Team: Christopher Conrad Nima Ahmadian
Duration: 2015-2018
Agricultural monitoring is essential for global issues related to food security and ecosystem services. European and international initiatives aim to develop data and information services that allow, for example, early detection of seasonal negative developments such as droughts or long-term monitoring of agricultural production. The project “Global Agricultural Monitoring. The German Contribution” (GLAM.DE) addresses the challenge of developing local, economically viable services in the field of agriculture. The scientific core objective of the GLAM.DE project is the development of innovative methods for agricultural monitoring on the basis of the high-resolution missions RapidEye/Sentinel-2 and TerraSAR/TanDEM-X/Sentinel-1. From a technical point of view, the content focuses on the topics of crop modelling and the monitoring of plant condition and growth conditions targeted in GEOGLAM and Copernicus and is thus oriented towards the topic of food security. Specifically, the aim is to derive vegetation and soil parameters to optimise a field-based yield model for wheat and maize used by industry. The so-called Light Use Efficiency Model aims to quantify the radiation turnover in the plant for its biomass growth. More…
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.