{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T15:10:55Z","timestamp":1786029055342,"version":"3.56.0"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T00:00:00Z","timestamp":1708387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recent GIS technologies are shaping the direction of Precision Agriculture and Viticulture. Sentinel-2 satellites and UAVs are key resources for multi-spectral analyses of vegetation. Despite being extensively adopted in numerous applications and scenarios, the pros and cons of both platforms are still debated. Researchers have currently investigated different aspects of these sources, mainly comparing different vegetation indexes and exploring potential relationships with agronomic variables. However, due to the costs and limitations of such an approach, a standardized methodology for agronomic purposes is still missing. This study aims to fill such a methodology gap by overcoming the potential flaws or shortages of previous works. To achieve this, an image acquisition campaign covering 6 months and over 17 hectares was carried out, followed by an NDVI comparison between Sentinel-2 and UAV to eventually explore relationships with agronomic variables. Comparative analyses were performed by using both classical (Ordinary Least Squares regression and Pearson Correlation) and spatial (Moran\u2019s Index) statistical approaches: here, 90% of cases show r and MI scores above 0.6 for plain images, with these scores expectedly lowering to 72% and 52% when considering segmented images. Moreover, NDVI thematic maps were classified into clusters and validated by the Chi-squared test. Finally, the relationship and distribution of agronomic variables within NDVI and clustered maps were consistently validated through the ANOVA test. The proposed open-source pipeline allows to strengthen existing UAV and satellite applications in Precision Agriculture by integrating more agronomic variables.<\/jats:p>","DOI":"10.3390\/rs16050735","type":"journal-article","created":{"date-parts":[[2024,2,20]],"date-time":"2024-02-20T07:50:26Z","timestamp":1708415426000},"page":"735","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["From Space to Field: Combining Satellite, UAV and Agronomic Data in an Open-Source Methodology for the Validation of NDVI Maps in Precision Viticulture"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6283-3225","authenticated-orcid":false,"given":"David","family":"Govi","sequence":"first","affiliation":[{"name":"Polaris Engineering Spa, Via Turati 29, 20121 Milano, Italy"},{"name":"Advanced Master GIScience and UAS, Department of Civil, Environmental and Architectural Engineering (ICEA), University of Padova, 35100 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1546-644X","authenticated-orcid":false,"given":"Salvatore Eugenio","family":"Pappalardo","sequence":"additional","affiliation":[{"name":"Laboratory GIScience and Drones for Good, Department of Civil, Environmental and Architectural Engineering (ICEA), University of Padova, 35100 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8184-013X","authenticated-orcid":false,"given":"Massimo","family":"De Marchi","sequence":"additional","affiliation":[{"name":"Advanced Master GIScience and UAS, Department of Civil, Environmental and Architectural Engineering (ICEA), University of Padova, 35100 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1693-7709","authenticated-orcid":false,"given":"Franco","family":"Meggio","sequence":"additional","affiliation":[{"name":"Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Padova, Italy"},{"name":"Interdepartmental Research Centre for Viticulture and Enology (CIRVE), University of Padova, Via XXVIII Aprile 14, 31015 Treviso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2253","DOI":"10.2135\/cropsci2005.11.0416gas","article-title":"A top 10 list of developments and issues impacting crop management and ecology during the past 50 years","volume":"46","author":"Crookston","year":"2006","journal-title":"Crop Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"111402","DOI":"10.1016\/j.rse.2019.111402","article-title":"Remote sensing for agricultural applications: A meta-review","volume":"236","author":"Weiss","year":"2020","journal-title":"Remote Sens. 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