Project member: Christopher Conrad, Nima Ahmadian Project duration: 2015-2018
Agricultural monitoring is essential for many global questions concerning food secrecy or ecosystem services. European and international initiatives aim on the development of data and information services for the early detection of seasonal negatively developments like droughts or long term monitoring of agricultural production on a global scale.
In contrast, the „Global Agricultural Monitoring. The German Contribution“(GLAM.DE) project is concerned with the development of local, economic services within the context of agriculture. GLMA.de aims on the development of methods for high resolution remote sensing (e.g.: RapidEye/ Sentinel-2 and TerraSAR/TanDEM-X/Sentinel-1) to assist agricultural monitoring.
The project is focusing on the topics of the GEOGLAM and Copernicus projects, like yield modelling and the monitoring of the growth and state of vegetation. In detail the project focuses on the derivation of vegetation and soil parameter in order to optimise a field based yield estimation model for winter wheat and maize used by the economy. The so called Light Use Efficiency Model quantifies the incoming radiation that’s been used by the plants for the gain of biomass.