Classification extraction of land coverage in the Ejina Oasis by airborne hyperspectral remote sensing

Yang Su; Yuan Qi; Jianhua Wang; Feinan Xu; Jinlong Zhang

doi:10.1117/12.2264804

8 March 2017 Classification extraction of land coverage in the Ejina Oasis by airborne hyperspectral remote sensing

Yang Su, Yuan Qi, Jianhua Wang, Feinan Xu, Jinlong Zhang

Proceedings Volume 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016; 102551W (2017) https://doi.org/10.1117/12.2264804
Event: Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 2016, Jinhua, Suzhou, Chengdu, Xi'an, Wuxi, China

Abstract

The hyperspectral data of the Ejina Oasis is performed dimensionality reduction by the minimum noise fraction transform, classified by the maximum likelihood method and clustering processing and finally, the classification of land coverage is obtained. The thesis analyzes the results of two dimensionality reductions, and finds the superiority of the minimum noise fraction. In the classification of land coverage, the overall accuracy and Kappa coefficient are respectively 87.75% and 0.8401. The classification is of high precision and can provide effective parameters for ecological research.

Citation Download Citation

Yang Su, Yuan Qi, Jianhua Wang, Feinan Xu, and Jinlong Zhang "Classification extraction of land coverage in the Ejina Oasis by airborne hyperspectral remote sensing", Proc. SPIE 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 102551W (8 March 2017); https://doi.org/10.1117/12.2264804

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