NDVI-based vigour maps production using automatic detection of vine rows in ultra-high resolution aerial images
In: Precision agriculture '15Search for other papers by J. Primicerio in
Current site
Google Scholar
PubMed
Search for other papers by P. Gay in
Current site
Google Scholar
PubMed
Search for other papers by D. Ricauda Aimonino in
Current site
Google Scholar
PubMed
Search for other papers by L. Comba in
Current site
Google Scholar
PubMed
Search for other papers by A. Matese in
Current site
Google Scholar
PubMed
Search for other papers by S.F. di Gennaro in
Current site
Google Scholar
PubMed
Purchase instant access (PDF download and unlimited online access):
In this paper, a new method to produce accurate vigour maps using a vine row automatic detection process is presented. It has been applied to 5 cm ground resolution multispectral aerial images (NIR, red, green). NDVI index has been calculated for pre-processed images, obtained by the selection of pixels that represent vine rows, masking non-vine vegetation and other background elements. The adopted pre-processing settlement is constituted by three steps based on dynamic segmentation, Hough Space Clustering and Total Least Squares techniques. The adaptive features of the algorithm make it robust in the presence of inter-row grassing, tree shadows and non-uniform image illumination.