Reconstructing the within-field spatio-temporal variability of a vineyard from data sampled in time and space

V.H.H. Pham; F. Rançon; J.-P. Da Costa

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Reconstructing the within-field spatio-temporal variability of a vineyard from data sampled in time and space

In: Precision agriculture '25

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V.H.H. Pham

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F. Rançon

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J.-P. Da Costa

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Type:: Chapter

Pages:: 901–908

DOI:: https://doi.org/10.1163/9789004725232_118

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Dar Hadith al Hassania

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In precision viticulture, understanding the spatial and temporal variability of plots is critical. Optical sensors are commonly used to measure this variability, but challenges remain in optimising spatial and temporal sampling strategies. The aim of this study was to reconstruct the spatio-temporal variability of a vineyard using two different data sources, temporal data from fixed points and spatially exhaustive maps at a few dates. Two methods - spatio-temporal kriging and generalised additive models - were evaluated on two leaf area datasets from a simulated vineyard: one homogeneous and one with strong field heterogeneities. The root mean square percentage errors calculated show that while both methods perform well, the reconstruction accuracy depends on the sampling strategy, with errors ranging from 2% to 10%. Increasing the amount of sensor data improves the accuracy, although the benefits plateau after a certain point.

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Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Reconstructing the within-field spatio-temporal variability of a vineyard from data sampled in time and space

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Precision agriculture '25

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