University of Bahrain
Scientific Journals

Calculating Spectral Index Based on Linear SVM Methods for Landsat OLI: Baiji Sand Dunes a Case Study, Iraq

Show simple item record Al-Zubaidi, Ehsan Ali Rabee, Furkan H. Al-Sulttani, Ahmed 2023-03-16T08:01:54Z 2023-03-16T08:01:54Z 2023-03-16
dc.identifier.issn 2210-142X
dc.description.abstract Machine learning and remote sensing technologies can effectively investigate and monitor the dynamic features of dunes, sand accumulations, and environmental changes. However, the present article examines the performance of models constructed using various Linear SVM model implementations during the binary classification task. In R software, three linear SVM libraries (LibSVM, LibLINEAR, and GLM) are used to find the optimal and accurate spectral sand index. The data of Landsat-8 (OLI) satellite is used and calibrated to reflectance value, and then 15 sequences of Normalized Difference (ND) are generated. The most important and weighted NDs among the 15 trained have been chosen (ND34, ND47, and ND57). Nine Linear SVM methods have been calculated. LibLINEAR library contains several classification types (LibLINEAR1 to LibLINEAR7). The accuracy of the result images is done by assigning random points to six levels 500 to 1000 points according to the reference image created by supervised classification. The average Kappa and overall accuracy for all levels of random points show that the optimal three methods are LibL1, LibL7, and LibL3; with Kappa values of 77.20%, 76.96%, and 76.83%, respectively, and overall accuracy values of 88.60%, 88.48%, and 88.41%, respectively. In contrast, the widely used LibSVM shows less accuracy with more execution time than LibLINEARs. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject SVM, LibSVM, LibLINEAR, GLM, Remote Sensing, Sand Dunes Index en_US
dc.title Calculating Spectral Index Based on Linear SVM Methods for Landsat OLI: Baiji Sand Dunes a Case Study, Iraq en_US
dc.type Article en_US
dc.volume 13 en_US
dc.issue 1 en_US
dc.pagestart 437 en_US
dc.pageend 450 en_US
dc.contributor.authoraffiliation Department of Computer Science,Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq en_US
dc.contributor.authoraffiliation Department of Environmental Planning,Faculty of Physical Planning, University of Kufa, Najaf, Iraq en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

Files in this item

This item appears in the following Issue(s)

Show simple item record

All Journals

Advanced Search


Administrator Account