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Journal of Applied Sciences

Year: 2005 | Volume: 5 | Issue: 5 | Page No.: 834-837
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Authors

Amir Bonyad

Keywords

Research Article

Multitemporal Satellite Image Database Classification for Land Cover Inventory and Mapping

Amir Bonyad
A raster Geographic Information System (GIS) database file created whit 12 satellite remote sensing image layers of test area. A widely recognized characteristic of these image layers is correlated that exists between image channels. The Principle Component Analysis (PCA) was used to reduce the dimensionality of the input database and to produce new uncorrelated image layers. The first, second and third principle component analysis eigen-channels (PCA1, PCA2 and PCA3), accounted for 93.42% of the variance from the 12 input Landsat TM image channels. Total accuracy of this classification was 80.63%. The results of classified of land cover of the study area by PCA eigen-channels are satisfactory. This methodology may will allow the greater application of satellite remote sensing image databases in land cover type in the future.
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