Mapping vineyard folliage density with multispectral proxidection imagery

This paper presents a new multispectral imaging system and a new approach to map vineyard leaf development in the context of Precision Viticulture. It is based on the use of a 2-CCD camera (RGB/NIR). This camera is embedded on a track laying tractor and associated with a GNSS system. It works with natural ambient light. A Greenseeker is also embedded to validate the first results of imagery. It is a sensor usually used in viticulture to assess the foliage density of vines. The images are calibrated in order to correct geometric distortion and variations of the natural light. The parameters of the geometric correction are stable over time, whereas the radiometric correction needs to include a color checker in the background of all the images. For each of them, a calibration model is computed and reflectance of objects is obtained. The calibrated images can be compared with each other. During 2013, four datasets of about 5000 images were acquired. For all the images, a vegetation index is performed to retrieve agronomic information. Based on these images, different vineyard maps were generated with calibrated images, with non-calibrated images, and with Greenseeker values. We present and discuss some of them in order to assess the relevancy of the approach.