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.
A multisensor platform for comprehensive detection of crop status: Results from two case studies / Rilling, S.; Nielsen, M.; Milella, A.; Jestel, C.; Frohlich, P.; Reina, G.. - (2017), pp. 8078479.1-8078479.6. (Intervento presentato al convegno 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 tenutosi a ita nel 2017) [10.1109/AVSS.2017.8078479].
A multisensor platform for comprehensive detection of crop status: Results from two case studies
Reina G.
2017-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
