Abstract
This work describes an approach to calculate pedological parameter maps using hyperspectral remote sensing and soil sensors. These maps serve as information basis for automated and precise agricultural treatments by tractors and field robots. Soil samples are recorded by a handheld hyperspectral sensor and analyzed in the laboratory for pedological parameters. The transfer of the correlation between these two data sets to aerial hyperspectral images leads to 2D-parameter maps of the soil surface. Additionally, rod-like soil sensors provide local 3D-information of pedological parameters under the soil surface. The goal is to combine the area-covering 2D-parameter maps with the local 3D-information to extrapolate large-scale 3D-parameter maps using AI approaches.
Zusammenfassung
Diese Arbeit beschreibt einen Ansatz zur Erstellung bodenkundlicher Parameterkarten mittels hyperspektraler Fernerkundung und Bodensensorik, als Informationsgrundlage für automatisierte und präzise landwirtschaftliche Anwendungen durch Traktoren und Feldroboter. Dazu werden Bodenproben hyperspektral untersucht und pedologische Parameter im Labor analysiert. Die Übertragung der Korrelation zwischen diesen beiden Datensätzen auf hyperspektrale Luftbilder erzeugt 2D-Parameterkarten der Bodenoberfläche. Zusätzlich werden stabähnliche Bodensensoren im Feld versenkt, die lokal 3D-Information über pedologische Parameter liefern. Ziel ist die Verknüpfung der flächendeckenden 2D-Parameterkarten mit lokaler 3D-Information durch KI, um flächendeckende 3D-Parameterkarten zu erstellen.
About the authors
Simon Schreiner received his Master of Science degree in Applied Geoinformatics at the University of Trier, Germany, in 2016. He was research assistant at this University from 2012 until 2016. In 2017, he was cartographer at the City Department of Surveying in Stuttgart, Germany. Since 2018, he has been employed at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB in Ettlingen, Germany. His research focusses on hyperspectral remote sensing for defense technologies and precision farming applications.
Dubravko Culibrk is a Full Professor of Information Systems Engineering at the Department of Industrial Engineering and Management of the Faculty of Technical Sciences, University of Novi Sad, Serbia. While pursuing his PhD degree (2003–2006) at the Florida Atlantic University, USA, he was affiliated with the Center for Coastline Security and the Center for Cryptology and Information Security. He spent two years (2013–2015) as a postdoc researcher at the University of Trento, Italy with the Multimedia and Human Understanding Group. His current research interests include: Neural Networks and Deep Learning, Computer Vision, Machine Learning and Data Science, Multimedia, Remote Sensing and Image/Video Processing. He is an NVIDIA Deep Learning Institute University Ambassador.
Michele Bandecchi is the CEO of SmartCloudFarming GmbH and he is supervising the business and technology development of the company’s products. He received his two Master degrees in (i) Plant Biotechnology with specialization plant genomics and (ii) Management, Marketing and Consumer Studies with a specialization in Innovation Management at the Wageningen University Research (The Netherlands). He gained experience in marketing and sales during an internship with GRASSLANDZ TECHNOLOGY LTD. in New Zealand and for ten years in his family business in marketing and sales and business development.
Wolfgang Gross was born in Karlsruhe, Germany, in 1985. He received the Diploma in technomathematics from the Karlsruhe Institute of Technology KIT, Germany, in 2011. In 2019, he received his Ph. D. in engineering from the University of Stuttgart, Faculty for Aerospace Engineering and Geodesy. He is currently employed by the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, His current research includes the development of algorithms for hyperspectral analysis regarding data-driven automatic preprocessing, classification and manifold alignment for data synthesis.
Dr. Wolfgang Middelmann is the head of the image interpretation group at Fraunhofer IOSB. He got his diploma in mathematics at University Dortmund (Germany) in 1993. In 1998 he received his PhD (Dr. rer. nat.) in mathematics at Friedrich-Schiller-University Jena (Germany). Until 2002 he worked as software engineering manager for ESA projects and as project manager of international military projects at Daimler-Chrysler Aerospace. Since 2002 he was project manager and scientist for ATR and reconnaissance systems at FGAN-FOM Research Institute for Optronics and Pattern Recognition (2010 merged into Fraunhofer IOSB), Ettlingen (Germany). In 2008 he advanced to the head of the image interpretation group. Currently he is responsible for concepts, development and assessment of airborne and spaceborne ISR systems.
Acknowledgment
The authors would like to thank the German Aerospace Center for providing EnMAP simulations based on HySpex data and Dylan Warren Raffa for the agronomic insights and expertise.
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