The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 267–270, 2018
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 267–270, 2018

  30 Apr 2018

30 Apr 2018


Y. Deng and C. Wu Y. Deng and C. Wu
  • Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, USA

Keywords: Spectral Transformation, Spectral Mixture Analysis, NSMA, BWVI, Between-class Variance, Within-class Variance, Total-class Variance

Abstract. While many spectral transformation techniques have been applied on spectral mixture analysis (SMA), few study examined their necessity and applicability. This paper focused on exploring the difference between spectrally transformed schemes and untransformed scheme to find out which transformed scheme performed better in SMA. In particular, nine spectrally transformed schemes as well as untransformed scheme were examined in two study areas. Each transformed scheme was tested 100 times using different endmember classes’ spectra under the endmember model of vegetation- high albedo impervious surface area-low albedo impervious surface area-soil (V-ISAh-ISAl-S). Performance of each scheme was assessed based on mean absolute error (MAE). Statistical analysis technique, Paired-Samples T test, was applied to test the significance of mean MAEs’ difference between transformed and untransformed schemes. Results demonstrated that only NSMA could exceed the untransformed scheme in all study areas. Some transformed schemes showed unstable performance since they outperformed the untransformed scheme in one area but weakened the SMA result in another region.