Increasing and Evaluating the Reliability of Multiple Endmember Spectral Mixture Analysis (mesma)

Evaluating Endmember and Band Selection Techniques for Multiple Endmember Spectral Mixture Analysis using Post-Fire Imaging Spectroscopy

Fire impacts many vegetated ecosystems across the world. The severity of a fire is major component in determining post-fire effects, including soil erosion, trace gas emissions, and the trajectory of recovery. In this study, we used imaging spectroscopy data combined with Multiple Endmember Spectral Mixture Analysis (MESMA), a form of spectral mixture analysis that accounts for endmember variab...

Development of a Class-Based Multiple Endmember Spectral Mixture Analysis (C-MESMA) Approach for Analyzing Urban Environments

Multiple endmember spectral mixture analysis (MESMA) has been widely applied for estimating fractional land covers from remote sensing imagery. MESMA has proven effective in addressing inter-class and intra-class endmember variability by allowing pixel-specific endmember combinations. This method, however, assumes that each land cover type has an equal probability of being included in the model...

Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE

Multiple endmember spectral mixture analysis (MESMA) models mixed spectra as a linear combination of endmembers that are allowed to vary in number and type on a per pixel basis. For modeling an image using MESMA, a parsimonious set of endmembers is desirable for computational efficiency and operational simplicity. This paper presents a method of selecting endmembers from a spectral library for ...

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

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. Theref...

Effect of image spatial and spectral characteristics on mapping semi-arid rangeland vegetation using multiple endmember spectral mixture analysis (MESMA)