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A method for object-oriented land cover classification combining Landsat TM data and aerial photographs

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Object-oriented classification techniques based on image segmentation are gaining interest as methods for producing output maps directly storable into Geophysical Information System (GIS) databases. A limitation in efficiently applying image segmentation is often represented by the spatial resolution of the image. This contribution proposes a method for overcoming this problem, based on the integrated use of images of different resolution. A high-resolution black and white (b/w) orthophoto and a subscene of a Landsat Thematic Mapper (TM) image have been used to obtain an object-oriented classification of the land cover of a study area in northern Italy. The method consists of a sequential application of segmentation and classification techniques. First, the TM image was classified using the maximum likelihood classifier and additional empirical rules. Subsequently, the orthophoto was segmented by applying a region-based segmentation algorithm. Finally, the classification of the segmented images was performed using as a reference the TM image previously classified. The resulting land cover map was tested for accuracy and the results are dicusssed.
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Document Type: Research Article

Affiliations: 1: Geological Survey Division, International Institute for Aerospace Survey and Earth Science (ITC), PO Box 6, 7500AA Enschede, The Netherlands; e-mail: [email protected]; [email protected] 2: Department of Geodesy, Delft University of Technology, PO Box 5030, 2600GA Delft, The Netherlands; e-mail: [email protected]

Publication date: 2003-03-01

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