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Published:
Aug 29, 2003
Keywords:
Landsat TM
supervised classification
remote sensing

Abstract

The objective of this study was to develop and evaluate a digital classification methodology for producing thematic cartography for the National Reserve in Valdivia using multispectral Landsat TM images. A supervised classification method with a maximum likelihood decision rule was selected for processing the satellite data. The proposed methodology permitted a separation of five different types of land uses, which corresponded to old native forest, secondary growth forest, plantation, shrub and grassland. Overall, the classification accuracy was about 64%, and the accuracy for the different forest types was about 77%. The results obtained can be considered acceptable, and are promising for the preliminary mapping of areas covered with native forests.

Reinaldo Segura M.
Guillermo Trincado V.
How to Cite
Segura M., R., & Trincado V., G. (2003). Digital cartography of the National Reserve in Valdivia based on Landsat TM images. Revista Bosque, 24(2), 43–52. Retrieved from https://revistabosque.org/index.php/bosque/article/view/1110

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