On-the-Fly Olive Tree Counting Using a UAS and Cloud Services

作     者：Salami, Esther Gallardo, Antonia Skorobogatov, Georgy Barrado, Cristina 

作者机构：UPC BarcelonaTECH Comp Architecture Dept Esteve Terrades 7 Castelldefels 08860 Spain 

出 版 物：《REMOTE SENSING》 (遥感)

年 卷 期：2019年第11卷第3期

页      面：316-316页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1002[医学-临床医学] 070801[理学-固体地球物理学] 07[理学] 08[工学] 0708[理学-地球物理学] 0816[工学-测绘科学与技术] 

基　　金：Ministry of Economy  Industry and Competitiveness of Spain [TRA2016-77012-R] 

主　　题：UAS UAV image segmentation tree counting distributed services cloud computing 

摘      要：Unmanned aerial systems (UAS) are becoming a common tool for aerial sensing applications. Nevertheless, sensed data need further processing before becoming useful information. This processing requires large computing power and time before delivery. In this paper, we present a parallel architecture that includes an unmanned aerial vehicle (UAV), a small embedded computer on board, a communication link to the Internet, and a cloud service with the aim to provide useful real-time information directly to the end-users. The potential of parallelism as a solution in remote sensing has not been addressed for a distributed architecture that includes the UAV processors. The architecture is demonstrated for a specific problem: the counting of olive trees in a crop field where the trees are regularly spaced from each other. During the flight, the embedded computer is able to process individual images on board the UAV and provide the total count. The tree counting algorithm obtains an F-1 score of 99.09% for a sequence of ten images with 332 olive trees. The detected trees are geolocated and can be visualized on the Internet seconds after the take-off of the flight, with no further processing required. This is a use case to demonstrate near real-time results obtained from UAS usage. Other more complex UAS applications, such as tree inventories, search and rescue, fire detection, or stock breeding, can potentially benefit from this architecture and obtain faster outcomes, accessible while the UAV is still on flight.