Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses
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 turfgr...
| Main Authors: | , , , |
|---|---|
| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
MDPI
2020
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/7337 |
| _version_ | 1789406517987901440 |
|---|---|
| author | Perea Moreno, Alberto Jesús Aguilera Ureña, María Jesús Meroño de Larriva, José Emilio Manzano Agugliaro, Francisco |
| author_facet | Perea Moreno, Alberto Jesús Aguilera Ureña, María Jesús Meroño de Larriva, José Emilio Manzano Agugliaro, Francisco |
| author_sort | Perea Moreno, Alberto Jesús |
| collection | DSpace |
| description | 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. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-7337 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-73372023-04-12T19:31:17Z Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses Perea Moreno, Alberto Jesús Aguilera Ureña, María Jesús Meroño de Larriva, José Emilio Manzano Agugliaro, Francisco water management golf course memory-prediction theory object-based classification unmanned aerial vehicle 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. 2020-01-16T08:56:34Z 2020-01-16T08:56:34Z 2016-12-08 info:eu-repo/semantics/article 2073-4441 http://hdl.handle.net/10835/7337 en https://www.mdpi.com/2073-4441/8/12/584 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | water management golf course memory-prediction theory object-based classification unmanned aerial vehicle Perea Moreno, Alberto Jesús Aguilera Ureña, María Jesús Meroño de Larriva, José Emilio Manzano Agugliaro, Francisco Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title | Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title_full | Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title_fullStr | Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title_full_unstemmed | Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title_short | Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses |
| title_sort | assessment of the potential of uav video image analysis for planning irrigation needs of golf courses |
| topic | water management golf course memory-prediction theory object-based classification unmanned aerial vehicle |
| url | http://hdl.handle.net/10835/7337 |
| work_keys_str_mv | AT pereamorenoalbertojesus assessmentofthepotentialofuavvideoimageanalysisforplanningirrigationneedsofgolfcourses AT aguileraurenamariajesus assessmentofthepotentialofuavvideoimageanalysisforplanningirrigationneedsofgolfcourses AT meronodelarrivajoseemilio assessmentofthepotentialofuavvideoimageanalysisforplanningirrigationneedsofgolfcourses AT manzanoagugliarofrancisco assessmentofthepotentialofuavvideoimageanalysisforplanningirrigationneedsofgolfcourses |