Optimal estimation for imaging spectrometer atmospheric correction
By David Ray Thompson, Vijay Natraj, Robert O. Green, M. Helmlinger, B. Gao, M. Eastwood. Remote Sensing of Environment, 2018
172 citations recorded by the source corpus.
Abstract We present a new method for atmospheric correction of remote Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Our approach fits a combined model of atmospheric scattering, absorption, and surface reflectance across the solar reflected interval from 380 to 2500 nm. This can estimate spectrally-broad atmospheric perturbations such as aerosol effects that are difficult to retrieve with narrow spectral windows. A probabilistic formulation from Optimal Estimation inversion theory accounts for uncertainties in model parameters and measurement noise. This paper presents a field experiment using NASA's Next Generation Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG) with analysis of retrieval accuracy and information content. The inversion outperforms traditional approaches, achieving mean reflectance accuracy of 1.0% on diverse validation surfaces. Predicted posterior distributions fully explain the observed discrepancies, demonstrating the first closed uncertainty budget for VSWIR imaging spectrometer atmospheric correction. This shows the potential of combined surface/atmosphere fitting to advance the accuracy and statistical rigor of remote reflectance measurements.
Subfields: Aerospace Engineering, Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/1cfa94bc862f74274ec25fd8ec579423b4e7139a
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Citations in the corpus
- The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission (2020, background): “Atmospheric correction compensates for the atmosphere and solar illumination geometry to deliver as surface reflectance product (Gao 1993, Thompson et al., 2015, 2018, 2019).”