Ridwan, Ichsan Identification of Characteristics of Land Cover in Mangkauk Catchment Area Using Support Vector Machine (SVM) And Artificial Neural Network (ANN). Identification of Characteristics of Land Cover in Mangkauk Catchment Area Using Support Vector Machine (SVM) And Artificial Neural Network (ANN), 14 (7). pp. 726-736. ISSN 1554-3641
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Abstract
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. Keywords: ANN, Mangkauk Catchment Area, Land Cover, SVM
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Depositing User: | Mr Arief Mirathan |
| Date Deposited: | 29 Nov 2017 00:37 |
| Last Modified: | 29 Nov 2017 00:37 |
| URI: | http://eprints.ulm.ac.id/id/eprint/2494 |
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