Object-based classification of very high resolution panchromatic images for evaluating recent change in the structure of patterned peatlands

An airphoto survey carried out at the La Grande hydroelectrical complex (James Bay, Quebec) revealed numerous signs of degradation of patterned fens, with a decrease in terrestrial vegetation and increase in ponds, a process known as aqualysis. The principal goal of this study is to provide information on the present and past (the last 50 years) state of patterned peatlands, associated with the pattern of the aquatic and terrestrial compartments, and to evaluate their changing cover using remote sensing techniques. In this paper, we present a semi-automated, object-based method for QuickBird panchromatic image classification. The method emphasizes contextual information. We have also integrated texture images calculated in advance as supplementary data layers in the process of segmentation and classification. The validation of QuickBird image classification shows that the proposed method can delineate peatlands with 95% producer’s accuracy and 88% user’s accuracy. The overall classification accuracy in the peatlands is 81%. The same robust technique was applied to the aerial photographs taken in 1957. The classification of QuickBird images and aerial photographs was used to assess the structural development of patterned peatlands in the La Grande 3 sector over the last 50 years. The analysis shows an increase in aquatic areas for only two out of seven studied peatlands. To confirm our hypothesis of active aqualysis, additional image analysis is required from other areas of the La Grande hydroelectrical complex where the aqualysis process is more pronounced.

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