We present a complete framework for vigour mapping in row crops by multispectral remote sensing. The main contribution consists in taking into account vegetation abundance in the computation of vigour indexes. Though developed in a viticulture context, the proposed algorithm is generic enough to be adapted to any row crop, especially in horticulture. It takes advantage of both spectral and spatial features extracted from image data. Spectral information is used at pixel level by an ICA-based algorithm to process vegetation abundance maps. As for spatial information, deformable models are used to fit a network of rectangles to individual plants. Both spectral and spatial information are then combined to compute abundance-weighted vigour indexes which are assigned to specific plants. Resulting measurements are then used for within block vigour mapping. A validation procedure is carried out on experimental vine plots. It is shown that the use of vegetation abundance by itself or as a weight in the computation of vegetation indexes allows to improve the accuracy of vigour assessment in row crops.