Experimental vegetation mapping study using remote sensing

The purpose of this study is to evaluate the potential of aerial and satellite imageries of high spatial resolution for large scale vegetation mapping on Brittany, Normandy and Pays de la Loire regions at 1/25 000. Different types of images (BDORTHO (R) IRC, SPOT5, Worldview-2) were acquired for four sites which represent vegetation diversity in the North-West of France. Classification processes were established and their reproducibility was assessed on another site. The classification used is the nested classification system of the National Botanical Conservatory of Brest (CBN), that schedules a phytosociological typology and a physiognomical typology. This nested classification system is compatible with remote sensing. An object-oriented classification was applied on images. It was combined with pixel-based classification when applied on the Worldview-2 image. Results were evaluated at three classification levels, corresponding to land cover, large vegetation types, and plant formation types. Best results, from more conclusive to less conclusive, were obtained with Worldview-2 image, then BDORTHO (R) IRC and then SPOT5 images. Some results are not satisfactory for some classes of plant formation type level, but they could be improved in adding photo-interpretation in post-processing, in using multi-date images from different sensors and in using GIS data.