This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm.
The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.
This work was done by Seungwon Lee, Rachel A. Hodos, and Paul A. Von Allmen of Caltech for NASA’s Jet Propulsion Laboratory.
This software is available for commercial licensing. Please contact Daniel Broderick of the California Institute of Technology at
This Brief includes a Technical Support Package (TSP).
Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer
(reference NPO-47510) is currently available for download from the TSP library.
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Overview
The document discusses the development of quantitative and physics-based algorithms aimed at improving the quality of images captured through turbid atmospheres using a multi-angle, multiband spectrometer, specifically the Multiangle Imaging SpectroRadiometer (MISR). The primary objective is to accurately retrieve atmospheric and surface parameters to mitigate the hazing effects caused by light scattering in the atmosphere, thereby yielding clearer images of terrestrial targets.
The research focuses on the retrieval of surface reflectance data, particularly in the near-infrared (NIR) and visible bands (red, green, and blue). The document presents findings from tests conducted using synthetic satellite data, which were generated by applying a simplified atmospheric model to the MISR surface reflectance data collected over the Los Angeles area on February 3, 2009. The methodology involved fitting numerical model results to this synthetic data, where the measured nadir reflectances were assumed to represent the surface in the absence of atmospheric interference.
Figures included in the document illustrate the original surface reflectance images, synthetic images obtained from various viewing angles, and the retrieved surface reflectance images. Notably, the retrieval process demonstrated high success rates in areas of high surface reflectance, while challenges were encountered in low reflectance regions due to convergence issues with the optimization algorithm. The document highlights that these convergence problems were primarily due to poor initial conditions, which could be improved by using solutions from neighboring pixels in previous retrieval runs.
The findings underscore the importance of initial conditions in the retrieval process and suggest that refining these conditions can lead to more successful outcomes. The research emphasizes the potential of the developed algorithms to enhance the accuracy of atmospheric and surface parameter retrievals, which is crucial for various applications in remote sensing and environmental monitoring.
Overall, this work represents a significant advancement in the field of remote sensing, providing a framework for improving image quality in challenging atmospheric conditions. The research was conducted at the Jet Propulsion Laboratory, California Institute of Technology, under NASA sponsorship, and aims to contribute to broader technological, scientific, and commercial applications.
