Arctic tundra ice-wedge landscape characterization by active contours without edges and structural analysis using high-resolution satellite imagery

In this letter, we present a semi-automated approach to identify and classify Arctic polygonal tundra landscape components, such as troughs, ponds, rivers and lakes, using high spatial resolution satellite imagery. The approach starts by segmenting water bodies from an image, which are then categorized using shape-based classification. Segmentation uses combination of multispectral bands and is based on the active contours without edges technique. The segmentation is robust to noise and can detect objects with weak boundaries, which is important for the extraction of troughs. Classification of the regions is accomplished by utilizing distance transform and regional structural characteristics. The approach is evaluated using 0.6m resolution WorldView-2 satellite image of ice-wedge polygonal tundra. The segmentation user's and producer's accuracies are approximately 92% and 97%, respectively. Visual inspection of the classification results has demonstrated qualitatively accurate object categorization.