An object-oriented approach to urban forest mapping in Phoenix

We present a classification procedure in order to delineate woody vegetation in an arid urban ecosystem using highresolution, true-color aerial photography. We adopted an object-oriented approach due to the physical nature of highresolution photography, in which the objects of interest were typically composed of many pixels. The segmentation process was parameterized to isolate vegetation patches from shrubs to large trees. These objects were then spectrally analyzed for discrimination between woody vegetation and all other objects and a classification scheme developed. Accuracy within subclasses was analyzed and indicated highest accuracy for large, dense vegetation. Error was caused by the following plant typologies: small vegetation, sparse canopy density, and gray vegetation. The outset of this procedure produces a binary matrix where the entire raster set is classified highlighting the elements of the urban forest.