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Water 2016, 8(12), 584; doi:10.3390/w8120584

Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses

1
Department of Applied Physics, University of Cordoba, CEIA3, Campus de Rabanales, 14071 Córdoba, Spain
2
Department of Graphic Engineering and Geomatics, University of Cordoba, CEIA3, Campus de Rabanales, 14071 Córdoba, Spain
3
CIAIMBITAL (Research Center on Agricultural and Food Biotechnology), University of Almeria, 04120 Almeria, Spain
4
Department of Engineering, University of Almeria, CEIA3, 04120 Almeria, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Hongjie Xie and Xianwei Wang
Received: 9 October 2016 / Revised: 22 November 2016 / Accepted: 2 December 2016 / Published: 8 December 2016
View Full-Text   |   Download PDF [8492 KB, uploaded 8 December 2016]   |  

Abstract

Golf courses can be considered as precision agriculture, as being a playing surface, their appearance is of vital importance. Areas with good weather tend to have low rainfall. Therefore, the water management of golf courses in these climates is a crucial issue due to the high water demand of turfgrass. Golf courses are rapidly transitioning to reuse water, e.g., the municipalities in the USA are providing price incentives or mandate the use of reuse water for irrigation purposes; in Europe this is mandatory. So, knowing the turfgrass surfaces of a large area can help plan the treated sewage effluent needs. Recycled water is usually of poor quality, thus it is crucial to check the real turfgrass surface in order to be able to plan the global irrigation needs using this type of water. In this way, the irrigation of golf courses does not detract from the natural water resources of the area. The aim of this paper is to propose a new methodology for analysing geometric patterns of video data acquired from UAVs (Unmanned Aerial Vehicle) using a new Hierarchical Temporal Memory (HTM) algorithm. A case study concerning maintained turfgrass, especially for golf courses, has been developed. It shows very good results, better than 98% in the confusion matrix. The results obtained in this study represent a first step toward video imagery classification. In summary, technical progress in computing power and software has shown that video imagery is one of the most promising environmental data acquisition techniques available today. This rapid classification of turfgrass can play an important role for planning water management. View Full-Text
Keywords: water management; golf course; memory-prediction theory; object-based classification; unmanned aerial vehicle water management; golf course; memory-prediction theory; object-based classification; unmanned aerial vehicle
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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

Perea-Moreno, A.-J.; Aguilera-Ureña, M.-J.; Meroño-De Larriva, J.-E.; Manzano-Agugliaro, F. Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses. Water 2016, 8, 584.

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