文章基本信息

标题：TELERILEVAMENTO MULTISPETTRALE DA DRONE PER IL MONITORAGGIO DELLE COLTURE IN AGRICOLTURA DI PRECISIONE. UN’APPLICAZIONE ALLA CIPOLLA ROSSA DI TROPEA
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作者：Giuseppe Modica ; Salvatore Praticò ; Gaetano Messina 等
期刊名称：LaborEst
印刷版ISSN：1973-7688
电子版ISSN：2421-3187
出版年度：2020
期号：21 (2020)
页码：85-90
DOI：10.19254/LaborEst.21.12
出版社："Mediterranea" University of Reggio Calabria
摘要：Recently, the International Society for Precision Agriculture (ISPA) defined Precision Agriculture (PA) as ‘a management strategy that gathers, processes and analyses temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production’. In the framework of PA the present paper shows a specific case study applied to the red onion of Tropea ( Cipolla Rossa di Tropea ) crop. The aim was the monitoring of fields using multispectral imagery acquired by a fixed-wings UAV, and through the use of different vegetation indexes. Multitemporal surveys were carried out using the eBee fixed-wing UAV, equipped with a multispectral camera Sequoia Parrot (R-G-RedEdge-NIR). UAV MS imagery were calibrated using a panel with known reflectance and verified with spectroradiometer measurements using the Apogee Ps-300 on bare soil and vegetation. The UAV monitoring has been implemented on three surveys carried out from November 2018 to January 2019. The results of the analysis of the three datasets showed a high correlation of GNDVI and NDVI vegetation indexes with SAVI. Therefore, the latter was chosen to analyse the vegetative vigour by applying the VI to onion crop’s masks extracted after segmentation and classification of the three images by a geographical object-based image classification (GEOBIA). The obtained results are promising although additional experiments are expected.
关键词：Precision Agriculture (PA);Remote sensing (RS);Unmanned aerial vehicles (UAVs);Vegetation indices (VIs);Multispectral surveys;Onion crop