Global Navigation Satellite Systems as State-of-the-Art Solutions in Precision Agriculture: A Review of Studies Indexed in the Web of Science
-
Published:2023-07-17
Issue:7
Volume:13
Page:1417
-
ISSN:2077-0472
-
Container-title:Agriculture
-
language:en
-
Short-container-title:Agriculture
Author:
Radočaj Dorijan1ORCID, Plaščak Ivan1ORCID, Jurišić Mladen1ORCID
Affiliation:
1. Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Abstract
Global Navigation Satellite Systems (GNSS) in precision agriculture (PA) represent a cornerstone for field mapping, machinery guidance, and variable rate technology. However, recent improvements in GNSS components (GPS, GLONASS, Galileo, and BeiDou) and novel remote sensing and computer processing-based solutions in PA have not been comprehensively analyzed in scientific reviews. Therefore, this study aims to explore novelties in GNSS components with an interest in PA based on the analysis of scientific papers indexed in the Web of Science Core Collection (WoSCC). The novel solutions in PA using GNSS were determined and ranked based on the citation topic micro criteria in the WoSCC. The most represented citation topics micro based on remote sensing were “NDVI”, “LiDAR”, “Harvesting robot”, and “Unmanned aerial vehicles” while the computer processing-based novelties included “Geostatistics”, “Precise point positioning”, “Simultaneous localization and mapping”, “Internet of things”, and “Deep learning”. Precise point positioning, simultaneous localization and mapping, and geostatistics were the topics that most directly relied on GNSS in 93.6%, 60.0%, and 44.7% of the studies indexed in the WoSCC, respectively. Meanwhile, harvesting robot research has grown rapidly in the past few years and includes several state-of-the-art sensors, which can be expected to improve further in the near future.
Subject
Plant Science,Agronomy and Crop Science,Food Science
Reference112 articles.
1. Shannon, D., Clay, D.E., and Sudduth, K.A. (2018). Precision Agriculture Basics, John Wiley & Sons, Ltd. 2. Petropoulos, G.P., and Srivastava, P.K. (2021). GPS and GNSS Technology in Geosciences, Elsevier. 3. Catania, P., Comparetti, A., Febo, P., Morello, G., Orlando, S., Roma, E., and Vallone, M. (2020). Positioning Accuracy Comparison of GNSS Receivers Used for Mapping and Guidance of Agricultural Machines. Agronomy, 10. 4. Radočaj, D., Plaščak, I., Heffer, G., and Jurišić, M. (2022). A Low-Cost Global Navigation Satellite System Positioning Accuracy Assessment Method for Agricultural Machinery. Appl. Sci., 12. 5. Gervasi, O., Murgante, B., Misra, S., Garau, C., Blečić, I., Taniar, D., Apduhan, B.O., Rocha, A.M.A.C., Tarantino, E., and Torre, C.M. (2020). Computational Science and Its Applications—ICCSA 2020, Proceedings of the 20th International Conference, Cagliari, Italy, 1–4 July 2020, Springer International Publishing.
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|