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Remote Sens. 2015, 7(5), 6280-6295; doi:10.3390/rs70506280

An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels

State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
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Academic Editors: Chandra Giri and Prasad S. Thenkabail
Received: 18 November 2014 / Revised: 25 March 2015 / Accepted: 8 May 2015 / Published: 20 May 2015
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Abstract

Endmember selection is the basis for sub-pixel land cover classifications using multiple endmember spectral mixture analysis (MESMA) that adopts variant endmember matrices for each pixel to mitigate errors caused by endmember variability in SMA. A spectral library covering a large number of endmembers can account for endmember variability, but it also lowers the computational efficiency. Therefore, an efficient endmember selection scheme to optimize the library is crucial to implement MESMA. In this study, we present an endmember selection method based on vector length. The spectra of a land cover class were divided into subsets using vector length intervals of the spectra, and the representative endmembers were derived from these subsets. Compared with the available endmember average RMSE (EAR) method, our approach improved the computational efficiency in endmember selection. The method accuracy was further evaluated using spectral libraries derived from the ground reference polygon and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery respectively. Results using the different spectral libraries indicated that MESMA combined with the new approach performed slightly better than EAR method, with Kappa coefficient improved from 0.75 to 0.78. A MODIS image was used to test the mapping fraction, and the representative spectra based on vector length successfully modeled more than 90% spectra of the MODIS pixels by 2-endmember models. View Full-Text
Keywords: endmember selection; multiple endmember spectral mixture analysis (MESMA); vector length endmember selection; multiple endmember spectral mixture analysis (MESMA); vector length
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Xu, Y.; Shi, J.; Du, J. An Improved Endmember Selection Method Based on Vector Length for MODIS Reflectance Channels. Remote Sens. 2015, 7, 6280-6295.

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