Method to analyze remotely sensed spectral data
- Albuquerque, NM
- Middletown, DE
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.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM
- Sponsoring Organization:
- United States Department of Energy
- DOE Contract Number:
- AC04-94AL85000
- Assignee:
- Sandia Corporation (Albuquerque, NM)
- Patent Number(s):
- 7,491,944
- Application Number:
- 11/410,445
- OSTI ID:
- 960205
- Country of Publication:
- United States
- Language:
- English
Similar Records
imageMCR
Reducing System Artifacts in Hyperspectral Image Data Analysis with the Use of Estimates of the Error Covariance in the Data