Successful adoption of precision viticulture at the farm level depends on the appreciation of vineyard spatial variability. Knowing the spatial variability of soil properties is a challenge, often very expensive and labor intensive. An alternative approach could be the combined utilization of proximal and remote sensors. This study combined proximal (Geonics EM38-MK2) and remote (normalized difference vegetation index, NDVI) sensing aimed at mapping homogeneous zones (HZs) of two 3.5-ha vineyards in the Chianti wine district (Italy). Two HZs in each vineyard were obtained by a k-means clustering of the first two factors of the principal component analysis performed on four maps: (i) apparent electrical conductivity, obtained by EM38-MK2 at 0 to 75 cm (ECa₁) and (ii) 0 to150 cm (ECa₂); (iii) topographic wetness index (TWI), calculated from a digital elevation model; and (iv) NDVI extrapolated by multispectral airborne images. Only ECa₁ and ECa₂ were correlated with some physical (silt and gravel content) and hydrologic (available water capacity) features of the soils. These two variables could also better discriminate the two HZs with respect to NDVI and TWI. The grapes (Vitis vinifera L.) of the selected HZs were separately harvested and vinified to test the differences in the wine quality. Significant differences emerged between the wines produced from the two HZs, especially in terms of color intensity, dry extract, and anthocyanin content. A wine tasting after 6-mo aging of the wines confirmed the differences between the wines produced in the two zones, especially in terms of color, structure, and total score.