{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:22:59Z","timestamp":1769520179032,"version":"3.49.0"},"reference-count":71,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T00:00:00Z","timestamp":1668902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Funds by FCT","award":["COA\/CAC\/0030\/2019"],"award-info":[{"award-number":["COA\/CAC\/0030\/2019"]}]},{"name":"National Funds by FCT","award":["UIDB\/04033\/2020"],"award-info":[{"award-number":["UIDB\/04033\/2020"]}]},{"name":"National Funds by FCT","award":["LA\/P\/0126\/2020"],"award-info":[{"award-number":["LA\/P\/0126\/2020"]}]},{"name":"National Funds by FCT","award":["CEECIND\/00447\/2017"],"award-info":[{"award-number":["CEECIND\/00447\/2017"]}]},{"name":"National Funds by FCT","award":["2022.02317.CEECIND"],"award-info":[{"award-number":["2022.02317.CEECIND"]}]},{"name":"FCT","award":["COA\/CAC\/0030\/2019"],"award-info":[{"award-number":["COA\/CAC\/0030\/2019"]}]},{"name":"FCT","award":["UIDB\/04033\/2020"],"award-info":[{"award-number":["UIDB\/04033\/2020"]}]},{"name":"FCT","award":["LA\/P\/0126\/2020"],"award-info":[{"award-number":["LA\/P\/0126\/2020"]}]},{"name":"FCT","award":["CEECIND\/00447\/2017"],"award-info":[{"award-number":["CEECIND\/00447\/2017"]}]},{"name":"FCT","award":["2022.02317.CEECIND"],"award-info":[{"award-number":["2022.02317.CEECIND"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Drones"],"abstract":"<jats:p>The increasing use of geospatial information from satellites and unmanned aerial vehicles (UAVs) has been contributing to significant growth in the availability of instruments and methodologies for data acquisition and analysis. For better management of vineyards (and most crops), it is crucial to access the spatial-temporal variability. This knowledge throughout the vegetative cycle of any crop is crucial for more efficient management, but in the specific case of viticulture, this knowledge is even more relevant. Some research studies have been carried out in recent years, exploiting the advantage of satellite and UAV data, used individually or in combination, for crop management purposes. However, only a few studies explore the multi-temporal use of these two types of data, isolated or synergistically. This research aims to clearly identify the most suitable data and strategies to be adopted in specific stages of the vineyard phenological cycle. Sentinel-2 data from two vineyard plots, located in the Douro Demarcated Region (Portugal), are compared with UAV multispectral data under three distinct conditions: considering the whole vineyard plot; considering only the grapevine canopy; and considering inter-row areas (excluding all grapevine vegetation). The results show that data from both platforms are able to describe the vineyards\u2019 variability throughout the vegetative growth but at different levels of detail. Sentinel-2 data can be used to map vineyard soil variability, whilst the higher spatial resolution of UAV-based data allows diverse types of applications. In conclusion, it should be noted that, depending on the intended use, each type of data, individually, is capable of providing important information for vineyard management.<\/jats:p>","DOI":"10.3390\/drones6110366","type":"journal-article","created":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T03:11:21Z","timestamp":1669000281000},"page":"366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Synergistic Use of Sentinel-2 and UAV Multispectral Data to Improve and Optimize Viticulture Management"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4119-2654","authenticated-orcid":false,"given":"Oiliam","family":"Stolarski","sequence":"first","affiliation":[{"name":"Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Tr\u00e1s-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7946-8786","authenticated-orcid":false,"given":"H\u00e9lder","family":"Fraga","sequence":"additional","affiliation":[{"name":"Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Tr\u00e1s-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal"},{"name":"Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, University of Tr\u00e1s-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4533-930X","authenticated-orcid":false,"given":"Joaquim J.","family":"Sousa","sequence":"additional","affiliation":[{"name":"Engineering Department, School of Science and Technology, University of Tr\u00e1s-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"Centre for Robotics in Industry and Intelligent Systems (CRIIS), Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7570-9773","authenticated-orcid":false,"given":"Lu\u00eds","family":"P\u00e1dua","sequence":"additional","affiliation":[{"name":"Centre for the Research and Technology of Agro-Environmental and Biological Sciences (CITAB), University of Tr\u00e1s-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal"},{"name":"Institute for Innovation, Capacity Building and Sustainability of Agri-Food Production, University of Tr\u00e1s-os-Montes e Alto Douro, 5001-801 Vila Real, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,20]]},"reference":[{"key":"ref_1","unstructured":"Khosla, R. (2010, January 1\u20136). Precision Agriculture: Challenges and Opportunities in a Flat World. Proceedings of the 2010 19th World Congress of Soil Science, Soil Solutions for a Changing World, Brisbane, Australia."},{"key":"ref_2","unstructured":"Pierce, F.J., Robert, P.C., and Mangold, G. (December, January 30). Site Specific Management: The Pros, the Cons, and the Realities. Proceedings of the Integrated Crop Management Conference, Ames, IA, USA."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.foodchem.2018.11.140","article-title":"Precision Viticulture and Advanced Analytics. A Short Review","volume":"279","author":"Santesteban","year":"2019","journal-title":"Food Chem."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Matese, A., and Di Gennaro, S.F. (2015). Technology in Precision Viticulture: A State of the Art Review. Int. J. Wine Res., 69.","DOI":"10.2147\/IJWR.S69405"},{"key":"ref_5","unstructured":"Wright, J.D. (2015). Geographic Information Systems and Remote Sensing. International Encyclopedia of the Social & Behavioral Sciences, Elsevier. [2nd ed.]."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/B978-0-12-386473-4.00005-1","article-title":"Proximal Soil Sensing: An Effective Approach for Soil Measurements in Space and Time","volume":"113","author":"Adamchuk","year":"2011","journal-title":"Adv. Agron."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"111679","DOI":"10.1016\/j.rse.2020.111679","article-title":"A Smart Multiple Spatial and Temporal Resolution System to Support Precision Agriculture from Satellite Images: Proof of Concept on Aglianico Vineyard","volume":"240","author":"Brook","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1111\/j.1755-0238.2002.tb00209.x","article-title":"Optical Remote Sensing Applications in Viticulture\u2014A Review","volume":"8","author":"Hall","year":"2002","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Gatti, M., Dosso, P., Maurino, M., Merli, M.C., Bernizzoni, F., Jos\u00e9 Pirez, F., Plat\u00e8, B., Bertuzzi, G.C., and Poni, S. (2016). MECS-VINE\u00ae: A New Proximal Sensor for Segmented Mapping of Vigor and Yield Parameters on Vineyard Rows. Sensors, 16.","DOI":"10.3390\/s16122009"},{"key":"ref_10","unstructured":"Green, E.P., and Edwards, A.J. (2000). Coastal Management Sourcebooks, Unesco Pub."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"100019","DOI":"10.1016\/j.srs.2021.100019","article-title":"UAV & Satellite Synergies for Optical Remote Sensing Applications: A Literature Review","volume":"3","author":"Corpetti","year":"2021","journal-title":"Sci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.biosystemseng.2012.08.009","article-title":"Twenty Five Years of Remote Sensing in Precision Agriculture: Key Advances and Remaining Knowledge Gaps|Elsevier Enhanced Reader","volume":"114","author":"Mulla","year":"2013","journal-title":"Biosyst. Eng."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sishodia, R.P., Ray, R.L., and Singh, S.K. (2020). Applications of Remote Sensing in Precision Agriculture: A Review. Remote Sens., 12.","DOI":"10.3390\/rs12193136"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.3389\/fpls.2017.01111","article-title":"Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives","volume":"8","author":"Yang","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_15","unstructured":"Themistocleous, K., Hadjimitsis, D.G., Michaelides, S., and Papadavid, G. (2016;, January 12). Fusion of Spatio-Temporal UAV and Proximal Sensing Data for an Agricultural Decision Support System. Proceedings of the Fourth International Conference on Remote Sensing and Geoinformation of the Environment, Paphos, Cyprus."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Gasmi, A., Masse, A., Ducrot, D., and Zouari, H. (2017). T\u00e9l\u00e9d\u00e9tection et photogramm\u00e9trie pour l\u2019\u00e9tude de la dynamique de l\u2019occupation du sol dans le bassin versant de l\u2019oued Chiba (Cap-Bon, Tunisie). Rev. Fr. Photogramm\u00e9trie T\u00e9l\u00e9d\u00e9tection, 43\u201351.","DOI":"10.52638\/rfpt.2017.344"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.compag.2018.02.013","article-title":"Vineyard Water Status Estimation Using Multispectral Imagery from an UAV Platform and Machine Learning Algorithms for Irrigation Scheduling Management","volume":"147","author":"Romero","year":"2018","journal-title":"Comput. Electron. Agric."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Hatfield, J.L., Prueger, J.H., Sauer, T.J., Dold, C., O\u2019Brien, P., and Wacha, K. (2019). Applications of Vegetative Indices from Remote Sensing to Agriculture: Past and Future. Inventions, 4.","DOI":"10.3390\/inventions4040071"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Giovos, R., Tassopoulos, D., Kalivas, D., Lougkos, N., and Priovolou, A. (2021). Remote Sensing Vegetation Indices in Viticulture: A Critical Review. Agriculture, 11.","DOI":"10.3390\/agriculture11050457"},{"key":"ref_20","first-page":"309","article-title":"Monitoring Vegetation Systems In The Great Plains With ERTS","volume":"351","author":"Rouse","year":"1974","journal-title":"NASA Spec. Publ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e1353691","DOI":"10.1155\/2017\/1353691","article-title":"Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications","volume":"2017","author":"Xue","year":"2017","journal-title":"J. Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1338","DOI":"10.2136\/sssaj2012.0376","article-title":"Improving Wine Quality through Harvest Zoning and Combined Use of Remote and Soil Proximal Sensing","volume":"77","author":"Priori","year":"2013","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Campos, J., Garc\u00eda-Ru\u00edz, F., and Gil, E. (2021). Assessment of Vineyard Canopy Characteristics from Vigour Maps Obtained Using UAV and Satellite Imagery. Sensors, 21.","DOI":"10.3390\/s21072363"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1007\/s11119-019-09663-9","article-title":"Mapping Vineyard Vigor Using Airborne Remote Sensing: Relations with Yield, Berry Composition and Sanitary Status under Humid Climate Conditions","volume":"21","author":"Ferrer","year":"2020","journal-title":"Precis. Agric."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cogato, A., Meggio, F., Collins, C., and Marinello, F. (2020). Medium-Resolution Multispectral Data from Sentinel-2 to Assess the Damage and the Recovery Time of Late Frost on Vineyards. Remote Sens., 12.","DOI":"10.3390\/rs12111896"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Cogato, A., Pagay, V., Marinello, F., Meggio, F., Grace, P., and De Antoni Migliorati, M. (2019). Assessing the Feasibility of Using Sentinel-2 Imagery to Quantify the Impact of Heatwaves on Irrigated Vineyards. Remote Sens., 11.","DOI":"10.3390\/rs11232869"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Comparetti, A., and Marques da Silva, J.R. (2022). Use of Sentinel-2 Satellite for Spatially Variable Rate Fertiliser Management in a Sicilian Vineyard. Sustainability, 14.","DOI":"10.3390\/su14031688"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Esteves, C., Fangueiro, D., Braga, R.P., Martins, M., Botelho, M., and Ribeiro, H. (2022). Assessing the Contribution of ECa and NDVI in the Delineation of Management Zones in a Vineyard. Agronomy, 12.","DOI":"10.3390\/agronomy12061331"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bollas, N., Kokinou, E., and Polychronos, V. (2021). Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece. Drones, 5.","DOI":"10.3390\/drones5020035"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Devaux, N., Crestey, T., Leroux, C., and Tisseyre, B. (2019). Potential of Sentinel-2 Satellite Images to Monitor Vine Fields Grown at a Territorial Scale. OENO One, 53.","DOI":"10.20870\/oeno-one.2019.53.1.2293"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Khaliq, A., Comba, L., Biglia, A., Ricauda Aimonino, D., Chiaberge, M., and Gay, P. (2019). Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment. Remote Sens., 11.","DOI":"10.3390\/rs11040436"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1353","DOI":"10.1007\/s11119-021-09788-w","article-title":"Estimation of Soil Classes and Their Relationship to Grapevine Vigor in a Bordeaux Vineyard: Advancing the Practical Joint Use of Electromagnetic Induction (EMI) and NDVI Datasets for Precision Viticulture","volume":"22","author":"Hubbard","year":"2021","journal-title":"Precis. Agric."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Di Gennaro, S.F., Dainelli, R., Palliotti, A., Toscano, P., and Matese, A. (2019). Sentinel-2 Validation for Spatial Variability Assessment in Overhead Trellis System Viticulture Versus UAV and Agronomic Data. Remote Sens., 11.","DOI":"10.3390\/rs11212573"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"887","DOI":"10.3389\/fpls.2017.00887","article-title":"Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring","volume":"8","year":"2017","journal-title":"Front. Plant Sci."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Messina, G., Pe\u00f1a, J.M., Vizzari, M., and Modica, G. (2020). A Comparison of UAV and Satellites Multispectral Imagery in Monitoring Onion Crop. An Application in the \u2018Cipolla Rossa Di Tropea\u2019 (Italy). Remote Sens., 12.","DOI":"10.3390\/rs12203424"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1007\/s12524-020-01251-z","article-title":"Calibration of Satellite Imagery with Multispectral UAV Imagery","volume":"49","author":"Jain","year":"2021","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_37","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 Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1111\/j.1755-0238.1995.tb00085.x","article-title":"Growth Stages of the Grapevine: Phenological Growth Stages of the Grapevine (Vitis Vinifera L. Ssp. Vinifera)\u2014Codes and Descriptions According to the Extended BBCH Scale","volume":"1","author":"Lorenz","year":"1995","journal-title":"Aust. J. Grape Wine Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s Optical High-Resolution Mission for GMES Operational Services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Main-Knorn, M., Pflug, B., Louis, J., Debaecker, V., M\u00fcller-Wilm, U., and Gascon, F. (2017, January 11\u201314). Sen2Cor for Sentinel-2. Proceedings of the Image and Signal Processing for Remote Sensing XXIII, Warsaw, Poland.","DOI":"10.1117\/12.2278218"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S0168-1923(97)00027-0","article-title":"Growing Degree-Days: One Equation, Two Interpretations","volume":"87","author":"McMaster","year":"1997","journal-title":"Agric. For. Meteorol."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Winkler, A.J. (1974). General Viticulture, University of California Press.","DOI":"10.1525\/9780520353183"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"493","DOI":"10.3733\/hilg.v15n06p493","article-title":"Composition and Quality of Musts and Wines of California Grapes","volume":"15","author":"Amerine","year":"1944","journal-title":"Hilgardia"},{"key":"ref_44","unstructured":"Meier, U. (2018). Growth Stages of Mono- and Dicotyledonous Plants: BBCH Monograph, Open Agrar Repositorium."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.scienta.2019.02.025","article-title":"Modeling Phenology of Four Grapevine Cultivars (Vitis vinifera L.) in Mediterranean Climate Conditions","volume":"250","year":"2019","journal-title":"Sci. Hortic."},{"key":"ref_46","first-page":"61","article-title":"Exig\u00eancias T\u00e9rmicas, Dura\u00e7\u00e3o e Precocidade de Estados Fenol\u00f3gicos de Castas Da Colec\u00e7\u00e3o Ampelogr\u00e1fica Nacional","volume":"23","author":"Lopes","year":"2007","journal-title":"Ci\u00eanc. E T\u00e9c. Vitivin\u00edcola"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1186\/s13007-020-00632-2","article-title":"Evaluation of Novel Precision Viticulture Tool for Canopy Biomass Estimation and Missing Plant Detection Based on 2.5D and 3D Approaches Using RGB Images Acquired by UAV Platform","volume":"16","author":"Matese","year":"2020","journal-title":"Plant Methods"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Duarte, L., Teodoro, A.C., Sousa, J.J., and P\u00e1dua, L. (2021). QVigourMap: A GIS Open Source Application for the Creation of Canopy Vigour Maps. Agronomy, 11.","DOI":"10.3390\/agronomy11050952"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"99","DOI":"10.2307\/3001913","article-title":"Comparing Individual Means in the Analysis of Variance","volume":"5","author":"Tukey","year":"1949","journal-title":"Biometrics"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.rse.2003.11.006","article-title":"Land Surface Phenology, Climatic Variation, and Institutional Change: Analyzing Agricultural Land Cover Change in Kazakhstan","volume":"89","author":"Henebry","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Borgogno-Mondino, E., de Palma, L., and Novello, V. (2020). Investigating Sentinel 2 Multispectral Imagery Efficiency in Describing Spectral Response of Vineyards Covered with Plastic Sheets. Agronomy, 10.","DOI":"10.3390\/agronomy10121909"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.agee.2018.11.002","article-title":"Disentangling the Carbon Budget of a Vineyard: The Role of Soil Management","volume":"272","author":"Tezza","year":"2019","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_53","unstructured":"Magalh\u00e3es, N. (2015). Tratado De Viticultura: A Videira, A Vinha E O \u201cTerroir\u201d, Esfera Po\u00e9tica. [2nd ed.]."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Puig-Sirera, \u00c0., Antichi, D., Warren Raffa, D., and Rallo, G. (2021). Application of Remote Sensing Techniques to Discriminate the Effect of Different Soil Management Treatments over Rainfed Vineyards in Chianti Terroir. Remote Sens., 13.","DOI":"10.3390\/rs13040716"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"919","DOI":"10.20870\/oeno-one.2020.54.4.4028","article-title":"Comparison between Satellite and Ground Data with UAV-Based Information to Analyse Vineyard Spatio-Temporal Variability: This Article Is Published in Cooperation with the XIIIth International Terroir Congress 17\u201318 November 2020, Adelaide, Australia. Guest Editors: Cassandra Collins and Roberta De Bei","volume":"54","author":"Pastonchi","year":"2020","journal-title":"OENO One"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"P\u00e1dua, L., Marques, P., Hru\u0161ka, J., Ad\u00e3o, T., Peres, E., Morais, R., and Sousa, J.J. (2018). Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery. Remote Sens., 10.","DOI":"10.3390\/rs10121907"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"P\u00e1dua, L., Marques, P., Ad\u00e3o, T., Guimar\u00e3es, N., Sousa, A., Peres, E., and Sousa, J.J. (2019). Vineyard Variability Analysis through UAV-Based Vigour Maps to Assess Climate Change Impacts. Agronomy, 9.","DOI":"10.3390\/agronomy9100581"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"14458","DOI":"10.3390\/rs71114458","article-title":"Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard","volume":"7","author":"Diago","year":"2015","journal-title":"Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"P\u00e1dua, L., Ad\u00e3o, T., Sousa, A., Peres, E., and Sousa, J.J. (2020). Individual Grapevine Analysis in a Multi-Temporal Context Using UAV-Based Multi-Sensor Imagery. Remote Sens., 12.","DOI":"10.3390\/rs12010139"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1111\/j.1365-2621.1970.tb12358.x","article-title":"Free Amino Acids and Other Nitrogenous Fractions in Wine Grapes","volume":"35","author":"Kliewer","year":"1970","journal-title":"J. Food Sci."},{"key":"ref_61","unstructured":"Van Leeuwen, C., Garnier, C., Agut, C., Baculat, B., Barbeau, G., Besnard, E., Bois, B., Boursiquot, J.-M., Chuine, I., and Dessup, T. (2008). Heat Requirements for Grapevine Varieties Is Essential Information to Adapt Plant Material in a Changing Climate, Food and Agriculture Organization."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez-Guisuraga, J.M., Sanz-Ablanedo, E., Su\u00e1rez-Seoane, S., and Calvo, L. (2018). Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges. Sensors, 18.","DOI":"10.3390\/s18020586"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"P\u00e1dua, L., Guimar\u00e3es, N., Ad\u00e3o, T., Sousa, A., Peres, E., and Sousa, J.J. (2020). Effectiveness of Sentinel-2 in Multi-Temporal Post-Fire Monitoring When Compared with UAV Imagery. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9040225"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"106905","DOI":"10.1016\/j.compag.2022.106905","article-title":"Vineyard Classification Using OBIA on UAV-Based RGB and Multispectral Data: A Case Study in Different Wine Regions","volume":"196","author":"Matese","year":"2022","journal-title":"Comput. Electron. Agric."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"de Castro, A.I., Pe\u00f1a, J.M., Torres-S\u00e1nchez, J., Jim\u00e9nez-Brenes, F.M., Valencia-Gredilla, F., Recasens, J., and L\u00f3pez-Granados, F. (2020). Mapping Cynodon Dactylon Infesting Cover Crops with an Automatic Decision Tree-OBIA Procedure and UAV Imagery for Precision Viticulture. Remote Sens., 12.","DOI":"10.3390\/rs12010056"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Jurado, J.M., P\u00e1dua, L., Feito, F.R., and Sousa, J.J. (2020). Automatic Grapevine Trunk Detection on UAV-Based Point Cloud. Remote Sens., 12.","DOI":"10.3390\/rs12183043"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"de Castro, A.I., Jim\u00e9nez-Brenes, F.M., Torres-S\u00e1nchez, J., Pe\u00f1a, J.M., Borra-Serrano, I., and L\u00f3pez-Granados, F. (2018). 3-D Characterization of Vineyards Using a Novel UAV Imagery-Based OBIA Procedure for Precision Viticulture Applications. Remote Sens., 10.","DOI":"10.3390\/rs10040584"},{"key":"ref_68","first-page":"262","article-title":"Unmanned Aerial Vehicle (UAV)-Based Remote Sensing to Monitor Grapevine Leaf Stripe Disease within a Vineyard Affected by Esca Complex","volume":"55","author":"Gennaro","year":"2016","journal-title":"Phytopathol. Mediterr."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Albetis, J., Jacquin, A., Goulard, M., Poilv\u00e9, H., Rousseau, J., Clenet, H., Dedieu, G., and Duthoit, S. (2019). On the Potentiality of UAV Multispectral Imagery to Detect Flavescence Dor\u00e9e and Grapevine Trunk Diseases. Remote Sens., 11.","DOI":"10.3390\/rs11010023"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1139\/juvs-2016-0024","article-title":"Monitoring Vineyards with UAV and Multi-Sensors for the Assessment of Water Stress and Grape Maturity","volume":"5","author":"Soubry","year":"2017","journal-title":"J. Unmanned Veh. Syst."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"P\u00e1dua, L., Bernardo, S., Dinis, L.-T., Correia, C., Moutinho-Pereira, J., and Sousa, J.J. (2022). The Efficiency of Foliar Kaolin Spray Assessed through UAV-Based Thermal Infrared Imagery. Remote Sens., 14.","DOI":"10.3390\/rs14164019"}],"container-title":["Drones"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-446X\/6\/11\/366\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:22:21Z","timestamp":1760145741000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-446X\/6\/11\/366"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,20]]},"references-count":71,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["drones6110366"],"URL":"https:\/\/doi.org\/10.3390\/drones6110366","relation":{},"ISSN":["2504-446X"],"issn-type":[{"value":"2504-446X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,20]]}}}