim.
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Wenzel, J.L., Conrad, C. and Poehlitz, J. (2024, February 27) Soil Moisture Simulations for a Sustainable Irrigation Management. Poster, Stuttgart-Hohenheim.
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Wenzel, J.L., Conrad, C., Piernicke, T., Haßelbusch, K., Boettcher, F. and Poehlitz, J. (2023) Observing Soil Moisture Dynamics on Starch Potato Fields for Improving Irrigation Management Based on Hydrological Simulations. A European Vision for Hydrological Observations and Experimentation, Naples, Italy.
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Wenzel, J.L., Conrad, C., Piernicke, T., Haßelbusch, K., Boettcher, F. and Poehlitz, J. (2023, June 14) Observing Soil Moisture Dynamics on Starch Potato Fields for Improving Irrigation Management Based on Hydrological Simulations. Poster, Naples, Italy.
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Piernicke, T., Wenzel, J.L. and Poehlitz, J. (2023) Teilflächenspezifische Beregnung: Effizientes Zusatzwasser. Bauernzeitung Wochenblatt für die ostdeutsche Landwirtschaft Ausgabe Sachsen, Thüringen & Sachsen-Anhalt, 22.
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Piernicke, T., Wenzel, J.L. and Poehlitz, J. (2023) Teilflächenspezifische Beregnung: Mit Smarten Wetterstationen Und Drohnen. Bauernzeitung Wochenblatt für die ostdeutsche Landwirtschaft Ausgabe Sachsen, Thüringen & Sachsen-Anhalt, 20. https://www.bauernzeitung.de/agrarpraxis/teilflaechenspezifische-beregnung-mit-smarten-wetterstationen-und-drohnen/.
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Wenzel, J.L., Conrad, C., Piernicke, T. and Poehlitz, J. (2023, May 15) Modeling Soil Moisture dynamics on Variably Irrigated Starch Fields. Oral Presentation, Berlin, Germany.
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Wenzel, J.L., Conrad, C., Piernicke, T., Spengler, D. and Poehlitz, J. (2022) Assessing the Impact of Different Irrigation Levels on Starch Potato Production. Agronomy, 12, 2685. https://doi.org/10.3390/agronomy12112685.
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Wenzel, J.L., Piernicke, T., Poehlitz, J., Haßelbusch, K., Böttcher, F., Spengler, D. and Conrad, C. (2022) Using Soil Hydraulic Properties for an Efficient Starch Potato Irrigation Management. Proceedings of the 14th International Symposium on Ecohydraulics, Nanjing, China. https://ise2022.org/en/web/index/231_129396.
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Wenzel, J.L., Piernicke, T., Poehlitz, J., Haßelbusch, K., Böttcher, F., Spengler, D. and Conrad, C. (2022, October 12) Using Soil Hydraulic Properties for an Efficient Starch Potato Irrigation Management. Oral Presentation, Nanjing, China.
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Wenzel, J.L., Piernicke, T., Böttcher, F., Spengler, D., Conrad, C. and Poehlitz, J. (2022, September 1) Economic Effects of Variable Irrigation on Yield and Quality Parameters of High-Amylopectin Potatoes. Poster, Potsdam, Germany.
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Poehlitz, J., Wenzel, J.L. and Piernicke, T. (2022) Digitales Wassersparen. Landwirtschaft ohne Pflug – Das Fachmagazin für den professionellen Pflanzenbau, 28, 44–48.
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Thürkow, F., Conrad, C., Thürkow, D. and Teucher, M. (2022, May 26) Suitability of Thermal UAV Data to Detect Stones and Artificial Objects in Agriculture. Bonn.
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Teucher, M., Conrad, C., Alb, P. and Thürkow, D. (2022, May 25) Provision of FAIR In-Situ Data for Calibration and Validation in RS Precision Agriculture. Bonn.
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Spengler, D., Böttcher, F., Borg, E., Dobers, E.S., Gerighausen, H., Klan, F., Otte, I., Teucher, M., Thiel, M., Truckenbrodt, S., Wenzl, M. and Conrad, C. (2022, May 23) Pathways to Using Remote Sensing in Crop Cultivation and Management – the German Digital Test Field AgriSens DEMMIN 4.0. Bonn.
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Poehlitz, J., Wenzel, J.L. and Piernicke, T. (2022) Mit Digitalisierung Wasser Sparen – Wie Kann Eine Ressourcenschonende Beregnung Gelingen. Bauernblatt Schleswig-Holstein, 47, 47–50.
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Teucher, M., Thürkow, D., Alb, P. and Conrad, C. (2022) Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture. Remote Sensing, 14, 393. https://doi.org/10.3390/rs14020393.
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Standort zur Kalibrierung und Validierung von Fernerkundungsdaten und zur Umweltmodellierung
Demmin, Mecklenburg Vorpommern
160.000 ha
1999, seit 2011 TERENO-Standort
Vegetations-, Boden-, Klimageographie