Comprehensive Spatial-Temporal Dataset for Precision Viticulture (2020-2021)

Over two growing seasons (2020-2021), this dataset offers comprehensive information on environmental factors and grapevine water status in a Vitis vinifera L. cv. Merlot vineyard located in Bakersfield, California, USA. It includes ground-based measurements of midday stem water potential, leaf gas exchange parameters, grape composition, soil data, and weather conditions, along with corresponding Landsat 8 satellite imagery. The study design features 24 experimental units aligned with Landsat 8 pixels, with biweekly measurements coinciding with satellite overpasses. Weather data from a nearby CIMIS station and Landsat 8 imagery with less than 10% cloud cover were acquired for all measurement dates. This dataset is valuable for researchers in viticulture, remote sensing, and agricultural sciences, offering opportunities to develop models for predicting grapevine water status using satellite imagery and machine learning techniques. It enables the exploration of spatial-temporal patterns in vineyard water status and the assessment of different cross-validation techniques for agricultural machine learning models.