Next Article in Journal
Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
Next Article in Special Issue
Development of a Spectrophotometric System to Detect White Striping Physiopathy in Whole Chicken Carcasses
Previous Article in Journal
Enhancing the Responsivity of Uncooled Infrared Detectors Using Plasmonics for High-Performance Infrared Spectroscopy
Previous Article in Special Issue
Robot-Beacon Distributed Range-Only SLAM for Resource-Constrained Operation
Article Menu
Issue 4 (April) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(4), 914; doi:10.3390/s17040914

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

1
Centre for Automation and Robotics, Spanish National Research Council, CSIC-UPM, Argandadel Rey, 28500 Madrid, Spain
2
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)
View Full-Text   |   Download PDF [1778 KB, uploaded 21 April 2017]   |  

Abstract

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
Figures

Figure 1

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top