An Object-oriented Approach to Urban Forest Mapping in Phoenix
By Jason S. Walker, J. Briggs. 2007
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.
Subfields: Remote Sensing
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Citations in the corpus
- Object‐based land‐cover classification for the Phoenix metropolitan area: optimization vs. transportability (2008, methodology): “Remote sensing has long provided monitoring capabilities for land-use and land-cover change in order to satisfy this need within the Phoenix metropolitan area (Grimm and Redman 2004, Möller 2005, Stefanov et al. 2001, Walker and Briggs 2007).”
- Object based image analysis for remote sensing (2010, methodology): “Walker and Briggs (2007) developed an object based classification approach for high resolution, true-colour aerial photography for the Phoenix Metropolitan area, and isolated vegetation patches ranging from shrubs to large trees for further analysis, while Walker and Blaschke (2008) adapted this…”