Comparing Raster and Object Generalization

Digital interpretation of imagery produces descriptions of the earth’s surface, each description relying on the inherent resolution of the original image. Forest cover geographic information (GIS) files have been produced by interpretation of aerial photography. Common mapping scales in Canada for representing land information are 1:20,000 and 1:250,000. This paper discusses two methods to automatically generalize GIS from higher spatial resolution scales to lower scales. These two methods are a raster method (MapGen) for generalization developed by Pamap and the BC Ministry of Forests, and an object-oriented method (ObjectGen). The GIS data set consists of topographic data and forest cover files, both at 1:20,000 scale and placed on the same datum. In this presentation we compare the results for generalizing forest objects by these different methods. This work leads to segmentations of remote sensing images, at corresponding resolutions to the GIS files, being used to constrain the generalizations.