Abstract
The widespread presence of mixed pixels in remotely sensed images is a pressing challenge for accurate target detection and classification. Linear spectral mixture analysis (LSMA) is commonly used to address this problem by deriving remotely sensed information at the subpixel level. In the implementation of LSMA, the effects of mixed-pixel spectral interference need to be taken into account; mixed spectra would exhibit as a pure spectral characteristic when the abundance of one endmember in a mixed pixel exceeds a specific threshold. However, the thresholds of endmember abundance resulting in mixed-pixel spectral interference remain unclear. Thus, this study designed an experiment to analyze the effect of the spectral interference of mixed pixels and to identify the thresholds causing such interference by spectral similarity measures (spectral angle and spectral distance). Four types of pure endmember spectra (vegetation, high-albedo impervious surface (HIS), low-albedo impervious surface (LIS), soil) and corresponding representative mixed spectra with endmember abundances of 95%-5% at intervals of 5% were collected from Earth Observing-1 Hyperion imagery. Spectral similarity measures among the pure endmember spectra and representative mixed spectra were used to determine the thresholds of endmember abundance that cause spectral interference. The results verified the effect of the spectral interference of mixed pixels. The thresholds of abundance causing mixed-pixel spectral interference in vegetation, HIS, LIS, and soil endmembers were 70%, 75%, 80%, and 70%, respectively. Therefore, when the endmember abundance within mixed pixels exceeds the abovementioned thresholds, these mixed spectra are interfered and would exhibit as a pure spectral characteristic. Accordingly, interfered mixed pixels have to be removed before applying LSMA or other unmixing methods to avoid the effect of spectral interference.
Highlights
A LL GROUND surfaces consisting of individual pixels of remote-sensing imagery are considered spatially heterogeneous on some scale [1], [2]
When the endmember abundance of mixed pixels exceeds the abovementioned thresholds, these mixed spectra would exhibit as pure spectral characteristics
Four pure endmember spectra and a large number of representative mixed spectra collected from an Earth Observing-1 (EO-1) Hyperion image were used to analyze the spectral characteristics of mixed pixels as the abundance changes of endmembers by spectral similarity measures
Summary
A LL GROUND surfaces consisting of individual pixels of remote-sensing imagery are considered spatially heterogeneous on some scale [1], [2]. The LSMA method assumes that the spectrum of each mixed pixel is expressed as a linear combination of the spectral signatures of the pure ground components (endmembers); this combination is weighted by these components’ corresponding areal proportions (abundance) within the pixel [11]. A specific endmember shows a varied spectral signature caused by differences in the illumination conditions within an image Under these circumstances, LSMA commonly uses the typical or average spectra of pure pixels to represent the endmember spectra [30]. This method assumes that all mixed spectra are linear mixtures of some set of endmember spectra and that these spectrally distinct endmembers within a pixel do not interfere with each other [34], [35]. Based on specific thresholds of abundances causing mixed-pixel spectral interference, interfered mixed pixels can be identified and removed before applying LSMA, or other unmixing methods to avoid the effect of spectral interference, so as to improve unmixing accuracy to some extent
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