Suitability of thermal UAV data to detect stones and artificial objects in agriculture

Stones on agricultural land can cause serious damage to agricultural machinery, when they are getting inside the machinery. This phenoma is especially pronounced in regions with high frequency of stones occurring on agricultural lands, e.g. in glacial morainic landscapes, as they occur in northern Germany. Therefore, stones must be removed from farmland several times a year. A worfklow for drone-based detection of stones is currently under development at the Geoecology department of MLU Halle to assist solving this problem. With our workflow, we demonstrate the particular suitability of UAS-based thermal data to differentiate between stones and soil surface on agricultural lands. Thermal inertia effects can be used to make significant temperature differences between stone and soil detectable. Which enables precise stone detection through UAS based thermal imaging. We have conducted extensive laboratory testing to investigate the suitability of thermal imaging to detect stones and to find the optimal pre-requisite for thermal UAV flights

Storymaps in der Lehrerbildung : Klimaanpassungsstrategien verstehen

Die aktuellen und zukunftsrelevanten Themen Klimawandel, Klimafolgen und Klimaanpassung stellen global, regional und lokal eine hohe gesellschaftliche Relevanz dar, weshalb die wachsenden Anforderungen an Landnutzungs- und Managementstrategien sowie an Maßnahmen zur Klimaanpassung im Geographieunterricht und somit in der universitären Lehrerbildung zunehmend im Fokus stehen. Zur Entwicklung eines Verständnisses für komplexe Zusammenhänge zum globalen Klimasystem, dessen Auswirkungen sowie anthropogenen Maßnahmen wurde eine digitale Lehr- und Lernumgebung in Form von Story Maps entwickelt. Unter Story Maps sind interaktive, multimediale (Geo-)Präsentationen mit Bild-, Karten-, Text-, Zeit- und Raumbezug zu verstehen. Die entwickelten Online-Lernmodule fokussieren auf ausgewählte Regionen und Themen Mitteldeutschlands,insbesondere das Mitteldeutsche Trockengebiet sowie die angrenzenden Mittelgebirgsregionen, welche gegenüber Prozessen des Klimawandels eine besonders hohe ökonomische und ökologische Relevanz aufweisen. Die Online Tools sind frei zugänglich und werden im Rahmen von Blended-Learning-Szenarien sowohl in fachwissenschaftlichen als auch in fachdidaktischen Modulen des Lehramtsstudiums im Fach Geographie genutzt

Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture

Digital solutions in agricultural management promote food security and support the sustainable use of resources. As a result, remote sensing (RS) can be seen as an innovation for the fast generation of reliable information for agricultural management. Near real-time processed RS data can be used as a tool for decision making on multiple scales, from subplot to the global level. This high potential is not yet fully applied, due to often limited access to ground truth information, which is crucial for the development of transferable applications and acceptance. In this study we present a digital workflow for the acquisition, processing and dissemination of agroecological information based on proprietary and open-source software tools with state-of-the-art web-mapping technologies. Data is processed in near real-time and thus can be used as ground truth information to enhance quality and performance of RS-based products. Data is disseminated by easy-to-understand visualizations and download functionalities for specific application levels to serve specific user needs. It thus can increase expert knowledge and can be used for decision support at the same time. The fully digital workflow underpins the great potential to facilitate quality enhancement of future RS products in the context of precision agriculture by safeguarding data quality. The generated FAIR (findable, accessible, interoperable, reusable) datasets can be used to strengthen the relationship between scientists, initiatives and stakeholders

Digital In Situ Data Collection in Earth Observation, Monitoring and Agriculture—Progress towards Digital Agriculture

Digital solutions in agricultural management promote food security and support the sustainable use of resources. As a result, remote sensing (RS) can be seen as an innovation for the fast generation of reliable information for agricultural management. Near real-time processed RS data can be used as a tool for decision making on multiple scales, from subplot to the global level. This high potential is not yet fully applied, due to often limited access to ground truth information, which is crucial for the development of transferable applications and acceptance. In this study we present a digital workflow for the acquisition, processing and dissemination of agroecological information based on proprietary and open-source software tools with state-of-the-art web-mapping technologies. Data is processed in near real-time and thus can be used as ground truth information to enhance quality and performance of RS-based products. Data is disseminated by easy-to-understand visualizations and download functionalities for specific application levels to serve specific user needs. It thus can increase expert knowledge and can be used for decision support at the same time. The fully digital workflow underpins the great potential to facilitate quality enhancement of future RS products in the context of precision agriculture by safeguarding data quality. The generated FAIR (findable, accessible, interoperable, reusable) datasets can be used to strengthen the relationship between scientists, initiatives and stakeholders