Logo des Repositoriums

Auflistung nach Autor:in "Conrad, Christopher"

1 - 4 von 4
  • Konferenzbeitrag
    AgriSens – DEMMIN 4.0
    (41. GIL-Jahrestagung, Informations- und Kommunikationstechnologie in kritischen Zeiten, 2021) Spengler, Daniel; Asam, Sarah; Boettcher, Falk; Borg, Erik; Dobers, Eike Stefan; Geßner, Ursula; Harfenmeister, Katharina; Hüttich, Christian; Klan, Friederike; Teucher, Mike; Truckenbrodt, Sina; Conrad, Christopher
    Die Digitalisierung der Landwirtschaft schreitet seit einigen Jahren immer weiter voran, wird aber in Deutschland noch nicht im großen Maßstab in landwirtschaftlichen Betrieben umgesetzt. Im Bereich der Geodatennutzung liegen die Herausforderungen vor allem bei der unzureichenden Definition von Schnittstellen sowie in einem mangelnden Daten- und Wissenstransfer zwischen Wissenschaft und Praxis. Hier setzt das Projekt „AgriSens – DEMMIN 4.0“ an, das vom Bundesministerium für Ernährung und Landwirtschaft (BMEL) im Rahmen der digitalen Experimentierfelder gefördert wird. Methoden zur Nutzung von Geodaten, insbesondere Fernerkundungsdaten, im Pflanzenbau werden analysiert und neu entwickelt und in konkreten Anwendungsfällen wie Ertragsabschätzung oder teilschlagspezifische Bewässerung dem Landwirt nutzbar gemacht.
  • Konferenzbeitrag
    Classification of agricultural land use and derivation of biophysical parameter
using SAR and optical data
    (Informatik in der Land-, Forst- und Ernährungswirtschaft 2017, 2017) Knöfel, Patrick; Dahms, Thorsten; Borg, Erik; Conrad, Christopher
    Agricultural monitoring is essential for global issues, which can be reflected by the terms of food security and ensuring ecosystem services. Due to the high spatial and temporal resolution of the remote sensing sensors enormous potential for precision farming has been worked out in cooperation between science and the private sector. However, the quality of field specific yield estimations, for instance, is highly influenced by the accuracy of the underlying information like land use, plant development, and stress indicators. Thus, particular knowledge about the accuracy of all the relevant indicators is crucial for agricultural monitoring. The chair of remote sensing at the University of Wuerzburg has gained a lot of expertise in this context by working on their three latest ongoing projects with agricultural focus. Within the framework of these projects, a classification and assessment tool with graphical user interface (MELanGe) was developed, which can be used for land use mapping and biophysical parameter derivation.
  • Konferenzbeitrag
    A multi-talented datacube: integrating, processing and presenting big geodata for the agricultural end user
    (44. GIL - Jahrestagung, Biodiversität fördern durch digitale Landwirtschaft, 2024) Friedrich, Christoph; Löw, Johannes; Otte, Insa; Hill, Steven; Förtsch, Sebastian; Schwalb-Willmann, Jakob; Gessner, Ursula; Schierghofer, Christoph; Truckenbrodt, Sina; Schonert, Eric; Piernicke, Thomas; Assmann, Denise; Conrad, Christopher; Thiel, Michael
    While scientific methods leveraging Earth Observation for agriculture are abundant, their actual application in Germany remains scarce. A key challenge in this context is to connect the end users to the data without the many technical obstacles. Therefore, we present a versatile platform that not only integrates and processes big geodata of highly diverse origin and type, but also provides access to these resources in ways that reflect the individual user’s requirements and expertise. Based on free and open-source software building blocks, our datacube facilitates scientific computation through R and Python environments or direct API access, including emergent technologies such as openEO, STAC, and COG. At the same time, the results are delivered to easy-to-use applications that adequately present them to non-technical experts. We detail the architecture of the system and demonstrate a use case serving computed plant vitality information directly to farmers in the field.
  • Konferenzbeitrag
    Soil moisture simulations for a sustainable irrigation management
    (44. GIL - Jahrestagung, Biodiversität fördern durch digitale Landwirtschaft, 2024) Wenzel, Jan Lukas; Conrad, Christopher; Pöhlitz, Julia
    Accurate estimations of crop water requirements accounting for spatial heterogeneous soil properties are recognized as a major contribution towards a sustainable agricultural irrigation management. Crop-specific irrigation demand estimations may be improved by physics-based soil moisture models, although spatially distributed soil moisture simulations strongly rely on profound assessments of the model accuracy and applicability under open-field conditions. Hence, this study aims to investigate simulated root-zone soil moisture dynamics on a variably irrigated potato field provided by the HYDRUS-1D model and its suitability for irrigation management purposes in terms of input parameter requirements and applicability on larger, heterogeneous sites. All simulations were highly accurate (RMSE = 0.018 m3 m-3), when compared to in-situ measurements, but varied stronger in topsoil than in subsoil layers. A pixel-based approach using aggregated soil properties, phenological characteristics and meteorological conditions enables appropriate trade-offs between simulation accuracy and the parameterization effort and applicability in irrigation management.