Publikationen DAKIS
2023
Melzer, M., Bellingrath-Kimura, S., Gandorfer, M.(2023). Commercial farm management information systems - A demand-oriented analysis of functions in practical use. Smart Agricultural Technology, 4, 100203. https://doi.org/10.1016/j.atech.2023.100203
2022
Donat, M., Geistert, J., Grahmann, K., Bloch, R., & Bellingrath-Kimura, S. D. (2022). Patch cropping- a new methodological approach to determine new field arrangements that increase the multifunctionality of agricultural landscapes. Computers and Electronics in Agriculture, 197, 106894. https://doi.org/10.1016/j.compag.2022.106894
Feld-Magazin. (seit 2017). Abgerufen 16. September 2022, von https://www.zalf.de/de/aktuelles/Feld-Magazin/Seiten/default.aspx
Golicz, K., Bellingrath-Kimura, S., Breuer, L., & Wartenberg, A. C. (2022). Carbon accounting in European agroforestry systems – Key research gaps and data needs. Current Research in Environmental Sustainability, 4, 100134. https://doi.org/10.1016/j.crsust.2022.100134
Grimpe, J.; Lucke, S.; Lorenz, T.; Bloch, R.; Cremer, T. (2022). Agroforst auf trockenen Böden. In Lumbrico (11), 41-45
Habib-ur-Rahman, M., Raza, A., Ahrends, H. E., Hüging, H., & Gaiser, T. (2022). Impact of in-field soil heterogeneity on biomass and yield of winter triticale in an intensively cropped hummocky landscape under temperate climate conditions. Precision Agriculture, 23(3), 912–938. https://doi.org/10.1007/s11119-021-09868-x
Lorenz, T., Gerster, L., Elias Wodzinowski, D., Wartenberg, A., Martetschläger, L., Molitor, H., Cremer, T., & Bloch, R. (2022). Innovative Teaching and Learning Formats for the Implementation of Agroforestry Systems—An Impact Analysis after Five Years of Experience with the Real-World Laboratory “Ackerbaum”. Forests, 13(7), 1064. https://doi.org/10.3390/f13071064
MacPherson, J., Voglhuber-Slavinsky, A., Olbrisch, M., Schöbel, P., Dönitz, E., Mouratiadou, I., & Helming, K. (2022). Future agricultural systems and the role of digitalization for achieving sustainability goals. A review. Agronomy for Sustainable Development, 42(4), 70. https://doi.org/10.1007/s13593-022-00792-6
Olbrisch, M. (2022). Agricultural Digital Policy. In M. Nachtmann & J. Dörr (Hrsg.), Handbook Digital Farming (S. 34–39).
Shaaban, M. (2022). The Viability of the Social-Ecological Agroecosystem (ViSA) Spatial Agent-based Model (1.0.0). CoMSES Net. https://doi.org/10.25937/6CEA-B617
Shaaban, M., Mouratiadou, I., & Piorr, A. (2022). Cooperative versus non-cooperative behaviour: Using agent-based modelling to identify spatial supply-demand mismatches of ecosystem services and to coordinate conflicting actors’ demands. https://doi.org/10.13140/RG.2.2.14062.08005
2021
Brose, A. H.; Gundlach, B.; Schuberth, J.; Gerster, L.; Martetschläger, L.; Bloch, R.; Cremer, T. (2021): Innovative Lehr- und Lernformate für neue Ackerbausysteme – dreijährige Erfahrungen aus dem Reallabor „Ackerbaum“. In: Kuratorium für Technik und Bauwesen in der Landwirtschaft e. V. (KTBL) Darmstadt (Hg.): Boden gut machen – neue Ackerbausysteme. Darmstadt, 16.-17.03.2021 (KTBL-Tage), 54-55.
Frohberg, M., Weidling, S., & Langendoerfer, P. (2021). Challenges in Developing a Wireless Sensor Network for an Agricultural Monitoring and Decision System. In B. Ghita & S. Shiaeles (Hrsg.), Selected Papers from the 12th International Networking Conference (Bd. 180, S. 224–240). Springer International Publishing. https://doi.org/10.1007/978-3-030-64758-2_16
Härtel, I. (2021). Agrar-Digitalrecht für Agrarsysteme der Zukunft. At - Automatisierungstechnik, 69(4), 278–280. https://doi.org/10.1515/auto-2021-0004
Montzka, C., Bayat, B., Tewes, A., Mengen, D., & Vereecken, H. (2021). Sentinel-2 Analysis of Spruce Crown Transparency Levels and Their Environmental Drivers After Summer Drought in the Northern Eifel (Germany). Frontiers in Forests and Global Change, 4, 667151. https://doi.org/10.3389/ffgc.2021.667151
Raza, A., Ahrends, H., Habib-Ur-Rahman, M., & Gaiser, T. (2021). Modeling Approaches to Assess Soil Erosion by Water at the Field Scale with Special Emphasis on Heterogeneity of Soils and Crops. Land, 10(4), 422. https://doi.org/10.3390/land10040422
Schöbel, P. (2021). Die behördliche Kontrolle durch Blockchain-Technologie in der Agrar- und Ernährungswirtschaft – Datenschutz- rechtliche Anforderungen. Frankfurt (Oder). https://www.rewi.europa-uni.de/de/lehrstuhl/or/verwaltrecht/Forschungsstelle-fuer-Digitalrecht/Die-behoerdliche-Kontrolle-durch-Blockchain-Technologie-in-der-Agar--und-Ernaehrungswirtschaft-Datenschutzrechtliche-Anforderungen.pdf
Schwartz, C., Shaaban, M., Bellingrath-Kimura, S. D., & Piorr, A. (2021). Participatory Mapping of Demand for Ecosystem Services in Agricultural Landscapes. Agriculture, 11(12), 1193. https://doi.org/10.3390/agriculture11121193
Shaaban, M., Schwartz, C., Macpherson, J., & Piorr, A. (2021). A Conceptual Model Framework for Mapping, Analyzing and Managing Supply–Demand Mismatches of Ecosystem Services in Agricultural Landscapes. Land, 10(2), 131. https://doi.org/10.3390/land10020131
Ungaro, F., Schwartz, C., & Piorr, A. (2021). Ecosystem services indicators dataset for the utilized agricultural area of the Märkisch-Oderland District-Brandenburg, Germany. Data in Brief, 34, 106645. https://doi.org/10.1016/j.dib.2020.106645
2020
Bellingrath-Kimura, S. D., & Bloch, R. (2020). Smart Farming – Eine Chance für nachhaltige Agrarsysteme? In M. Göpel, H. Leitschuh, A. Brunnengräber, P. L. Ibisch, R. Loske, M. Müller, J. Sommer, & E. U. von Weizsäcker (Hrsg.), Die Ökologie der digitalen Gesellschaft. S. Hirzel Verlag.
Dönitz, E., Voglhuber-Slavinsk, A., Moller, B., & Fraunhofer Institute for Systems and Innovation Research ISI. (2020). Agribusiness in 2035 – Farmers of the Future. https://adz-dakis.com/wp-content/uploads/agribusiness-in-2035-farmers-of-the-future.pdf
Härtel, I. (2020). Künstliche Intelligenz in der nachhaltigen Landwirtschaft – Datenrechte und Haftungsregime. Natur und Recht, 42(7), 439–453. https://doi.org/10.1007/s10357-020-3704-3
MacPherson, J., Paul, C., & Helming, K. (2020). Linking Ecosystem Services and the SDGs to Farm-Level Assessment Tools and Models. Sustainability, 12(16), 6617. https://doi.org/10.3390/su12166617
Tewes, A., Hoffmann, H., Krauss, G., Schäfer, F., Kerkhoff, C., & Gaiser, T. (2020). New Approaches for the Assimilation of LAI Measurements into a Crop Model Ensemble to Improve Wheat Biomass Estimations. Agronomy, 10(3), 446. https://doi.org/10.3390/agronomy10030446
Tewes, A., Hoffmann, H., Nolte, M., Krauss, G., Schäfer, F., Kerkhoff, C., & Gaiser, T. (2020). How Do Methods Assimilating Sentinel-2-Derived LAI Combined with Two Different Sources of Soil Input Data Affect the Crop Model-Based Estimation of Wheat Biomass at Sub-Field Level? Remote Sensing, 12(6), 925. https://doi.org/10.3390/rs12060925
Tewes, A., Montzka, C., Nolte, M., Krauss, G., Hoffmann, H., & Gaiser, T. (2020). Assimilation of Sentinel-2 Estimated LAI into a Crop Model: Influence of Timing and Frequency of Acquisitions on Simulation of Water Stress and Biomass Production of Winter Wheat. Agronomy, 10(11), 1813. https://doi.org/10.3390/agronomy10111813
2019
Härtel, I. (2019). Agrar-Digitalrecht für eine nachhaltige Landwirtschaft 4.0. Natur und Recht, 41(9), 577–586. https://doi.org/10.1007/s10357-019-3571-y