Method to analyze remotely sensed spectral data
Abstract
A fast and rigorous multivariate curve resolution (MCR) algorithm is applied to remotely sensed spectral data. The algorithm is applicable in the solar-reflective spectral region, comprising the visible to the shortwave infrared (ranging from approximately 0.4 to 2.5 .mu.m), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 .mu.m). For example, employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, MCR can be used to successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. Further, MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of a gas plume component near the minimum detectable quantity.
- Inventors:
-
- Albuquerque, NM
- Middletown, DE
- Publication Date:
- Research Org.:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 960205
- Patent Number(s):
- 7,491,944
- Application Number:
- 11/410,445
- Assignee:
- Sandia Corporation (Albuquerque, NM)
- DOE Contract Number:
- AC04-94AL85000
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Stork, Christopher L, and Van Benthem, Mark H. Method to analyze remotely sensed spectral data. United States: N. p., 2009.
Web.
Stork, Christopher L, & Van Benthem, Mark H. Method to analyze remotely sensed spectral data. United States.
Stork, Christopher L, and Van Benthem, Mark H. 2009.
"Method to analyze remotely sensed spectral data". United States. https://www.osti.gov/servlets/purl/960205.
@article{osti_960205,
title = {Method to analyze remotely sensed spectral data},
author = {Stork, Christopher L and Van Benthem, Mark H},
abstractNote = {A fast and rigorous multivariate curve resolution (MCR) algorithm is applied to remotely sensed spectral data. The algorithm is applicable in the solar-reflective spectral region, comprising the visible to the shortwave infrared (ranging from approximately 0.4 to 2.5 .mu.m), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 .mu.m). For example, employing minimal a priori knowledge, notably non-negativity constraints on the extracted endmember profiles and a constant abundance constraint for the atmospheric upwelling component, MCR can be used to successfully compensate thermal infrared hyperspectral images for atmospheric upwelling and, thereby, transmittance effects. Further, MCR can accurately estimate the relative spectral absorption coefficients and thermal contrast distribution of a gas plume component near the minimum detectable quantity.},
doi = {},
url = {https://www.osti.gov/biblio/960205},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Feb 17 00:00:00 EST 2009},
month = {Tue Feb 17 00:00:00 EST 2009}
}
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