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

Annalisa Milella;
2017

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.
2017
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
multi-sensor systems
precision agriculture
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/329808
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