Support Vector Machine and Spectral Angle Mapper Classifications of High Resolution Hyper Spectral Aerial Image

Support Vector Machine and Spectral Angle Mapper Classifications of High Resolution Hyper Spectral Aerial Image
Support Vector Machine and Spectral Angle Mapper Classifications of High Resolution Hyper Spectral Aerial Image

ㆍ 저자명: Enkhbaatar. Lkhagva,Jayakumar. S.,Heo. Joon
ㆍ 간행물명: 大韓遠隔探査學會誌
ㆍ 권/호정보: 2009년|25권 3호|pp.233-242 (10 pages)
ㆍ 발행정보: 대한원격탐사학회
ㆍ 파일정보: 정기간행물|ENG|
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ㆍ 주제분야: 기타

이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.

서지반출

기타언어초록

This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

키워드

supervised classification support vector machine classifier spectral angle mapper classifier high resolution aerial image

다운URL