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Sensors 2017, 17(4), 914;

Influence of Wind Speed on RGB-D Images in Tree Plantations

Centre for Automation and Robotics, Spanish National Research Council, CSIC-UPM, Argandadel Rey, 28500 Madrid, Spain
Institute of Agricultural Sciences, Spanish National Research Council, CSIC, 28006 Madrid, Spain
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 19 January 2017 / Revised: 10 April 2017 / Accepted: 18 April 2017 / Published: 21 April 2017
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
Full-Text   |   PDF [1778 KB, uploaded 21 April 2017]   |  


Weather conditions can affect sensors’ readings when sampling outdoors. Although sensors are usually set up covering a wide range of conditions, their operational range must be established. In recent years, depth cameras have been shown as a promising tool for plant phenotyping and other related uses. However, the use of these devices is still challenged by prevailing field conditions. Although the influence of lighting conditions on the performance of these cameras has already been established, the effect of wind is still unknown. This study establishes the associated errors when modeling some tree characteristics at different wind speeds. A system using a Kinect v2 sensor and a custom software was tested from null wind speed up to 10 m·s−1. Two tree species with contrasting architecture, poplars and plums, were used as model plants. The results showed different responses depending on tree species and wind speed. Estimations of Leaf Area (LA) and tree volume were generally more consistent at high wind speeds in plum trees. Poplars were particularly affected by wind speeds higher than 5 m·s−1. On the contrary, height measurements were more consistent for poplars than for plum trees. These results show that the use of depth cameras for tree characterization must take into consideration wind conditions in the field. In general, 5 m·s−1 (18 km·h−1) could be established as a conservative limit for good estimations. View Full-Text
Keywords: RGB-D images; Kinect sensor limits; depth information; wind speed; woody crops RGB-D images; Kinect sensor limits; depth information; wind speed; woody crops

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Andújar, D.; Dorado, J.; Bengochea-Guevara, J.M.; Conesa-Muñoz, J.; Fernández-Quintanilla, C.; Ribeiro, Á. Influence of Wind Speed on RGB-D Images in Tree Plantations. Sensors 2017, 17, 914.

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