PT - JOURNAL ARTICLE AU - Oger, Baptiste AU - Aboutalebi, Mahyar AU - Dokoozlian, Nick AU - Sanchez, Luis AU - Alsina, Maria Mar TI - Vineyard Design, Vine Age, and Floor Management Practices Affect Sentinel-2 NDVI Time Series Analysis of California Vineyards AID - 10.5344/ajev.2025.25010 DP - 2025 Sep 01 TA - American Journal of Enology and Viticulture PG - 0760023 VI - 76 IP - 2 4099 - http://www.ajevonline.org/content/76/2/0760023.short 4100 - http://www.ajevonline.org/content/76/2/0760023.full SO - Am J Enol Vitic.2025 Sep 01; 76 AB - Background and goals Monitoring vineyards with remote sensing tools is challenging due to the site specificity and difficulty of accurately scaling the technology across large regions. To overcome these challenges, this study aimed to understand how a time series of remote sensing vegetation indices is influenced by vineyard design, vine age, and vineyard floor management practices.Methods and key findings We examined Sentinel-2 time series data over a 5-yr period from over 1000 vineyard blocks covering more than 10,000 ha across California. Our analysis revealed a strong annual effect and a significant impact of vine trellis-training systems. Vine age was particularly relevant for blocks younger than 3 yr and older than 25 yr, while factors such as variety and row distance (ranging from ~2 to 4 m) were less significant. We also found that remote sensing vegetation indices calculated from the top of the canopy were less relevant for vines grown on the vertical shoot-positioned trellis compared to vines grown on other trellis systems.Conclusions and significance These findings help define key vineyard characteristics that influence the normalized difference vegetation index and potentially other commonly used vegetation indices. They provide new insights into the factors that must be considered when using remote sensing data across heterogeneous sets of vineyard blocks, as well as the characteristic seasonal pattern for each factor. This work paves the way for large-scale vineyard monitoring using satellite-based vegetation indices.