GeoPard for Science and Education

Cornell Nutrient Management Spear Program (NMSP) leader and CAST collaborator Quirine Ketterings and her team are using data from CAST fields to evaluate and improve the accuracy of GeoPard’s algorithms to map yield and determine synthetic yield. Together with GeoPard, they are also assessing data quality and protocols to generate yield stability zone maps for fields with multiple years of data.

As part of the collaboration, NUBiP master’s and postgraduate students will gain access to GeoPard’s professional tools for satellite data analysis, variable rate application (VRA) planning, and field production potential research. This will allow future agronomists and scientists to apply modern digital technologies that are already used in leading agricultural holdings and farms in Europe, the USA, and Latin America.

LfL (the Bavarian State Research Center for Agriculture) and GeoPard, through the Future Crop Farming project, are advancing analysis tools for unconventional field structures by leveraging GeoPard’s advanced spatial analytics platform to complement LfL’s research results and create clear visualizations for communicating project insights to the public. With a shared focus on precision farming, productivity, and environmental stewardship, this innovative LfL project highlights the potential for a more sustainable future in crop production.

Svetainė AKI4KMU project, led by a consortium including Hochschule Hamm-Lippstadt, FlyPard Analytics GmbH, and Pfeifer & Langen GmbH & Co. KG, focuses on harnessing artificial intelligence (AI) and modern communication technologies to drive innovation and sustainability, particularly in the agricultural sector.

As part of the EU-funded ECO-Ready initiative, GeoPard contributed to the Lippe Living Lab by supporting targeted soil sampling and field monitoring. Productivity maps and scouting apps informed recommendations for farmers on managing field variability and optimizing inputs under climate stress.

As part of a biodiversity monitoring project led by the Helmholtz Centre Potsdam – GFZ, GeoPard delivered multi-year
datasets covering diverse ecosystems, from deserts to river deltas. The data was prepared to support AI-based modeling, enabling researchers to focus on interpretation rather than preprocessing.