Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery

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 implement...

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Main Authors: Shanshan Feng, Fenglei Fan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9298822/
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spelling doaj-aae6288accb64e738ade26b4956200ae2021-06-03T23:06:01ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01141434144610.1109/JSTARS.2020.30457129298822Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral ImageryShanshan Feng0https://orcid.org/0000-0001-6283-9707Fenglei Fan1https://orcid.org/0000-0001-6190-9072School of Geography, South China Normal University, Guangzhou, ChinaSchool of Geography, South China Normal University, Guangzhou, ChinaThe 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.https://ieeexplore.ieee.org/document/9298822/Endmember abundancehyperspectrallinear spectral mixture analysis (LSMA)spectral interferencespectral similarity measure
collection DOAJ
language English
format Article
sources DOAJ
author Shanshan Feng
Fenglei Fan
spellingShingle Shanshan Feng
Fenglei Fan
Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Endmember abundance
hyperspectral
linear spectral mixture analysis (LSMA)
spectral interference
spectral similarity measure
author_facet Shanshan Feng
Fenglei Fan
author_sort Shanshan Feng
title Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
title_short Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
title_full Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
title_fullStr Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
title_full_unstemmed Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery
title_sort analyzing the effect of the spectral interference of mixed pixels using hyperspectral imagery
publisher IEEE
series IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
issn 2151-1535
publishDate 2021-01-01
description 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.
topic Endmember abundance
hyperspectral
linear spectral mixture analysis (LSMA)
spectral interference
spectral similarity measure
url https://ieeexplore.ieee.org/document/9298822/
work_keys_str_mv AT shanshanfeng analyzingtheeffectofthespectralinterferenceofmixedpixelsusinghyperspectralimagery
AT fengleifan analyzingtheeffectofthespectralinterferenceofmixedpixelsusinghyperspectralimagery
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