Highlights We propose a novel technique – Variable Endmember Constrained Least Square (VECLS). This accounts for the endmember variability into the LMM through class covariance matrices. VECLS is first tested with a computer simulated data having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS.
Abstract Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class.
Assimilation of endmember variability in spectral mixture analysis for urban land cover extraction
Advances in Space Research ; 52 , 11 ; 2015-2033
2013-08-16
19 pages
Article (Journal)
Electronic Resource
English
Assimilation of endmember variability in spectral mixture analysis for urban land cover extraction
Online Contents | 2013
|