DocumentCode
314791
Title
Comparing raster and object generalization
Author
Daley, Nigel ; Goodenough, David G. ; Bhogal, A. S Pal ; Bradley, Quetzalcoatl ; Yin, Z.
Author_Institution
Pacific Forestry Centre, Victoria, BC, Canada
Volume
2
fYear
1997
fDate
3-8 Aug 1997
Firstpage
677
Abstract
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. The authors 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
Keywords
forestry; geographic information systems; geophysical signal processing; geophysical techniques; geophysics computing; image processing; image segmentation; object-oriented databases; object-oriented methods; remote sensing; GIS; MapGen; ObjectGen; forest; forestry; geographic information system; geophysical measurement technique; image processing; image segmentation; object generalization; object-oriented method; raster generalization; remote sensing; vegetation mapping; Computer science; Forestry; Geographic Information Systems; Hydrology; Image resolution; Image segmentation; Photography; Remote sensing; Spatial resolution; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International
Print_ISBN
0-7803-3836-7
Type
conf
DOI
10.1109/IGARSS.1997.615221
Filename
615221
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