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Applying Supervised Clustering to Landsat MSS Images into GIS-Application

Applying Supervised Clustering to Landsat MSS Images into GIS-Application

Miguel Torres, Marco Moreno-Ibarra, Rolando Quintero, Giovanni Guzmán
Copyright: © 2013 |Volume: 4 |Issue: 3 |Pages: 9
ISSN: 1947-8429|EISSN: 1947-8437|EISBN13: 9781466633612|DOI: 10.4018/ijksr.2013070110
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MLA

Torres, Miguel, et al. "Applying Supervised Clustering to Landsat MSS Images into GIS-Application." IJKSR vol.4, no.3 2013: pp.114-122. http://doi.org/10.4018/ijksr.2013070110

APA

Torres, M., Moreno-Ibarra, M., Quintero, R., & Guzmán, G. (2013). Applying Supervised Clustering to Landsat MSS Images into GIS-Application. International Journal of Knowledge Society Research (IJKSR), 4(3), 114-122. http://doi.org/10.4018/ijksr.2013070110

Chicago

Torres, Miguel, et al. "Applying Supervised Clustering to Landsat MSS Images into GIS-Application," International Journal of Knowledge Society Research (IJKSR) 4, no.3: 114-122. http://doi.org/10.4018/ijksr.2013070110

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Abstract

In this paper, the authors describe and implement an algorithm to perform a supervised classification into Landsat MSS satellite images. The Maximum Likelihood Classification method is used to generate raster digital thematic maps by means of a supervised clustering. The clustering method has been proved in Landsat MSS images of different regions of Mexico to detect several training data related to the geographic environment. The algorithm has been integrated into Spatial Analyzer Module to improve the decision making model and the spatial analysis into GIS-applications.

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