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ISPRS Int. J. Geo-Inf. 2016, 5(6), 79; doi:10.3390/ijgi5060079

Evaluation of Different Irrigation Methods for an Apple Orchard Using an Aerial Imaging System

1
Department of Physics and Engineering, Northwest Nazarene University, Nampa 83686, USA
2
Parma Research and Extension Center, University of Idaho, Parma 83660, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz and Wolfgang Kainz
Received: 9 April 2016 / Revised: 23 May 2016 / Accepted: 26 May 2016 / Published: 1 June 2016
(This article belongs to the Special Issue Unmanned Aerial Vehicles in Geomatics)
View Full-Text   |   Download PDF [5451 KB, uploaded 1 June 2016]   |  

Abstract

Regular monitoring and assessment of crops is one of the keys to optimal crop production. This research presents the development of a monitoring system called the Crop Monitoring and Assessment Platform (C-MAP). The C-MAP is composed of an image acquisition unit which is an off-the-shelf unmanned aerial vehicle (UAV) equipped with a multispectral camera (near-infrared, green, blue), and an image processing and analysis component. The experimental apple orchard at the Parma Research and Extension Center of the University of Idaho was used as the target for monitoring and evaluation. Five experimental rows of the orchard were randomly treated with five different irrigation methods. An image processing algorithm to detect individual trees was developed to facilitate the analysis of the rows and it was able to detect over 90% of the trees. The image analysis of the experimental rows was based on vegetation indices and results showed that there was a significant difference in the Enhanced Normalized Difference Vegetation Index (ENDVI) among the five different irrigation methods. This demonstrates that the C-MAP has very good potential as a monitoring tool for orchard management. View Full-Text
Keywords: apple; digital image processing; machine vision; unmanned aerial vehicle (UAV); vegetation indices apple; digital image processing; machine vision; unmanned aerial vehicle (UAV); vegetation indices
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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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MDPI and ACS Style

Bulanon, D.M.; Lonai, J.; Skovgard, H.; Fallahi, E. Evaluation of Different Irrigation Methods for an Apple Orchard Using an Aerial Imaging System. ISPRS Int. J. Geo-Inf. 2016, 5, 79.

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