L. Klingbeil: Where exactly is my plant? How to accurately georeference sensor data from mobile platforms in agricultural applications

Lasse Klingbeil is a permanent researcher at the Institute of Geodesy and Geoinformation at the University of Bonn, Germany. He leads the ‘Mobile sensor systems and GNSS’ group within the Geodesy lab. His research interest is 3D monitoring of objects and environments using mobile sensing systems within applications, such as agriculture, geomorphology as well as in classical surveying and engineering geodesy.

From 2008 to 2011 he was a research scientist at the Institute of Microsystems and Information Technology of the Hahn-Schickard-Gesellschaft (HSG-IMIT) in Villingen-Schwenningen, Germany, where he worked on various projects related to inertial sensors, multi-sensor fusion and indoor localization. From 2006 to 2008 he was a postdoctoral fellow at the ‘Autonomous Systems Laboratory’ of the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Brisbane, Australia, working on sensor networks for agricultural applications and indoor localization. In 2006 he received his PhD in Experimental Physics from the University of Bonn (Real-time pose estimation for moving objects).

One key aspect of digital agriculture is the acquisition of sensor data with a high temporal and spatial resolution. This is more and more realized using mobile sensing platforms, such as planes, UAVs, ground robots or common agricultural machinery. In order to analyze the sensor data and the derived parameters by monitoring them over time or integrating them with other spatial information sources, such as soil data, they need to be registered in the same global coordinate system. Depending on the application, this needs to happen in real time or it can be done in a post processing step.

Following the vision, that every leaf should have a coordinate, this presentation reviews the applications, methods and challenges of highly accurate georeferencing of sensor data, that are recorded with mobile platforms in the context of agriculture and field phenotyping.