{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:19:38Z","timestamp":1782231578823,"version":"3.54.5"},"reference-count":290,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,5,9]],"date-time":"2022-05-09T00:00:00Z","timestamp":1652054400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers and Electronics in Agriculture"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1016\/j.compag.2022.107017","type":"journal-article","created":{"date-parts":[[2022,5,18]],"date-time":"2022-05-18T07:35:09Z","timestamp":1652859309000},"page":"107017","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":621,"special_numbering":"C","title":["Drones in agriculture: A review and bibliometric analysis"],"prefix":"10.1016","volume":"198","author":[{"given":"Abderahman","family":"Rejeb","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1620-8872","authenticated-orcid":false,"given":"Alireza","family":"Abdollahi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karim","family":"Rejeb","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Horst","family":"Treiblmaier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.compag.2022.107017_b0005","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.isprsjprs.2015.08.002","article-title":"Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: from camera calibration to quality assurance","volume":"108","author":"Aasen","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0010","first-page":"37","article-title":"Development of pattern recognition algorithm for automatic bird detection from unmanned aerial vehicle imagery","volume":"65","author":"Abd-Elrahman","year":"2005","journal-title":"Survey. Land Inform. Sci."},{"issue":"21","key":"10.1016\/j.compag.2022.107017_b0015","doi-asserted-by":"crossref","first-page":"12011","DOI":"10.3390\/su132112011","article-title":"Wireless sensor networks in agriculture: insights from bibliometric analysis","volume":"13","author":"Abdollahi","year":"2021","journal-title":"Sustainability"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0020","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/s00271-018-0613-9","article-title":"Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration","volume":"37","author":"Aboutalebi","year":"2019","journal-title":"Irrig. Sci."},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0025","doi-asserted-by":"crossref","DOI":"10.3390\/rs9111110","article-title":"Hyperspectral imaging: a review on UAV-based sensors, data processing and applications for agriculture and forestry","volume":"9","author":"Ad\u00e3o","year":"2017","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0030","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.biosystemseng.2015.01.008","article-title":"Multi-temporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop","volume":"132","author":"Ag\u00fcera Vega","year":"2015","journal-title":"Biosyst. Eng."},{"issue":"8\u201310","key":"10.1016\/j.compag.2022.107017_b0035","doi-asserted-by":"crossref","first-page":"3113","DOI":"10.1080\/01431161.2017.1285085","article-title":"Generation of accurate digital elevation models from UAV acquired low percentage overlapping images","volume":"38","author":"Ajayi","year":"2017","journal-title":"Int. J. Remote Sens."},{"issue":"12","key":"10.1016\/j.compag.2022.107017_b0040","doi-asserted-by":"crossref","first-page":"16398","DOI":"10.3390\/rs71215841","article-title":"Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data","volume":"7","author":"Ali","year":"2015","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2021.102505","article-title":"Green internet of things using UAVs in B5G networks: A review of applications and strategies","volume":"117","author":"Alsamhi","year":"2021","journal-title":"Ad. Hoc. Netw."},{"key":"10.1016\/j.compag.2022.107017_b0050","series-title":"20th IEEE Mediterranean Electrotechnical Conference","article-title":"Drones for Sheep Livestock Monitoring","author":"Al-Thani","year":"2020"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0055","doi-asserted-by":"crossref","first-page":"410","DOI":"10.3390\/rs11040410","article-title":"UAV-based high throughput phenotyping in citrus utilizing multispectral imaging and artificial intelligence","volume":"11","author":"Ampatzidis","year":"2019","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105457","article-title":"Agroview: Cloud-based application to process, analyze and visualize UAV-collected data for precision agriculture applications utilizing artificial intelligence","volume":"174","author":"Ampatzidis","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b0065","doi-asserted-by":"crossref","first-page":"36699","DOI":"10.1109\/ACCESS.2021.3051196","article-title":"Big data and machine learning with hyperspectral information in agriculture","volume":"9","author":"Ang","year":"2021","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.animal.2021.100429","article-title":"Review: precision Livestock Farming technologies in pasture-based livestock systems","volume":"16","author":"Aquilani","year":"2022","journal-title":"Animal"},{"issue":"12","key":"10.1016\/j.compag.2022.107017_b0075","doi-asserted-by":"crossref","first-page":"Article 12","DOI":"10.3390\/agronomy10121989","article-title":"Trends on advanced information and communication technologies for improving agricultural productivities: a bibliometric analysis","volume":"10","author":"Armenta-Medina","year":"2020","journal-title":"Agronomy"},{"key":"10.1016\/j.compag.2022.107017_b0080","first-page":"329","article-title":"The flying gator: towards aerial robotics in occam-\u03c0","volume":"2011","author":"Armstrong","year":"2011","journal-title":"Commun. Process Architect."},{"key":"10.1016\/j.compag.2022.107017_b0085","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.jbusres.2020.08.043","article-title":"Intellectual structure of consumer complaining behavior (CCB) research: A bibliometric analysis","volume":"122","author":"Arora","year":"2021","journal-title":"J. Business Res."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0090","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.3390\/app12031047","article-title":"A comprehensive survey of the recent studies with UAV for precision agriculture in open fields and greenhouses","volume":"12","author":"Aslan","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0095","doi-asserted-by":"crossref","unstructured":"Atkinson, J. A., Jackson, R. J., Bentley, A. R., Ober, E., & Wells, D. M. (2018). Field Phenotyping for the Future. In Annual Plant Reviews online (pp. 719\u2013736). John Wiley & Sons, Ltd. doi: 10.1002\/9781119312994.apr0651.","DOI":"10.1002\/9781119312994.apr0651"},{"key":"10.1016\/j.compag.2022.107017_b0100","series-title":"Unmanned Aircraft Systems: UAVS Design, Development and Deployment","article-title":"Unmanned Aircraft Systems: UAVS Design, Development and Deployment","author":"Austin","year":"2010"},{"key":"10.1016\/j.compag.2022.107017_b0105","article-title":"UAV-based remote sensing in plant stress imagine using high-resolution thermal sensor for digital agriculture practices: a meta-review","author":"Awais","year":"2022","journal-title":"Int. J. Environ. Sci. Technol."},{"key":"10.1016\/j.compag.2022.107017_b0110","first-page":"1","article-title":"Smart farming: Opportunities, challenges and technology enablers. 2018 IoT Vertical and","author":"Bacco","year":"2018","journal-title":"Topical Summit on Agriculture - Tuscany (IOT Tuscany)"},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0115","doi-asserted-by":"crossref","first-page":"1690","DOI":"10.3390\/rs10111690","article-title":"Deep learning with unsupervised data labeling for weed detection in line crops in UAV images","volume":"10","author":"Bah","year":"2018","journal-title":"Remote Sensing"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0120","doi-asserted-by":"crossref","first-page":"829","DOI":"10.2307\/2657504","article-title":"Normative versus social constructivist processes in the allocation of citations: a network-analytic model","volume":"63","author":"Baldi","year":"1998","journal-title":"Am. Sociol. Rev."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0125","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1007\/s00271-012-0382-9","article-title":"Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV)","volume":"30","author":"Baluja","year":"2012","journal-title":"Irrig. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0130","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.plantsci.2015.07.010","article-title":"Next generation breeding","volume":"242","author":"Barabaschi","year":"2016","journal-title":"Plant Sci."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0135","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1177\/0030727018781876","article-title":"Perspectives on the use of unmanned aerial systems to monitor cattle","volume":"47","author":"Barbedo","year":"2018","journal-title":"Outlook Agric."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0140","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1127\/pfg\/2015\/0256","article-title":"Low-weight and UAV-based hyperspectral full-frame cameras for monitoring crops: Spectral comparison with portable spectroradiometer measurements","volume":"2015","author":"Bareth","year":"2015","journal-title":"Photogrammetrie, Fernerkundung, Geoinformation"},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0145","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1002\/rob.20403","article-title":"Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots","volume":"28","author":"Barrientos","year":"2011","journal-title":"J. Field Rob."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0150","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1017\/S0373463321000825","article-title":"A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture","volume":"75","author":"Basiri","year":"2022","journal-title":"J. Navig."},{"key":"10.1016\/j.compag.2022.107017_b0155","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2018\/7425720","article-title":"The state-of-the-art of knowledge-intensive agriculture: a review on applied sensing systems and data analytics","volume":"2018","author":"Basnet","year":"2018","journal-title":"J. Sens."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0160","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1127\/1432-8364\/2013\/0200","article-title":"UAV-based imaging for multi-temporal, very high resolution crop surface models to monitor crop growth variability","volume":"2013","author":"Bendig","year":"2013","journal-title":"Photogrammetrie, Fernerkundung, Geoinformation"},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0165","doi-asserted-by":"crossref","first-page":"10395","DOI":"10.3390\/rs61110395","article-title":"Estimating biomass of barley using crop surface models (CSMs) derived from UAV-based RGB imaging","volume":"6","author":"Bendig","year":"2014","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0170","first-page":"79","article-title":"Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley","volume":"39","author":"Bendig","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0175","doi-asserted-by":"crossref","first-page":"2380","DOI":"10.1016\/j.rse.2009.06.018","article-title":"Mapping canopy conductance and CWSI in olive orchards using high resolution thermal remote sensing imagery","volume":"113","author":"Berni","year":"2009","journal-title":"Remote Sens. Environ."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0180","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TGRS.2008.2010457","article-title":"Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle","volume":"47","author":"Berni","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0185","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.tifs.2019.11.002","article-title":"Internet of Things in food safety: Literature review and a bibliometric analysis","volume":"94","author":"Bouzembrak","year":"2019","journal-title":"Trends Food Sci. Technol."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0190","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/MCOM.2017.1600528","article-title":"IoT in agriculture: Designing a Europe-wide large-scale pilot","volume":"55","author":"Brewster","year":"2017","journal-title":"IEEE Commun. Mag."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0195","doi-asserted-by":"crossref","first-page":"81","DOI":"10.3390\/drones3040081","article-title":"Multi-sensor UAV tracking of individual seedlings and seedling communities at millimetre accuracy","volume":"3","author":"Buters","year":"2019","journal-title":"Drones"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0200","doi-asserted-by":"crossref","first-page":"4026","DOI":"10.3390\/rs70404026","article-title":"Evaluating multispectral images and vegetation indices for precision farming applications from UAV images","volume":"7","author":"Candiago","year":"2015","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105331","article-title":"Monitoring of sugar beet growth indicators using wide-dynamic-range vegetation index (WDRVI) derived from UAV multispectral images","volume":"171","author":"Cao","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0210","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1111\/j.1741-6248.2007.00092.x","article-title":"Evolution of the intellectual structure of family business literature: a bibliometric study of FBR","volume":"20","author":"Casillas","year":"2007","journal-title":"Family Business Rev."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0215","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s13007-019-0418-8","article-title":"Dynamic monitoring of biomass of rice under different nitrogen treatments using a lightweight UAV with dual image-frame snapshot cameras","volume":"15","author":"Cen","year":"2019","journal-title":"Plant Methods"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0220","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1007\/s42452-019-1901-6","article-title":"Securing sustainability in Indian agriculture through civilian UAV: a responsible innovation perspective","volume":"2","author":"Chamuah","year":"2019","journal-title":"SN Appl. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0225","doi-asserted-by":"crossref","DOI":"10.1016\/j.jrt.2022.100025","article-title":"Responsible governance of civilian unmanned aerial vehicle (UAV) innovations for Indian crop insurance applications","volume":"9","author":"Chamuah","year":"2022","journal-title":"J. Responsible Technol."},{"key":"10.1016\/j.compag.2022.107017_b0230","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.agwat.2019.02.017","article-title":"Applying high-resolution visible-channel aerial imaging of crop canopy to precision irrigation management","volume":"216","author":"Chen","year":"2019","journal-title":"Agric. Water Manag."},{"key":"10.1016\/j.compag.2022.107017_b0235","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2016.12.007","article-title":"Lightweight UAV with on-board photogrammetry and single-frequency GPS positioning for metrology applications","volume":"127","author":"Daakir","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0240","series-title":"Proceedings of the 2nd ACM MobiCom Workshop on Drone Assisted Wireless Communications for 5G and Beyond","first-page":"31","article-title":"Blockchain-based IoT platform for autonomous drone operations management","author":"Dawaliby","year":"2020"},{"key":"10.1016\/j.compag.2022.107017_b0245","series-title":"How to write and publish a scientific paper","author":"Day","year":"1998"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0250","doi-asserted-by":"crossref","first-page":"56","DOI":"10.3390\/rs12010056","article-title":"Mapping cynodon dactylon infesting cover crops with an automatic decision tree-OBIA procedure and UAV imagery for precision viticulture","volume":"12","author":"de Castro","year":"2020","journal-title":"Remote Sensing"},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0255","doi-asserted-by":"crossref","DOI":"10.3390\/rs10020285","article-title":"An automatic random forest-OBIA algorithm for early weed mapping between and within crop rows using UAV imagery","volume":"10","author":"de Castro","year":"2018","journal-title":"Remote Sensing"},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0260","first-page":"350","article-title":"Automated Measurement of Plant Height of Wheat Genotypes Using a DSM Derived from UAV Imagery","volume":"2","author":"Demir","year":"2018","journal-title":"Proceedings"},{"issue":"20","key":"10.1016\/j.compag.2022.107017_b0265","doi-asserted-by":"crossref","first-page":"7132","DOI":"10.3390\/app10207132","article-title":"Lightweight semantic segmentation network for real-time weed mapping using unmanned aerial vehicles","volume":"10","author":"Deng","year":"2020","journal-title":"Appl. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0270","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.isprsjprs.2018.09.008","article-title":"UAV-based multispectral remote sensing for precision agriculture: a comparison between different cameras","volume":"146","author":"Deng","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0275","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecolind.2021.108517","article-title":"Machine learning and remote sensing techniques applied to estimate soil indicators \u2013 review","volume":"135","author":"Diaz-Gonzalez","year":"2022","journal-title":"Ecol. Ind."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0280","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.3390\/rs70404213","article-title":"High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: application in breeding trials","volume":"7","author":"D\u00edaz-Varela","year":"2015","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0285","doi-asserted-by":"crossref","first-page":"102010","DOI":"10.1016\/j.jairtraman.2020.102010","article-title":"Airport capacity management: a review and bibliometric analysis","volume":"91","author":"Dixit","year":"2021","journal-title":"J. Air Transp. Manag."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0290","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1007\/s11119-019-09646-w","article-title":"Using RapidEye imagery to identify within-field variability of crop growth and yield in Ontario, Canada","volume":"20","author":"Dong","year":"2019","journal-title":"Precision Agric."},{"key":"10.1016\/j.compag.2022.107017_b0295","series-title":"Agricultural Informatics: Automation Using the IoT and Machine Learning","first-page":"67","article-title":"Application of agricultural drones and iot to understand food supply chain during post COVID-19","author":"Dutta","year":"2021"},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0300","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s11192-009-0146-3","article-title":"Software survey: VOSviewer, a computer program for bibliometric mapping","volume":"84","author":"van Eck","year":"2009","journal-title":"Scientometrics"},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0305","doi-asserted-by":"crossref","first-page":"3758","DOI":"10.1109\/JIOT.2018.2844296","article-title":"An overview of Internet of Things (IoT) and data analytics in agriculture: benefits and challenges","volume":"5","author":"Elijah","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.compag.2022.107017_b0310","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.compag.2019.02.011","article-title":"Validation of agronomic UAV and field measurements for tomato varieties","volume":"158","author":"Enciso","year":"2019","journal-title":"Comput. Electron. Agric."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0315","doi-asserted-by":"crossref","first-page":"961","DOI":"10.3390\/rs9090961","article-title":"High resolution multispectral and thermal remote sensing-based water stress assessment in subsurface irrigated grapevines","volume":"9","author":"Espinoza","year":"2017","journal-title":"Remote Sensing"},{"issue":"20","key":"10.1016\/j.compag.2022.107017_b0320","doi-asserted-by":"crossref","first-page":"3312","DOI":"10.3390\/rs12203312","article-title":"Utilizing hyperspectral remote sensing for soil gradation","volume":"12","author":"Ewing","year":"2020","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0325","doi-asserted-by":"crossref","first-page":"514","DOI":"10.3390\/rs12030514","article-title":"Multi-scale evaluation of drone-based multispectral surface reflectance and vegetation indices in operational conditions","volume":"12","author":"Fawcett","year":"2020","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0330","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1007\/s11277-019-06496-7","article-title":"Study of wireless communication technologies on Internet of Things for precision agriculture","volume":"108","author":"Feng","year":"2019","journal-title":"Wireless Pers. Commun."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0335","doi-asserted-by":"crossref","first-page":"1899","DOI":"10.1007\/s11192-013-1172-8","article-title":"The transaction costs theory in international business research: a bibliometric study over three decades","volume":"98","author":"Ferreira","year":"2014","journal-title":"Scientometrics"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0340","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1071\/CP08347","article-title":"Advances in precision agriculture in south-eastern Australia. I. a regression methodology to simulate spatial variation in cereal yields using farmers\u2019 historical paddock yields and normalised difference vegetation index","volume":"60","author":"Fisher","year":"2009","journal-title":"Crop Pasture Sci."},{"issue":"7553","key":"10.1016\/j.compag.2022.107017_b0345","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1038\/nature14542","article-title":"Science, technology and the future of small autonomous drones","volume":"521","author":"Floreano","year":"2015","journal-title":"Nature"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0350","doi-asserted-by":"crossref","first-page":"718","DOI":"10.1109\/JAS.2021.1003925","article-title":"Internet of things for the future of smart agriculture: a comprehensive survey of emerging technologies","volume":"8","author":"Friha","year":"2021","journal-title":"IEEE CAA J. Autom. Sinica"},{"issue":"10","key":"10.1016\/j.compag.2022.107017_b0355","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.3390\/rs11101157","article-title":"Fig plant segmentation from aerial images using a deep convolutional encoder-decoder network","volume":"11","author":"Fuentes-Pacheco","year":"2019","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0360","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.agwat.2015.01.020","article-title":"UAVs challenge to assess water stress for sustainable agriculture","volume":"153","author":"Gago","year":"2015","journal-title":"Agric. Water Manag."},{"key":"10.1016\/j.compag.2022.107017_b0365","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.agwat.2018.06.002","article-title":"Thermal imaging at plant level to assess the crop-water status in almond trees (cv. Guara) under deficit irrigation strategies","volume":"208","author":"Garc\u00eda-Tejero","year":"2018","journal-title":"Agric. Water Manag."},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0370","doi-asserted-by":"crossref","first-page":"472","DOI":"10.3390\/rs9050472","article-title":"Surface reflectance and sun-induced fluorescence spectroscopy measurements using a small hyperspectral UAS","volume":"9","author":"Garzonio","year":"2017","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0375","doi-asserted-by":"crossref","first-page":"105385","DOI":"10.1016\/j.compag.2020.105385","article-title":"An automatic method for weed mapping in oat fields based on UAV imagery","volume":"173","author":"Ga\u0161parovi\u0107","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"5967","key":"10.1016\/j.compag.2022.107017_b0380","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1126\/science.1183899","article-title":"Precision agriculture and food security","volume":"327","author":"Gebbers","year":"2010","journal-title":"Science"},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0385","doi-asserted-by":"crossref","first-page":"10335","DOI":"10.3390\/rs61110335","article-title":"Combined spectral and spatial modeling of corn yield based on aerial images and crop surface models acquired with an unmanned aircraft system","volume":"6","author":"Geipel","year":"2014","journal-title":"Remote Sensing"},{"issue":"24","key":"10.1016\/j.compag.2022.107017_b0390","doi-asserted-by":"crossref","first-page":"29824","DOI":"10.1007\/s11356-020-09283-1","article-title":"Sustainable design for users: a literature review and bibliometric analysis","volume":"27","author":"Geng","year":"2020","journal-title":"Environ. Sci. Pollut. Res."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0395","doi-asserted-by":"crossref","first-page":"3140","DOI":"10.1109\/JSTARS.2015.2406339","article-title":"Generation of spectral-temporal response surfaces by combining multispectral satellite and hyperspectral UAV imagery for precision agriculture applications","volume":"8","author":"Gevaert","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0400","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/JOEUC.2017100101","article-title":"IoT based agriculture as a cloud and big data service: the beginning of digital India","volume":"29","author":"Gill","year":"2017","journal-title":"J. Org. and End User Comput. (JOEUC)"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0405","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1023\/A:1023619503005","article-title":"Co-citation analysis and the search for invisible colleges: a methodological evaluation","volume":"57","author":"Gm\u00fcr","year":"2006","journal-title":"Scientometrics"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0410","doi-asserted-by":"crossref","DOI":"10.3390\/rs9060544","article-title":"Digital counts of maize plants by Unmanned Aerial Vehicles (UAVs)","volume":"9","author":"Gn\u00e4dinger","year":"2017","journal-title":"Remote Sensing"},{"issue":"1\u20134","key":"10.1016\/j.compag.2022.107017_b0415","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1007\/s10846-009-9371-5","article-title":"A Rotary-wing unmanned air vehicle for aquatic weed surveillance and management","volume":"57","author":"G\u00f6kto\u01e7an","year":"2010","journal-title":"J. Intell. Robotic Syst.: Theor. Appl."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0420","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/s11119-013-9335-4","article-title":"Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat","volume":"15","author":"G\u00f3mez-Cand\u00f3n","year":"2014","journal-title":"Precis. Agric."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0425","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1007\/s11119-016-9449-6","article-title":"Field phenotyping of water stress at tree scale by UAV-sensed imagery: new insights for thermal acquisition and calibration","volume":"17","author":"G\u00f3mez-Cand\u00f3n","year":"2016","journal-title":"Precis. Agric."},{"key":"10.1016\/j.compag.2022.107017_b0430","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.agrformet.2014.08.003","article-title":"Applicability and limitations of using the crop water stress index as an indicator of water deficits in citrus orchards","volume":"198\u2013199","author":"Gonzalez-Dugo","year":"2014","journal-title":"Agric. For. Meteorol."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0435","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1007\/s11119-013-9322-9","article-title":"Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard","volume":"14","author":"Gonzalez-Dugo","year":"2013","journal-title":"Precis. Agric."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0440","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1111\/ijcs.12605","article-title":"Financial literacy: A systematic review and bibliometric analysis","volume":"45","author":"Goyal","year":"2021","journal-title":"Int. J. Consumer Studies"},{"key":"10.1016\/j.compag.2022.107017_b0445","first-page":"1207","article-title":"The photogrammetric potential of low-cost uavs in forestry and agriculture","volume":"37","author":"Grenzd\u00f6rffer","year":"2008","journal-title":"International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives"},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0450","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3390\/rs11020112","article-title":"Assessing correlation of high-resolution NDVI with fertilizer application level and yield of rice and wheat crops using small UAVs","volume":"11","author":"Guan","year":"2019","journal-title":"Remote Sensing"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0455","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s10551-012-1240-7","article-title":"Management research and religion: a citation analysis","volume":"112","author":"Gundolf","year":"2013","journal-title":"J. Bus. Ethics"},{"key":"10.1016\/j.compag.2022.107017_b0460","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105343","article-title":"CFD simulation and experimental verification of the spatial and temporal distributions of the downwash airflow of a quad-rotor agricultural UAV in hover","volume":"172","author":"Guo","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0465","doi-asserted-by":"crossref","DOI":"10.1186\/s13007-016-0134-6","article-title":"Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries","volume":"12","author":"Haghighattalab","year":"2016","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2022.107017_b0470","doi-asserted-by":"crossref","unstructured":"Hakala, T., Honkavaara, E., Saari, H., M\u00e4kynen, J., Kaivosoja, J., Pesonen, L., & P\u00f6l\u00f6nen, I., 2013. Spectral imaging from UAVs under varying illumination conditions. In G. G. Bill R. (Ed.), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences\u2014ISPRS Archives (Vol. 40, Issue 1W2, pp. 189\u2013194). International Society for Photogrammetry and Remote Sensing. https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-848875632.","DOI":"10.5194\/isprsarchives-XL-1-W2-189-2013"},{"key":"10.1016\/j.compag.2022.107017_b0475","article-title":"Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches","volume":"89","author":"Hamylton","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"8","key":"10.1016\/j.compag.2022.107017_b0480","doi-asserted-by":"crossref","first-page":"4511","DOI":"10.3390\/su13084511","article-title":"Smart farming through responsible leadership in bangladesh: possibilities, opportunities, and beyond","volume":"13","author":"Haque","year":"2021","journal-title":"Sustainability"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0485","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1111\/j.1749-8198.2010.00381.x","article-title":"Small-scale remotely piloted vehicles in environmental research","volume":"4","author":"Hardin","year":"2010","journal-title":"Geography Compass"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0490","doi-asserted-by":"crossref","first-page":"99","DOI":"10.2747\/1548-1603.48.1.99","article-title":"Small-scale unmanned aerial vehicles in environmental remote sensing: challenges and opportunities","volume":"48","author":"Hardin","year":"2011","journal-title":"GISci. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0495","series-title":"Agricultural Internet of Things: technologies and applications","author":"He","year":"2021"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0500","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.compag.2004.02.006","article-title":"Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support","volume":"44","author":"Herwitz","year":"2004","journal-title":"Comput. Electron. Agric."},{"issue":"12","key":"10.1016\/j.compag.2022.107017_b0505","doi-asserted-by":"crossref","DOI":"10.3390\/rs8121031","article-title":"High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing","volume":"8","author":"Holman","year":"2016","journal-title":"Remote Sensing"},{"issue":"10","key":"10.1016\/j.compag.2022.107017_b0510","doi-asserted-by":"crossref","first-page":"5006","DOI":"10.3390\/rs5105006","article-title":"Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture","volume":"5","author":"Honkavaara","year":"2013","journal-title":"Remote Sensing"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0515","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1109\/JIOT.2016.2612119","article-title":"Low-altitude unmanned aerial vehicles-based internet of things services: comprehensive survey and future perspectives","volume":"3","author":"Hossein Motlagh","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.compag.2022.107017_b0520","series-title":"2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems","first-page":"3309","article-title":"Combined optic-flow and stereo-based navigation of urban canyons for a UAV","author":"Hrabar","year":"2005"},{"key":"10.1016\/j.compag.2022.107017_b0525","article-title":"A Creative IoT agriculture platform for cloud fog computing","volume":"28","author":"Hsu","year":"2020","journal-title":"Sustain. Comput. Inf. Syst."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0530","doi-asserted-by":"crossref","first-page":"e0196302","DOI":"10.1371\/journal.pone.0196302","article-title":"A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery","volume":"13","author":"Huang","year":"2018","journal-title":"PLoS ONE"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0535","doi-asserted-by":"crossref","first-page":"3446","DOI":"10.1080\/01431161.2019.1706112","article-title":"Deep learning versus Object-based Image Analysis (OBIA) in weed mapping of UAV imagery","volume":"41","author":"Huang","year":"2020","journal-title":"Int. J. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0540","article-title":"Deep color calibration for UAV imagery in crop monitoring using semantic style transfer with local to global attention","volume":"104","author":"Huang","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0545","first-page":"1","article-title":"Development and prospect of unmanned aerial vehicle technologies for agricultural production management","volume":"6","author":"Huang","year":"2013","journal-title":"Int. J. Agric. Biol. Eng."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0550","doi-asserted-by":"crossref","first-page":"803","DOI":"10.13031\/2013.29229","article-title":"Development of a spray system for an unmanned aerial vehicle platform","volume":"25","author":"Huang","year":"2009","journal-title":"Appl. Eng. Agric."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0555","doi-asserted-by":"crossref","first-page":"290","DOI":"10.3390\/rs2010290","article-title":"Acquisition of NIR-green-blue digital photographs from unmanned aircraft for crop monitoring","volume":"2","author":"Hunt","year":"2010","journal-title":"Remote Sensing"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0560","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1080\/00380768.2020.1738899","article-title":"Satellite- and drone-based remote sensing of crops and soils for smart farming\u2013a review","volume":"66","author":"Inoue","year":"2020","journal-title":"Soil Sci. Plant Nutr."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0565","doi-asserted-by":"crossref","first-page":"1821","DOI":"10.3390\/su13041821","article-title":"A review of applications and communication technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) based sustainable smart farming","volume":"13","author":"Islam","year":"2021","journal-title":"Sustainability"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0570","doi-asserted-by":"crossref","first-page":"465","DOI":"10.3390\/rs8060465","article-title":"Assessing the accuracy of high resolution digital surface models computed by PhotoScan\u00ae and MicMac\u00ae in sub-optimal survey conditions","volume":"8","author":"Jaud","year":"2016","journal-title":"Remote Sensing"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0575","doi-asserted-by":"crossref","DOI":"10.1186\/s13007-017-0205-3","article-title":"Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling","volume":"13","author":"Jim\u00e9nez-Brenes","year":"2017","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2022.107017_b0580","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.rse.2017.06.007","article-title":"Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery","volume":"198","author":"Jin","year":"2017","journal-title":"Remote Sens. Environ."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0585","doi-asserted-by":"crossref","first-page":"8929","DOI":"10.1007\/s10586-018-2022-5","article-title":"Agricultural product monitoring system supported by cloud computing","volume":"22","author":"Jinbo","year":"2019","journal-title":"Cluster Comput."},{"key":"10.1016\/j.compag.2022.107017_b0590","unstructured":"Ju, C., & Son, H. I. 2018a. Performance evaluation of multiple UAV systems for remote sensing in agriculture. Proceedings of the Workshop on Robotic Vision and Action in Agriculture at the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 21\u201326."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0595","doi-asserted-by":"crossref","first-page":"162","DOI":"10.3390\/electronics7090162","article-title":"Multiple UAV systems for agricultural applications: control, implementation, and evaluation","volume":"7","author":"Ju","year":"2018","journal-title":"Electronics"},{"key":"10.1016\/j.compag.2022.107017_b0600","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.copbio.2020.09.003","article-title":"The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems","volume":"70","author":"Jung","year":"2021","journal-title":"Curr. Opin. Biotechnol."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0605","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.1094\/PDIS-08-18-1373-RE","article-title":"An improved crop scouting technique incorporating unmanned aerial vehicle\u2013assisted multispectral crop imaging into conventional scouting practice for gummy stem blight in watermelon","volume":"103","author":"Kalischuk","year":"2019","journal-title":"Plant Dis."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0610","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1007\/s10796-017-9810-y","article-title":"Advances in social media research: past, present and future","volume":"20","author":"Kapoor","year":"2018","journal-title":"Inform. Syst. Front."},{"issue":"20","key":"10.1016\/j.compag.2022.107017_b0615","doi-asserted-by":"crossref","first-page":"3305","DOI":"10.3390\/rs12203305","article-title":"VddNet: vine disease detection network based on multispectral images and depth map","volume":"12","author":"Kerkech","year":"2020","journal-title":"Remote Sensing"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0620","doi-asserted-by":"crossref","DOI":"10.3390\/rs11040436","article-title":"Comparison of satellite and UAV-based multispectral imagery for vineyard variability assessment","volume":"11","author":"Khaliq","year":"2019","journal-title":"Remote Sensing"},{"issue":"10","key":"10.1016\/j.compag.2022.107017_b0625","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.3390\/s20102990","article-title":"IoT-blockchain enabled optimized provenance system for food industry 4.0 using advanced deep learning","volume":"20","author":"Khan","year":"2020","journal-title":"Sensors"},{"key":"10.1016\/j.compag.2022.107017_b0630","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2021\/5541859","article-title":"Image-based detection of plant diseases: from classical machine learning to deep learning journey","volume":"2021","author":"Khan","year":"2021","journal-title":"Wireless Commun. Mobile Comput."},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0635","doi-asserted-by":"crossref","first-page":"e0251008","DOI":"10.1371\/journal.pone.0251008","article-title":"A novel semi-supervised framework for UAV based crop\/weed classification","volume":"16","author":"Khan","year":"2021","journal-title":"PLoS ONE"},{"key":"10.1016\/j.compag.2022.107017_b0640","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.compag.2017.05.001","article-title":"An overview of current and potential applications of thermal remote sensing in precision agriculture","volume":"139","author":"Khanal","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b0645","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.compag.2018.12.039","article-title":"Evolution of Internet of Things (IoT) and its significant impact in the field of Precision Agriculture","volume":"157","author":"Khanna","year":"2019","journal-title":"Comput. Electron. Agric."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0650","doi-asserted-by":"crossref","first-page":"631","DOI":"10.3390\/su8070631","article-title":"Employee engagement for sustainable organizations: keyword analysis using social network analysis and burst detection approach","volume":"8","author":"Kim","year":"2016","journal-title":"Sustainability"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0655","doi-asserted-by":"crossref","first-page":"1366","DOI":"10.3390\/rs10091366","article-title":"Integration of terrestrial and drone-borne hyperspectral and photogrammetric sensing methods for exploration mapping and mining monitoring","volume":"10","author":"Kirsch","year":"2018","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b0660","article-title":"Corn plant counting using deep learning and UAV images","volume":"1\u20135","author":"Kitano","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0665","doi-asserted-by":"crossref","first-page":"858","DOI":"10.3390\/rs13050858","article-title":"Automated machine learning for high-throughput image-based plant phenotyping","volume":"13","author":"Koh","year":"2021","journal-title":"Remote Sensing"},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0670","doi-asserted-by":"crossref","DOI":"10.1088\/1742-6596\/1515\/5\/052068","article-title":"Modern technological trends in the development of the ecosystem of cargo UAVs","volume":"1515","author":"Kovalev","year":"2020","journal-title":"J. Phys. Conf. Ser."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0675","doi-asserted-by":"crossref","first-page":"41","DOI":"10.3390\/drones5020041","article-title":"Visual SLAM for indoor livestock and farming using a small drone with a monocular camera: a feasibility study","volume":"5","author":"Krul","year":"2021","journal-title":"Drones"},{"key":"10.1016\/j.compag.2022.107017_b0680","series-title":"INES 2018 - IEEE 22nd International Conference on Intelligent Engineering Systems","first-page":"000353","article-title":"Survey of drones for agriculture automation from planting to harvest","author":"Kulbacki","year":"2018"},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b0685","doi-asserted-by":"crossref","first-page":"4015","DOI":"10.3390\/s18114015","article-title":"UAV IoT framework views and challenges: towards protecting drones as \u201cThings\u201d","volume":"18","author":"Lagkas","year":"2018","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0690","doi-asserted-by":"crossref","first-page":"4","DOI":"10.2747\/1548-1603.48.1.4","article-title":"Image processing and classification procedures for analysis of sub-decimeter imagery acquired with an unmanned aircraft over arid rangelands","volume":"48","author":"Laliberte","year":"2011","journal-title":"GISci. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0695","series-title":"ASPRS Annual Conference Proceedings","article-title":"Unmanned aerial vehicles for rangeland mapping and monitoring: a comparison of two systems","author":"Laliberte","year":"2007"},{"issue":"sup1","key":"10.1016\/j.compag.2022.107017_b0700","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1080\/22797254.2020.1793687","article-title":"An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: Using Rumex obtusifolius as a case study","volume":"54","author":"Lam","year":"2021","journal-title":"Eur. J. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0705","article-title":"Adoption, profitability, and making better use of precision farming data. Working paper","author":"Lambert","year":"2004","journal-title":"Purdue University"},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0710","doi-asserted-by":"crossref","first-page":"3557","DOI":"10.3390\/s8053557","article-title":"Assessment of unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots","volume":"8","author":"Lelong","year":"2008","journal-title":"Sensors"},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b0715","doi-asserted-by":"crossref","DOI":"10.1177\/1550147720917065","article-title":"Design of smart agriculture based on big data and Internet of things","volume":"16","author":"Li","year":"2020","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"10.1016\/j.compag.2022.107017_b0720","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.ecolind.2016.03.036","article-title":"Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system","volume":"67","author":"Li","year":"2016","journal-title":"Ecol. Ind."},{"issue":"8","key":"10.1016\/j.compag.2022.107017_b0725","doi-asserted-by":"crossref","first-page":"2674","DOI":"10.3390\/s18082674","article-title":"Machine learning in agriculture: a review","volume":"18","author":"Liakos","year":"2018","journal-title":"Sensors"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0730","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s13007-015-0048-8","article-title":"Remote, aerial phenotyping of maize traits with a mobile multi-sensor approach","volume":"11","author":"Liebisch","year":"2015","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2022.107017_b0735","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2020.534853","article-title":"Sorghum panicle detection and counting using unmanned aerial system images and deep learning","volume":"11","author":"Lin","year":"2020","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2022.107017_b0740","doi-asserted-by":"crossref","first-page":"37050","DOI":"10.1109\/ACCESS.2019.2903720","article-title":"Internet of Things monitoring system of modern eco-agriculture based on cloud computing","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0745","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1365-3180.2010.00829.x","article-title":"Weed detection for site-specific weed management: mapping and real-time approaches","volume":"51","author":"L\u00f3pez-Granados","year":"2011","journal-title":"Weed Res."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0750","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13593-016-0405-7","article-title":"Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery","volume":"36","author":"L\u00f3pez-Granados","year":"2016","journal-title":"Agron. Sustain. Dev."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0755","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s11119-015-9415-8","article-title":"Early season weed mapping in sunflower using UAV technology: variability of herbicide treatment maps against weed thresholds","volume":"17","author":"L\u00f3pez-Granados","year":"2016","journal-title":"Precis. Agric."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0760","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1002\/rob.21508","article-title":"HyperUAS - imaging spectroscopy from a multirotor unmanned aircraft system","volume":"31","author":"Lucieer","year":"2014","journal-title":"J. Field Rob."},{"key":"10.1016\/j.compag.2022.107017_b0765","unstructured":"Lumme, J., Karjalainen, M., Kaartinen, H., Kukko, A., Hyypp\u00e4, J., Hyypp\u00e4, H., Jaakkola, A., & Kleemola, J., 2008. Terrestrial laser scanning of agricultural crops. In J. J. Chen J. Maas H\u2013G. (Ed.), International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences\u2014ISPRS Archives (Vol. 37, pp. 563\u2013566). International Society for Photogrammetry and Remote Sensing. https:\/\/www.scopus.com\/inward\/record.uri?eid=2-s2.0-84919356328&partnerID=40&md5=574b802131a99d16318ce619a01ca1bf."},{"key":"10.1016\/j.compag.2022.107017_b0770","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.isprsjprs.2017.06.001","article-title":"A review of supervised object-based land-cover image classification","volume":"130","author":"Ma","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b0775","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.tplants.2018.11.007","article-title":"Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture","volume":"24","author":"Maes","year":"2019","journal-title":"Trends Plant Sci."},{"key":"10.1016\/j.compag.2022.107017_b0780","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.isprsjprs.2017.10.011","article-title":"Unmanned aerial system (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine","volume":"134","author":"Maimaitijiang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0785","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.3390\/rs12091357","article-title":"Crop monitoring using satellite\/UAV data fusion and machine learning","volume":"12","author":"Maimaitijiang","year":"2020","journal-title":"Remote Sensing"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0790","doi-asserted-by":"crossref","first-page":"641","DOI":"10.3390\/rs10040641","article-title":"On the use of unmanned aerial systems for environmental monitoring","volume":"10","author":"Manfreda","year":"2018","journal-title":"Remote Sensing"},{"issue":"1\u20132","key":"10.1016\/j.compag.2022.107017_b0795","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1300\/J123v35n01_03","article-title":"Citations to women\u2019s studies journals in dissertations, 1989 and 1994","volume":"35","author":"Marinko","year":"1998","journal-title":"The Serials Librarian"},{"key":"10.1016\/j.compag.2022.107017_b0800","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2021.102596","article-title":"Resource management in UAV-assisted wireless networks: an optimization perspective","volume":"121","author":"Masroor","year":"2021","journal-title":"Ad Hoc Netw."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0805","doi-asserted-by":"crossref","first-page":"116","DOI":"10.3390\/agriculture8070116","article-title":"Practical applications of a multisensor UAV platform based on multispectral, thermal and RGB high resolution images in precision viticulture","volume":"8","author":"Matese","year":"2018","journal-title":"Agriculture"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0810","doi-asserted-by":"crossref","first-page":"2721","DOI":"10.1038\/s41598-021-81652-3","article-title":"Beyond the traditional NDVI index as a key factor to mainstream the use of UAV in precision viticulture","volume":"11","author":"Matese","year":"2021","journal-title":"Sci. Rep."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0815","doi-asserted-by":"crossref","first-page":"2971","DOI":"10.3390\/rs70302971","article-title":"Intercomparison of UAV, aircraft and satellite remote sensing platforms for precision viticulture","volume":"7","author":"Matese","year":"2015","journal-title":"Remote Sensing"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0820","doi-asserted-by":"crossref","first-page":"2530","DOI":"10.3390\/s20092530","article-title":"UAV and machine learning based refinement of a satellite-driven vegetation index for precision agriculture","volume":"20","author":"Mazzia","year":"2020","journal-title":"Sensors"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b0825","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<433::AID-ASI11>3.0.CO;2-Q","article-title":"Mapping authors in intellectual space: a technical overview","volume":"41","author":"McCain","year":"1990","journal-title":"J. Am. Soc. Info. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0830","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2021.104962","article-title":"Agricultural erosion modelling: evaluating USLE and WEPP field-scale erosion estimates using UAV time-series data","volume":"137","author":"Meinen","year":"2021","journal-title":"Environ. Modell. Software"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0835","doi-asserted-by":"crossref","first-page":"5","DOI":"10.3390\/drones3010005","article-title":"Classification of lowland native grassland communities using hyperspectral Unmanned Aircraft System (UAS) Imagery in the Tasmanian midlands","volume":"3","author":"Melville","year":"2019","journal-title":"Drones"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b0840","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.3390\/rs12091491","article-title":"Applications of UAV thermal imagery in precision agriculture: state of the art and future research outlook","volume":"12","author":"Messina","year":"2020","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0845","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1108\/BPMJ-10-2015-0149","article-title":"A bibliographic study on big data: concepts, trends and challenges","volume":"23","author":"Mishra","year":"2017","journal-title":"Business Process Manag. J."},{"key":"10.1016\/j.compag.2022.107017_b0850","doi-asserted-by":"crossref","DOI":"10.3389\/fpls.2015.00740","article-title":"Crop improvement using life cycle datasets acquired under field conditions","volume":"6","author":"Mochida","year":"2015","journal-title":"Front. Plant Sci."},{"key":"10.1016\/j.compag.2022.107017_b0855","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1016\/j.procs.2018.07.063","article-title":"Review on application of drone systems in precision agriculture","volume":"133","author":"Mogili","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"10.1016\/j.compag.2022.107017_b0860","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.isprsjprs.2016.09.002","article-title":"Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery","volume":"122","author":"Moharana","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b0865","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.compag.2018.12.011","article-title":"IoT and agriculture data analysis for smart farm","volume":"156","author":"Muangprathub","year":"2019","journal-title":"Comput. Electron. Agric."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0870","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1146\/annurev-ento-010715-023834","article-title":"Remote sensing and reflectance profiling in entomology","volume":"61","author":"Nansen","year":"2016","journal-title":"Annu. Rev. Entomol."},{"key":"10.1016\/j.compag.2022.107017_b0875","first-page":"1351","article-title":"Multispectral mapping in agriculture: terrain mosaic using an autonomous quadcopter UAV","volume":"2016","author":"Navia","year":"2016","journal-title":"Int. Conf. Unmanned Aircraft Syst. (ICUAS)"},{"key":"10.1016\/j.compag.2022.107017_b0880","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1007\/978-981-15-0029-9_45","article-title":"The internet of drone things (Iodt): future envision of smart drones","volume":"1045","author":"Nayyar","year":"2020","journal-title":"Adv. Intell. Syst. Comput."},{"issue":"B1","key":"10.1016\/j.compag.2022.107017_b0885","first-page":"1193","article-title":"A light-weight multispectral sensor for micro UAV\u2014opportunities for very high resolution airborne remote sensing","volume":"37","author":"Nebiker","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci"},{"key":"10.1016\/j.compag.2022.107017_b0890","series-title":"2019 7th International Conference on Robot Intelligence Technology and Applications (RiTA)","first-page":"254","article-title":"Emerging UAV applications in agriculture","author":"Negash","year":"2019"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0895","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1002\/smj.659","article-title":"The intellectual structure of the strategic management field: an author co-citation analysis","volume":"29","author":"Nerur","year":"2008","journal-title":"Strateg. Manag. J."},{"issue":"19","key":"10.1016\/j.compag.2022.107017_b0900","doi-asserted-by":"crossref","first-page":"3841","DOI":"10.3390\/rs13193841","article-title":"Automatic identification and monitoring of plant diseases using unmanned aerial vehicles: a review","volume":"13","author":"Neupane","year":"2021","journal-title":"Remote Sensing"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b0905","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12518-013-0120-x","article-title":"UAV for 3D mapping applications: a review","volume":"6","author":"Nex","year":"2014","journal-title":"Appl. Geomatics"},{"issue":"22","key":"10.1016\/j.compag.2022.107017_b0910","doi-asserted-by":"crossref","first-page":"6427","DOI":"10.3390\/s20226427","article-title":"Evapotranspiration estimation with small UAVs in precision agriculture","volume":"20","author":"Niu","year":"2020","journal-title":"Sensors"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0915","first-page":"149","article-title":"Bibliometrics, Citation Analysis and Co-Citation Analysis","volume":"46","author":"Osareh","year":"1996","journal-title":"A Review of Literature I"},{"issue":"8\u201310","key":"10.1016\/j.compag.2022.107017_b0920","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1080\/01431161.2017.1297548","article-title":"UAS, sensors, and data processing in agroforestry: a review towards practical applications","volume":"38","author":"P\u00e1dua","year":"2017","journal-title":"Int. J. Remote Sens."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0925","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/drones4030041","article-title":"A review on drone-based data solutions for cereal crops","volume":"4","author":"Panday","year":"2020","journal-title":"Drones"},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0935","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1002\/aocs.12356","article-title":"Estimating oil and protein content of sesame seeds using image processing and artificial neural network","volume":"97","author":"Parsaeian","year":"2020","journal-title":"J. Am. Oil Chemists\u2019 Soc."},{"issue":"10","key":"10.1016\/j.compag.2022.107017_b0940","doi-asserted-by":"crossref","first-page":"e77151","DOI":"10.1371\/journal.pone.0077151","article-title":"Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) Images","volume":"8","author":"Pe\u00f1a","year":"2013","journal-title":"PLoS ONE"},{"key":"10.1016\/j.compag.2022.107017_b0945","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/j.asoc.2015.08.027","article-title":"A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method","volume":"37","author":"P\u00e9rez-Ortiz","year":"2015","journal-title":"Appl. Soft Comput. J."},{"key":"10.1016\/j.compag.2022.107017_b0950","doi-asserted-by":"crossref","first-page":"105889","DOI":"10.1016\/j.compag.2020.105889","article-title":"Cost-effective IoT devices as trustworthy data sources for a blockchain-based water management system in precision agriculture","volume":"180","author":"Pincheira","year":"2021","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b0955","doi-asserted-by":"crossref","first-page":"817","DOI":"10.3390\/s20030817","article-title":"Advanced UAV\u2013WSN system for intelligent monitoring in precision agriculture","volume":"20","author":"Popescu","year":"2020","journal-title":"Sensors"},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b0960","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.1080\/00207543.2019.1650976","article-title":"Blockchain applications in supply chains, transport and logistics: a systematic review of the literature","volume":"58","author":"Pournader","year":"2020","journal-title":"Int. J. Prod. Res."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0965","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/s11119-012-9257-6","article-title":"A flexible unmanned aerial vehicle for precision agriculture","volume":"13","author":"Primicerio","year":"2012","journal-title":"Precis. Agric."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0970","first-page":"348","article-title":"Statistical bibliography or bibliometrics","volume":"25","author":"Pritchard","year":"1969","journal-title":"J. Document."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0975","first-page":"431","article-title":"The suitability of an unmanned aerial vehicle (UAV) for the evaluation of experimental fields and crops","volume":"99","author":"Pudelko","year":"2012","journal-title":"Agriculture"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0980","first-page":"507","article-title":"Agriculture drones: a modern breakthrough in precision agriculture","volume":"20","author":"Puri","year":"2017","journal-title":"J. Statis. Manag. Syst."},{"key":"10.1016\/j.compag.2022.107017_b0985","doi-asserted-by":"crossref","DOI":"10.1016\/j.comnet.2020.107148","article-title":"A compilation of UAV applications for precision agriculture","volume":"172","author":"Radoglou-Grammatikis","year":"2020","journal-title":"Comput. Netw."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b0990","doi-asserted-by":"crossref","first-page":"383","DOI":"10.59797\/ija.v65i4.2991","article-title":"Application of big data analytics and artificial intelligence in agronomic research","volume":"65","author":"Ramesh","year":"2020","journal-title":"Indian J. Agron."},{"issue":"24","key":"10.1016\/j.compag.2022.107017_b0995","doi-asserted-by":"crossref","first-page":"9070","DOI":"10.1080\/01431161.2019.1569793","article-title":"A bibliometric analysis on the use of unmanned aerial vehicles in agricultural and forestry studies","volume":"40","author":"Raparelli","year":"2019","journal-title":"Int. J. Remote Sens."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1000","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1111\/wre.12026","article-title":"Potential uses of small unmanned aircraft systems (UAS) in weed research","volume":"53","author":"Rasmussen","year":"2013","journal-title":"Weed Res."},{"key":"10.1016\/j.compag.2022.107017_b1005","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.eja.2015.11.026","article-title":"Are vegetation indices derived from consumer-grade cameras mounted on UAVs sufficiently reliable for assessing experimental plots?","volume":"74","author":"Rasmussen","year":"2016","journal-title":"Eur. J. Agron."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1010","doi-asserted-by":"crossref","first-page":"83","DOI":"10.3390\/su14010083","article-title":"Digitalization in food supply chains: a bibliometric review and key-route main path analysis","volume":"14","author":"Rejeb","year":"2022","journal-title":"Sustainability"},{"key":"10.1016\/j.compag.2022.107017_b1015","first-page":"1","article-title":"Drones for supply chain management and logistics: a review and research agenda","author":"Rejeb","year":"2021","journal-title":"Int. J. Logist. Res. Appl."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1020","doi-asserted-by":"crossref","first-page":"72","DOI":"10.3390\/logistics5040072","article-title":"Blockchain technologies in logistics and supply chain management: a bibliometric review","volume":"5","author":"Rejeb","year":"2021","journal-title":"Logistics"},{"key":"10.1016\/j.compag.2022.107017_b1025","doi-asserted-by":"crossref","DOI":"10.1016\/j.iot.2021.100434","article-title":"Humanitarian drones: a review and research agenda","volume":"16","author":"Rejeb","year":"2021","journal-title":"Internet of Things"},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b1030","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1007\/s42488-021-00046-2","article-title":"Blockchain research in healthcare: a bibliometric review and current research trends","volume":"3","author":"Rejeb","year":"2021","journal-title":"J. of Data, Inf. and Manag."},{"key":"10.1016\/j.compag.2022.107017_b1035","doi-asserted-by":"crossref","first-page":"100318","DOI":"10.1016\/j.iot.2020.100318","article-title":"Internet of Things research in supply chain management and logistics: a bibliometric analysis","volume":"12","author":"Rejeb","year":"2020","journal-title":"Internet of Things"},{"key":"10.1016\/j.compag.2022.107017_b1040","article-title":"Global Agriculture Drones Market to Reach US$15.2 Billion by the Year 2027","year":"2021","journal-title":"GlobeNewswire News Room"},{"issue":"10","key":"10.1016\/j.compag.2022.107017_b1045","doi-asserted-by":"crossref","DOI":"10.3390\/s17102173","article-title":"Uncooled thermal camera calibration and optimization of the photogrammetry process for UAV applications in agriculture","volume":"17","author":"Ribeiro-Gomes","year":"2017","journal-title":"Sensors (Switzerland)"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1050","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1108\/IJCHM-03-2014-0146","article-title":"Advances in hospitality research: \u201cFrom Rodney Dangerfield to Aretha Franklin\u201d","volume":"27","author":"Rivera","year":"2015","journal-title":"Int. J. Contempor. Hospital. Manag."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b1055","doi-asserted-by":"crossref","first-page":"3334","DOI":"10.3390\/s150203334","article-title":"Mini-UAV based sensory system for measuring environmental variables in greenhouses","volume":"15","author":"Rold\u00e1n","year":"2015","journal-title":"Sensors"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1060","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.1007\/s11119-021-09786-y","article-title":"Consumer-grade UAV utilized for detecting and analyzing late-season weed spatial distribution patterns in commercial onion fields","volume":"22","author":"Rozenberg","year":"2021","journal-title":"Precis. Agric."},{"key":"10.1016\/j.compag.2022.107017_b1065","article-title":"Unmanned aerial vehicle (UAV) operated spectral camera system for forest and agriculture applications","volume":"8174","author":"Saari","year":"2011","journal-title":"Proceed. SPIE \u2013 Int. Soc. Opt. Eng."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b1070","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1080\/13675567.2020.1782862","article-title":"Analysis of barriers to implement drone logistics","volume":"24","author":"Sah","year":"2021","journal-title":"Int. J. Logist. Res. Appl."},{"key":"10.1016\/j.compag.2022.107017_b1075","doi-asserted-by":"crossref","unstructured":"Saha, A. K., Saha, J., Ray, R., Sircar, S., Dutta, S., Chattopadhyay, S. P., & Saha, H. N., 2018. IOT-based drone for improvement of crop quality in agricultural field. In S. H. N. Chakrabarti S. (Ed.), 2018 IEEE 8th Annual Computing and Communication Workshop and Conference, CCWC 2018 (Vols. 2018-January, pp. 612\u2013615). Institute of Electrical and Electronics Engineers Inc. doi: 10.1109\/CCWC.2018.8301662.","DOI":"10.1109\/CCWC.2018.8301662"},{"key":"10.1016\/j.compag.2022.107017_b1080","first-page":"1","article-title":"LEDCOM: a novel and efficient LED based communication for precision agriculture","volume":"2019","author":"Sai Vineeth","year":"2019","journal-title":"IEEE Conf. Info. Commun. Technol."},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b1085","doi-asserted-by":"crossref","first-page":"11051","DOI":"10.3390\/rs61111051","article-title":"UAV flight experiments applied to the remote sensing of vegetated areas","volume":"6","author":"Salam\u00ed","year":"2014","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b1090","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.eja.2015.07.004","article-title":"Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: a review","volume":"70","author":"Sankaran","year":"2015","journal-title":"Eur. J. Agron."},{"key":"10.1016\/j.compag.2022.107017_b1095","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.agwat.2016.08.026","article-title":"High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard","volume":"183","author":"Santesteban","year":"2017","journal-title":"Agric. Water Manag."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1100","doi-asserted-by":"crossref","first-page":"17","DOI":"10.3163\/1536-5050.98.1.008","article-title":"Beyond citation analysis: A model for assessment of research impact","volume":"98","author":"Sarli","year":"2010","journal-title":"J. Med. Library Assoc. : JMLA"},{"key":"10.1016\/j.compag.2022.107017_b1105","doi-asserted-by":"crossref","first-page":"S123","DOI":"10.1016\/j.rse.2009.03.001","article-title":"Earth system science related imaging spectroscopy\u2014an assessment","volume":"113","author":"Schaepman","year":"2009","journal-title":"Remote Sens. Environ."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b1110","doi-asserted-by":"crossref","DOI":"10.3390\/rs8090706","article-title":"Monitoring agronomic parameters of winter wheat crops with low-cost UAV imagery","volume":"8","author":"Schirrmann","year":"2016","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1115","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1002\/rob.20232","article-title":"Development and application of an autonomous unmanned aerial vehicle for precise aerobiological sampling above agricultural fields","volume":"25","author":"Schmale","year":"2008","journal-title":"J. Field Rob."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b1120","doi-asserted-by":"crossref","first-page":"4103","DOI":"10.1109\/TIM.2019.2947125","article-title":"Enabling precision agriculture through embedded sensing with artificial intelligence","volume":"69","author":"Shadrin","year":"2019","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.compag.2022.107017_b1125","doi-asserted-by":"crossref","first-page":"48572","DOI":"10.1109\/ACCESS.2019.2909530","article-title":"Unmanned Aerial Vehicles (UAVs): a survey on civil applications and key research challenges","volume":"7","author":"Shakhatreh","year":"2019","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1130","doi-asserted-by":"crossref","first-page":"1","DOI":"10.2135\/tppj2018.12.0009","article-title":"Big data driven agriculture: big data analytics in plant breeding, genomics, and the use of remote sensing technologies to advance crop productivity","volume":"2","author":"Shakoor","year":"2019","journal-title":"Plant Phenome J."},{"key":"10.1016\/j.compag.2022.107017_b1135","series-title":"Proceedings - 2019 Amity International Conference on Artificial Intelligence","article-title":"Comparitive Analysis and Implication of UAV and AI in Forensic Investigations","author":"Sharma","year":"2019"},{"key":"10.1016\/j.compag.2022.107017_b1140","first-page":"1","article-title":"The role of artificial intelligence in supply chain management: mapping the territory","author":"Sharma","year":"2022","journal-title":"Int. J. Prod. Res."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b1145","doi-asserted-by":"crossref","first-page":"e0159781","DOI":"10.1371\/journal.pone.0159781","article-title":"Unmanned aerial vehicles for high-throughput phenotyping and agronomic research","volume":"11","author":"Shi","year":"2016","journal-title":"PLoS ONE"},{"issue":"20","key":"10.1016\/j.compag.2022.107017_b1150","doi-asserted-by":"crossref","first-page":"4446","DOI":"10.3390\/s19204446","article-title":"Capturing maize stand heterogeneity across yield-stability zones using Unmanned Aerial Vehicles (UAV)","volume":"19","author":"Shuai","year":"2019","journal-title":"Sensors"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1155","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1002\/asi.4630240406","article-title":"Co-citation in the scientific literature: a new measure of the relationship between two documents","volume":"24","author":"Small","year":"1973","journal-title":"J. Am. Soc. Info. Sci."},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b1160","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1002\/(SICI)1097-4571(1999)50:9<799::AID-ASI9>3.0.CO;2-G","article-title":"Visualizing science by citation mapping","volume":"50","author":"Small","year":"1999","journal-title":"J. Am. Soc. Info. Sci."},{"key":"10.1016\/j.compag.2022.107017_b1165","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106354","article-title":"Cattle counting in the wild with geolocated aerial images in large pasture areas","volume":"189","author":"Soares","year":"2021","journal-title":"Comput. Electron. Agric."},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1170","doi-asserted-by":"crossref","first-page":"58","DOI":"10.3390\/drones4030058","article-title":"An approach for route optimization in applications of precision agriculture using UAVs","volume":"4","author":"Srivastava","year":"2020","journal-title":"Drones"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1175","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1006\/jaer.2000.0577","article-title":"Implementing precision agriculture in the 21st century","volume":"76","author":"Stafford","year":"2000","journal-title":"J. Agric. Eng. Res."},{"key":"10.1016\/j.compag.2022.107017_b1180","series-title":"In 2018 37th Chinese Control Conference (CCC)","article-title":"Wheat drought assessment by remote sensing imagery using unmanned aerial vehicle","author":"Su","year":"2018"},{"key":"10.1016\/j.compag.2022.107017_b1185","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.compag.2018.10.017","article-title":"Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery","volume":"155","author":"Su","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b1190","article-title":"Innovation of agricultural economic management in the process of constructing smart agriculture by big data","volume":"31","author":"Su","year":"2021","journal-title":"Sustainable Comput. Inf. Syst."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b1195","doi-asserted-by":"crossref","first-page":"1955","DOI":"10.13031\/2013.24091","article-title":"Evaluating the sensitivity of an unmanned thermal infrared aerial system to detect water stress in a cotton canopy","volume":"50","author":"Sullivan","year":"2007","journal-title":"Trans. ASABE"},{"key":"10.1016\/j.compag.2022.107017_b1200","article-title":"Integration of RGB-based vegetation index, crop surface model and object-based image analysis approach for sugarcane yield estimation using unmanned aerial vehicle","volume":"180","author":"Sumesh","year":"2021","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b1205","series-title":"2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","first-page":"1","article-title":"A light-weight hyperspectral mapping system for unmanned aerial vehicles\u2014the first results","author":"Suomalainen","year":"2013"},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b1210","doi-asserted-by":"crossref","first-page":"11013","DOI":"10.3390\/rs61111013","article-title":"A lightweight hyperspectral mapping system and photogrammetric processing chain for unmanned aerial vehicles","volume":"6","author":"Suomalainen","year":"2014","journal-title":"Remote Sensing"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1215","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1108\/WJE-09-2020-0459","article-title":"Advance control strategies using image processing, UAV and AI in agriculture: A review","volume":"18","author":"Syeda","year":"2021","journal-title":"World J. Eng."},{"issue":"2\u20133","key":"10.1016\/j.compag.2022.107017_b1220","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1016\/S0306-4573(97)00082-4","article-title":"Information processing using citations to investigate journal influence in accounting","volume":"34","author":"Tahai","year":"1998","journal-title":"Inf. Process. Manage."},{"key":"10.1016\/j.compag.2022.107017_b1225","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105895","article-title":"A survey on the 5G network and its impact on agriculture: challenges and opportunities","volume":"180","author":"Tang","year":"2021","journal-title":"Comput. Electron. Agric."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1230","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1080\/10496505.2019.1638264","article-title":"Data-driven decision making in precision agriculture: the rise of big data in agricultural systems","volume":"20","author":"Tantalaki","year":"2019","journal-title":"J. Agric. Food Info."},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1235","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.3390\/s20041231","article-title":"Estimation of the yield and plant height of winter wheat using UAV-based hyperspectral images","volume":"20","author":"Tao","year":"2020","journal-title":"Sensors"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1240","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1002\/rob.20335","article-title":"Coordinated aerobiological sampling of a plant pathogen in the lower atmosphere using two autonomous unmanned aerial vehicles","volume":"27","author":"Techy","year":"2010","journal-title":"J. Field Rob."},{"key":"10.1016\/j.compag.2022.107017_b1245","doi-asserted-by":"crossref","first-page":"105836","DOI":"10.1016\/j.compag.2020.105836","article-title":"Detection and classification of soybean pests using deep learning with UAV images","volume":"179","author":"Tetila","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b1250","series-title":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","first-page":"401","article-title":"The Use of Uas for Assessing Agricultural Systems in AN Wetland in Tanzania in the\u2014And Wet-Season for Sustainable Agriculture and Providing Ground Truth for Terra-Sar X Data","author":"Thamm","year":"2013"},{"issue":"4","key":"10.1016\/j.compag.2022.107017_b1255","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1177\/0165551507087238","article-title":"Bibliometrics to webometrics","volume":"34","author":"Thelwall","year":"2008","journal-title":"J. Info. Sci."},{"key":"10.1016\/j.compag.2022.107017_b1260","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.compag.2015.03.019","article-title":"An automatic object-based method for optimal thresholding in UAV images: application for vegetation detection in herbaceous crops","volume":"114","author":"Torres-S\u00e1nchez","year":"2015","journal-title":"Comput. Electron. Agric."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b1265","doi-asserted-by":"crossref","first-page":"e0130479","DOI":"10.1371\/journal.pone.0130479","article-title":"High-throughput 3-D monitoring of agricultural-tree plantations with Unmanned Aerial Vehicle (UAV) technology","volume":"10","author":"Torres-S\u00e1nchez","year":"2015","journal-title":"PLoS ONE"},{"key":"10.1016\/j.compag.2022.107017_b1270","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.compag.2014.02.009","article-title":"Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV","volume":"103","author":"Torres-S\u00e1nchez","year":"2014","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.compag.2022.107017_b1275","article-title":"A review on UAV-based applications for precision agriculture","volume":"10","author":"Tsouros","year":"2019","journal-title":"Information (Switzerland)"},{"key":"10.1016\/j.compag.2022.107017_b1280","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.isprsjprs.2019.12.006","article-title":"Optimising drone flight planning for measuring horticultural tree crop structure","volume":"160","author":"Tu","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b1285","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.biosystemseng.2017.09.007","article-title":"Internet of Things in agriculture, recent advances and future challenges","volume":"164","author":"Tzounis","year":"2017","journal-title":"Biosyst. Eng."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1290","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/s11192-015-1654-y","article-title":"Scientometric mapping of computer science research in Mexico","volume":"105","author":"Uddin","year":"2015","journal-title":"Scientometrics"},{"key":"10.1016\/j.compag.2022.107017_b1295","unstructured":"UN., 2019. World population prospects 2019. https:\/\/population.un.org\/wpp\/ (Accessed on 15\/04\/2022)."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b1300","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1109\/JSTARS.2013.2250921","article-title":"Characterization of rice paddies by a UAV-mounted miniature hyperspectral sensor system","volume":"6","author":"Uto","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b1305","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/bs.agron.2020.03.001","article-title":"Drones in agriculture","volume":"162","author":"van der Merwe","year":"2020","journal-title":"Adv. Agron."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1310","doi-asserted-by":"crossref","first-page":"217","DOI":"10.3390\/en15010217","article-title":"Unmanned Aerial Vehicles (UAV) in precision agriculture: applications and challenges","volume":"15","author":"Velusamy","year":"2022","journal-title":"Energies"},{"issue":"9","key":"10.1016\/j.compag.2022.107017_b1315","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.3390\/rs10091331","article-title":"Mapping and classification of ecologically sensitive marine habitats using Unmanned Aerial Vehicle (UAV) imagery and Object-Based Image Analysis (OBIA)","volume":"10","author":"Ventura","year":"2018","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b1320","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1016\/j.rse.2014.06.006","article-title":"Green area index from an unmanned aerial system over wheat and rapeseed crops","volume":"152","author":"Verger","year":"2014","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1325","doi-asserted-by":"crossref","first-page":"163","DOI":"10.5194\/bg-12-163-2015","article-title":"Deploying four optical UAV-based sensors over grassland: challenges and limitations","volume":"12","author":"Von Bueren","year":"2015","journal-title":"Biogeosciences"},{"key":"10.1016\/j.compag.2022.107017_b1330","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/j.adhoc.2018.07.017","article-title":"Internet of underground things in precision agriculture: architecture and technology aspects","volume":"81","author":"Vuran","year":"2018","journal-title":"Ad Hoc Netw."},{"key":"10.1016\/j.compag.2022.107017_b1335","first-page":"1","article-title":"Responsible artificial intelligence as a secret ingredient for digital health: bibliometric analysis, insights, and research directions","author":"Wamba","year":"2021","journal-title":"Info. Syst. Front."},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b1340","doi-asserted-by":"crossref","DOI":"10.3390\/rs11070809","article-title":"Bibliometric analysis of remote sensing research trend in crop growth monitoring: A case study in China","volume":"11","author":"Wang","year":"2019","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1345","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1002\/asi.4630320302","article-title":"Author cocitation: A literature measure of intellectual structure","volume":"32","author":"White","year":"1981","journal-title":"J. Am. Soc. Info. Sci."},{"issue":"2","key":"10.1016\/j.compag.2022.107017_b1350","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.biosystemseng.2010.11.010","article-title":"Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV)","volume":"108","author":"Xiang","year":"2011","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2022.107017_b1355","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2020.105731","article-title":"A review on plant high-throughput phenotyping traits using UAV-based sensors","volume":"178","author":"Xie","year":"2020","journal-title":"Comput. Electron. Agric."},{"issue":"12","key":"10.1016\/j.compag.2022.107017_b1360","doi-asserted-by":"crossref","DOI":"10.3390\/rs11121443","article-title":"Unmanned aerial vehicle for remote sensing applications\u2014a review","volume":"11","author":"Yao","year":"2019","journal-title":"Remote Sensing"},{"issue":"3","key":"10.1016\/j.compag.2022.107017_b1365","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3390\/drones5030065","article-title":"Moving people tracking and false track removing with infrared thermal imaging by a multirotor","volume":"5","author":"Yeom","year":"2021","journal-title":"Drones"},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b1370","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.3390\/rs10071138","article-title":"A comparison of crop parameters estimation using images from UAV-mounted snapshot hyperspectral sensor and high-definition digital camera","volume":"10","author":"Yue","year":"2018","journal-title":"Remote Sensing"},{"issue":"7","key":"10.1016\/j.compag.2022.107017_b1375","doi-asserted-by":"crossref","DOI":"10.3390\/rs9070708","article-title":"Estimation of winter wheat above-ground biomass using unmanned aerial vehicle-based snapshot hyperspectral sensor and crop height improved models","volume":"9","author":"Yue","year":"2017","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b1380","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.biocon.2015.03.031","article-title":"Using lightweight unmanned aerial vehicles to monitor tropical forest recovery","volume":"186","author":"Zahawi","year":"2015","journal-title":"Biol. Conserv."},{"key":"10.1016\/j.compag.2022.107017_b1385","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.biosystemseng.2018.10.014","article-title":"Smart farming IoT platform based on edge and cloud computing","volume":"177","author":"Zamora-Izquierdo","year":"2019","journal-title":"Biosyst. Eng."},{"key":"10.1016\/j.compag.2022.107017_b1390","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.eja.2014.01.004","article-title":"Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods","volume":"55","author":"Zarco-Tejada","year":"2014","journal-title":"Eur. J. Agron."},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b1395","doi-asserted-by":"crossref","first-page":"1450","DOI":"10.3390\/s20051450","article-title":"Image-based phenotyping of flowering intensity in cool-season crops","volume":"20","author":"Zhang","year":"2020","journal-title":"Sensors"},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b1400","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s11119-012-9274-5","article-title":"The application of small unmanned aerial systems for precision agriculture: a review","volume":"13","author":"Zhang","year":"2012","journal-title":"Precis. Agric."},{"issue":"6","key":"10.1016\/j.compag.2022.107017_b1405","doi-asserted-by":"crossref","first-page":"605","DOI":"10.3390\/rs11060605","article-title":"Mapping maize water stress based on UAV multispectral remote sensing","volume":"11","author":"Zhang","year":"2019","journal-title":"Remote Sensing"},{"issue":"13","key":"10.1016\/j.compag.2022.107017_b1410","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.3390\/rs11131554","article-title":"A deep learning-based approach for automated yellow rust disease detection from high-resolution hyperspectral UAV images","volume":"11","author":"Zhang","year":"2019","journal-title":"Remote Sensing"},{"key":"10.1016\/j.compag.2022.107017_b1415","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106717","article-title":"Detection and discrimination of disease and insect stress of tea plants using hyperspectral imaging combined with wavelet analysis","volume":"193","author":"Zhao","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"10.1016\/j.compag.2022.107017_b1420","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3225843","article-title":"Entropy guided adversarial domain adaptation for aerial image semantic segmentation","volume":"60","author":"Zheng","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.compag.2022.107017_b1425","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.fcr.2016.08.027","article-title":"Detection of rice phenology through time series analysis of ground-based spectral index data","volume":"198","author":"Zheng","year":"2016","journal-title":"Field Crops Res."},{"issue":"05","key":"10.1016\/j.compag.2022.107017_b1430","doi-asserted-by":"crossref","first-page":"184","DOI":"10.3991\/ijoe.v14i05.8653","article-title":"Design of a precision agriculture leakage seeding system based on wireless sensors","volume":"14","author":"Zheng","year":"2018","journal-title":"Int. J. Online Eng."},{"issue":"5","key":"10.1016\/j.compag.2022.107017_b1435","doi-asserted-by":"crossref","first-page":"146","DOI":"10.3390\/agriculture10050146","article-title":"Analysis of plant height changes of lodged maize using UAV-LiDAR data","volume":"10","author":"Zhou","year":"2020","journal-title":"Agriculture"},{"issue":"1","key":"10.1016\/j.compag.2022.107017_b1440","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s13007-021-00747-0","article-title":"Maize-IAS: A maize image analysis software using deep learning for high-throughput plant phenotyping","volume":"17","author":"Zhou","year":"2021","journal-title":"Plant Methods"},{"key":"10.1016\/j.compag.2022.107017_b1445","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.isprsjprs.2017.05.003","article-title":"Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery","volume":"130","author":"Zhou","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"issue":"05","key":"10.1016\/j.compag.2022.107017_b1450","doi-asserted-by":"crossref","first-page":"43","DOI":"10.3991\/ijoe.v12i05.5735","article-title":"Simulation of the core technology of a greenhouse-monitoring system based on a wireless sensor network","volume":"12","author":"Zhou","year":"2016","journal-title":"Int. J. Online Eng."},{"key":"10.1016\/j.compag.2022.107017_b1455","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2021.106019","article-title":"Assessment for crop water stress with infrared thermal imagery in precision agriculture: a review and future prospects for deep learning applications","volume":"182","author":"Zhou","year":"2021","journal-title":"Comput. Electron. Agric."}],"container-title":["Computers and Electronics in Agriculture"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169922003349?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0168169922003349?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T13:38:23Z","timestamp":1759153103000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0168169922003349"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":290,"alternative-id":["S0168169922003349"],"URL":"https:\/\/doi.org\/10.1016\/j.compag.2022.107017","relation":{},"ISSN":["0168-1699"],"issn-type":[{"value":"0168-1699","type":"print"}],"subject":[],"published":{"date-parts":[[2022,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Drones in agriculture: A review and bibliometric analysis","name":"articletitle","label":"Article Title"},{"value":"Computers and Electronics in Agriculture","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compag.2022.107017","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"107017"}}