Viticulture is progressively adopting the tools provided by Precision Agriculture, earlier used for other crops. The success of Precision Viticulture has required more precise imaging sensors to be available and more complex computing algorithms to be developed to overcome some of the difficult issues it has necessary to address to, particularly the discontinuous and non-uniformly shaped canopies it has to deal with. Our research presents some research from a 200 ha vineyard at Olite (Navarra, Spain), where a NDVI mapping was performed out of 0.3 m resolution multispectral image taken at veraison. Four classes were established according to NDVI values, and 64 sampling points were marked. Agronomical values measured at these 64 points were used to compare the defined classes with vineyard field performance. The obtained results suggest that a classification made out just from NDVI values is not relevant enough to establish vineyard management units since,though it is well related to vegetative growth, it cannot explain differences in grape composition. Grape quality is known to be heavily affected by many other agronomic circumstances, and fruit load in particular has probably to be taken into account to explain grape quality differences. Taking these two information sources into account (NDVI and fruit load) would probably allow establishing vineyard management units, although further research is needed.