Delineating Individual Tree Crowns in an Uneven-Aged, Mixed Broadleaf Forest Using Multispectral Watershed Segmentation and Multiscale Fitting

Delineating individual tree crowns (ITCs) in high-spatial-resolution images can help to improve forest inventory and management. However, single-band watershed segmentation methods often fail to delineate broadleaf species, particularly in uneven-aged stands when a single-scale parameter is used to fit segments to reference crowns of different sizes. In this study, we present multispectral watershed segmentation and multiscale fitting method for ITC delineation, and the method involves two steps: 1) multispectral watershed segmentation to produce multiscale segmentation for subsequent fitting, which takes full advantage of boundary information contained in the spectral contrast of multiple bands; and 2) multiscale fitting to identify optimal parameters to best fit each ITC, rather than selecting a single parameter value based on its overall fit to the image as a whole. We evaluate the effectiveness of the proposed method using two multispectral images from a mixed broadleaf forest in Central Ontario, Canada. Our results show that multispectral watershed segmentation at multiple spatial scales produces ITC maps of higher quality than the commonly used multiresolution segmentation method. The automated multiscale fitting produces ITC maps of higher quality than the best single-scale segmentation.