P344 - 44. GIL-Jahrestagung 2024 - Fokus: Biodiversität fördern durch digitale Landwirtschaft

Permanent URI for this collectionhttps://dl.gi.de/handle/20.500.12116/43863

Authors with most Documents  

Ackermann, Andrea
2
Assmann, Denise
2
Aue, Alexander
2
Becker, Rolf
2
Conrad, Christopher
2

Browse

Author: search.filters.author.Conrad, Christopher

Search Results

1 - 2 of 2
  • Conference Paper
    Soil moisture simulations for a sustainable irrigation management
    (Gesellschaft für Informatik e.V., 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.
  • Conference Paper
    A multi-talented datacube: integrating, processing and presenting big geodata for the agricultural end user
    (Gesellschaft für Informatik e.V., 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.
Load citations