Techniques for accuracy assessment of tree locations extracted from remotely sensed imagery

Remotely sensed imagery is becoming a common source of environmental data. Consequently, there is an increasing need for tools to assess the accuracy and information content of such data. Particularly when the spatial resolution of imagery is fine, the accuracy of image processing is determined by comparisons with field data. However, the nature of error is more difficult to assess. In this paper we describe a set of tools intended for such an assessment when tree objects are extracted and field data are available for comparison. These techniques are demonstrated on individual tree locations extracted from an IKONOS image via local maximum filtering. The locations of the extracted trees are compared with field data to determine the number of found and missed trees. Aspatial and spatial (Voronoi) analysis methods are used to examine the nature of errors by searching for trends in characteristics of found and missed trees. As well, analysis is conducted to assess the information content of found trees.