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A multisensor platform for comprehensive detection of crop status: Results from two case studies

: Rilling, Stefan; Nielsen, Michael; Milella, Annalisa; Jestel, Christian; Fröhlich, Peter; Reina, Giulio

Postprint urn:nbn:de:0011-n-4803462 (908 KByte PDF)
MD5 Fingerprint: 5ac764bd0509277a1244a0d118a9b9b2
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Created on: 24.1.2018

Institute of Electrical and Electronics Engineers -IEEE-:
14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 : August 29, 2017-September 1, 2017, Lecce
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-2939-0
ISBN: 978-1-5386-2940-6 (Print)
International Conference on Advanced Video and Signal Based Surveillance (AVSS) <14, 2017, Lecce>
Bundesministerium für Ernährung und Landwirtschaft BMEL
2815ERA08H; S3-CAV
Conference Paper, Electronic Publication
Fraunhofer IAIS ()

The measurement of the growth state and health status of single plants or even single parts of the plants within a crop to conduct precision farming actions is a difficult task. We address this challenge by adopting a multi-sensor suite, which can be used on several sensor-platforms. Based on experimental field studies in relevant agricultural environments, we show how the acquired hyperspectral, LIDAR, stereo and thermal image data can be processed and classified to get a comprehensive understanding of the agricultural acreage.