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) | |
Ridwan, Ichsan1  | |
关键词: ANN; Mangkauk Catchment Area; Land Cover; SVM; | |
DOI : 10.3844/ajassp.2017.726.736 | |
学科分类:自然科学(综合) | |
来源: Science Publications | |
【 摘 要 】
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.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201902010967257ZK.pdf | 440KB | download |