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Journal of Applied Remote Sensing • Open Access

Satellite-based land use mapping: comparative analysis of Landsat-8, Advanced Land Imager, and big data Hyperion imagery
Author(s): Wasim Pervaiz; Vali Uddin; Shoab Ahmad Khan; Junaid Aziz Khan

Paper Abstract

Until recently, Landsat technology has suffered from low signal-to-noise ratio (SNR) and comparatively poor radiometric resolution, which resulted in limited application for inland water and land use/cover mapping. The new generation of Landsat, the Landsat Data Continuity Mission carrying the Operational Land Imager (OLI), has improved SNR and high radiometric resolution. This study evaluated the utility of orthoimagery from OLI in comparison with the Advanced Land Imager (ALI) and hyperspectral Hyperion (after preprocessing) with respect to spectral profiling of classes, land use/cover classification, classification accuracy assessment, classifier selection, study area selection, and other applications. For each data source, the support vector machine (SVM) model outperformed the spectral angle mapper (SAM) classifier in terms of class discrimination accuracy (i.e., water, built-up area, mixed forest, shrub, and bare soil). Using the SVM classifier, Hyperion hyperspectral orthoimagery achieved higher overall accuracy than OLI and ALI. However, OLI outperformed both hyperspectral Hyperion and multispectral ALI using the SAM classifier, and with the SVM classifier outperformed ALI in terms of overall accuracy and individual classes. The results show that the new generation of Landsat achieved higher accuracies in mapping compared with the previous Landsat multispectral satellite series.

Paper Details

Date Published: 7 April 2016
PDF: 20 pages
J. Appl. Rem. Sens. 10(2) 026004 doi: 10.1117/1.JRS.10.026004
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Wasim Pervaiz, National Univ. of Sciences and Technology (Pakistan)
Vali Uddin, Hamdard Univ. (Pakistan)
Shoab Ahmad Khan, National Univ. of Sciences and Technology (Pakistan)
Junaid Aziz Khan, National Univ. of Sciences and Technology (Pakistan)

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