Supervised and unsupervised classification for obtaining land use/cover classes from hyperspectral and multi-spectral imagery

M. S. Boori; R. Paringer; K. Choudhary; A. Kupriyanov

doi:10.1117/12.2322624

6 August 2018 Supervised and unsupervised classification for obtaining land use/cover classes from hyperspectral and multi-spectral imagery

M. S. Boori, R. Paringer, K. Choudhary, A. Kupriyanov

Author Affiliations +

Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 107730L (2018) https://doi.org/10.1117/12.2322624
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus

Abstract

In this study we compare supervised and unsupervised classification for land use/cover classes from hyperspectral and multispectral imagery. The algorithms include migrating means clustering (MMC) and k-nearest neighbor algorithm (KNN). We were analyzed and compared Earth Observing-1 (EO-1) Hyperion hyperspectral data to Landsat 8 Operational Land Imager (OLI) and Advance Land Imager (ALI) multispectral data. Validation of the derived landuse/cover maps from the above two algorithms was performed through error matrix statistics using the validation points from the very high resolution imagery. Results show that both classification have high accuracy and useful for land use/cover classification but supervised classification slightly outperforming than unsupervised classification by overall higher classification accuracy and kappa statistics. In addition, it is demonstrated that the hyperspectral satellite image provides more accurate classification results than those extracted from the multispectral satellite image. The higher classification accuracy by KNN supervised was attributed principally to the ability of this classifier to identify optimal separating classes with low generalization error, thus producing the best possible classes’ separation.

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M. S. Boori, R. Paringer, K. Choudhary, and A. Kupriyanov "Supervised and unsupervised classification for obtaining land use/cover classes from hyperspectral and multi-spectral imagery", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730L (6 August 2018); https://doi.org/10.1117/12.2322624

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