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.
Highlights
As a case of precision agriculture, golf courses can be considered; this is called precision turfgrass in the literature [1]
Given the positive results previously obtained in the classification of images and given that the applications developed using the Hierarchical Temporal Memory (HTM) algorithm are capable of analyzing video images, the objective of the current study is to develop a recognition methodology for golf courses in real-time using video images taken by an Unmanned aerial vehicles (UAVs) based in a HTM for possible application in planning irrigation needs in order to maximize the water use efficiency and help to plan water requirements of reuse water
The first stage of this study is to propose a new methodology for analysing geometric patterns of of video data acquired from UAVs using a new Hierarchical Temporal Memory (HTM) algorithm
Summary
As a case of precision agriculture, golf courses can be considered; this is called precision turfgrass in the literature [1]. Spatio-temporal variation of soil, climate, plants and irrigation requirements are new challenges for precision agriculture and, above all, complex turfgrass sites [3]. The irrigation of golf courses is a major concern in this crop maintenance, especially in a Mediterranean climate, both in the USA and in Europe [4]. When reuse water of poor quality is used, as on golf courses in the arid southwestern United States, proper irrigation management is critical [6], so greenkeepers should pay attention to irrigation strategies employed on reuse water irrigated golf courses to properly manage for higher nitrogen and salt loads
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