American Journal of Applied Sciences

Identification of Characteristics of Land Cover in Mangkauk Catchment Area Using Support Vector Machine (SVM) And Artificial Neural Network (ANN)

Ichsan Ridwan, Mohammad Bisri, Fadly Hairannoor Yusran, Luchman Hakim and Syarifuddin Kadir

DOI : 10.3844/ajassp.2017.726.736

American Journal of Applied Sciences

Volume 14, Issue 7

Pages 726-736

Abstract

Land cover is anything that includes any types of appearance on the surface of the earth on a particular land. Information related to land cover can be used as at the parameter to determine the amount of runoff in a catchment area. This study was conducted in the Catchment Area (CA) of Mangkauk using Landsat 8 OLI/TIRS 2014 scene path/row 117/62 with the methods of Support Vector Machine (SVM) and Artificial Neural Network (ANN). The classification of land cover in Mangkauk catchment area included forests, plantations, shrubs, reeds/grasses, rice fields, open lands, settlements and water body. Based on the accuracy test of land cover classification using SVM, the value of the overall accuracy was 97.22% with Kappa Coefficient 0.96, while using ANN 86.33% with Kappa Coefficient 0.79.

Copyright

© 2017 Ichsan Ridwan, Mohammad Bisri, Fadly Hairannoor Yusran, Luchman Hakim and Syarifuddin Kadir. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.