Large-scale monitoring of California vineyards with Sentinel-2 time-series

Baptiste Oger; Mahyar Aboutalebi; Brent Sams; Nick Dokoozlian; Maria Mar Alsina

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Large-scale monitoring of California vineyards with Sentinel-2 time-series

In: Precision agriculture '25

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Baptiste Oger

Baptiste Oger

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Mahyar Aboutalebi

Mahyar Aboutalebi

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Brent Sams

Brent Sams

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Nick Dokoozlian

Nick Dokoozlian

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Maria Mar Alsina

Maria Mar Alsina

mariadelmar.alsina@irta.cat

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Type:: Chapter

Pages:: 775–782

DOI:: https://doi.org/10.1163/9789004725232_102

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Dar Hadith al Hassania

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Remote sensing has become a valuable tool for enhancing agricultural efficiency. However, its application in vineyards is challenging due to the high variability of viticultural systems coexisting. Using Sentinel-2 time series data from 1,014 vineyards across California, this study analysed the influence of the region and vineyard characteristics on seasonal growth patterns and introduced a clustering approach to categorize vineyards into six typologies of expected growth behaviour. The results show that region, followed by vineyard age, row spacing, and trellis type, are key factors influencing clustering. The proposed clustering method showcases the potential of remote sensing to support large-scale, data-driven decision-making in viticulture.

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Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

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- Life Sciences
  - General
  - Agriculture & Environment

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Large-scale monitoring of California vineyards with Sentinel-2 time-series

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Precision agriculture '25

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