An improved unmixing-based fusion method: Potential application to remote monitoring of Inland waters

Abstract

Although remote sensing technology has been widely used to monitor inland water bodies; the lack of suitable data with high spatial and spectral resolution has severely obstructed its practical development. The objective of this study is to improve the unmixing-based fusion (UBF) method to produce fused images that maintain both spectral and spatial information from the original images. Images from Environmental Satellite 1 (HJ1) and Medium Resolution Imaging Spectrometer (MERIS) were used in this study to validate the method. An improved UBF (IUBF) algorithm is established by selecting a proper HJ1-CCD image band for each MERIS band and thereafter applying an unsupervised classification method in each sliding window. Viewing in the visual sense-the radiance and the spectrum-the results show that the improved method effectively yields images with the spatial resolution of the HJ1-CCD image and the spectrum resolution of the MERIS image. When validated using two datasets; the ERGAS index (Relative Dimensionless Global Error) indicates that IUBF is more robust than UBF. Finally, the fused data were applied to evaluate the chlorophyll a concentrations (C chla) in Taihu Lake. The result shows that the C chla map obtained by IUBF fusion captures more detailed information than that of MERIS.