Method to analyze remotely sensed spectral data
| DWPI Title: Sensed spectral data analyzing method for e.g. aircraft remote sensing system, involves calculating atmospheric transmittance matrix and additive atmospheric component, and obtaining resolution estimate of subject to constraints |
| 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 mum), midwave infrared, and thermal emission spectral region, comprising the thermal infrared (ranging from approximately 8 to 15 mum). 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. |
| Use: Method for analyzing remotely sensed spectral data in satellite and aircraft remote sensing systems. Uses include but are not limited to aid weather prediction, agricultural forecasting, resource exploration, land cover mapping, environmental monitoring, industrial plant monitoring, civil defense, and military surveillance. |
| Advantage: The method analyzes the remotely sensed spectral data by utilizing a fast and rigorous multivariate curve resolution (MCR) algorithm effectively. The method performs rapid and comprehensive data exploitation of remotely sensed spectral data. The MCR focuses on recovering the end member and abundance profiles of the components in the unresolved mixture effectively, when the prior information is not available about the nature and composition of the mixtures. |
| Novelty: The method involves acquiring a remotely sensed spectral data set. The data set is modulated according to a specific formula. An atmospheric transmittance matrix and an additive atmospheric component are calculated to provide an atmospherically compensated data set according to another specific formula. A multivariate curve resolution (MCR) estimate of subject to constraints is obtained, where the data set includes solar-reflective spectral data, and midwave infrared spectral data. |
| Filed: 4/25/2006 |
| Application Number: US2006410445A |
| Tech ID: SD 7796.1 |
| This invention was made with Government support under Contract No. DE-NA0003525 awarded by the United States Department of Energy/National Nuclear Security Administration. The Government has certain rights in the invention. |
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