Abstract

In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model has been extended to cover the visible through longwave infrared portion of the optical spectrum (0.4–14 m). The model uses statistical descriptions of surface spectral reflectances/emissivities and temperature variations in a scene and propagates them through the effects of the atmosphere, the sensor, and processing transformations. A resultant system performance metric is then calculated based on these propagated statistics. This paper presents theory for the analytical transformation of surface statistics to at-sensor spectral radiance statistics for a downward-looking hyperspectral sensor observing both reflected sunlight and thermally emitted radiation. Comparisons of the model predictions with measurements from an airborne hyperspectral sensor are presented. Example parameter trades are included to show the utility of the model for applications in sensor design and operation.

Publication Date

2005

Comments

©2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. The authors acknowledge the support of this work by LT M. Rigo and the Spectral Information Technology Applications Center (SITAC), CAPT F. Garcia (Office of the Deputy Undersecretary of Defense for Science and Technology), and T. Cooley and R. Lockwood (Air Force Research Laboratory Space Vehicles Directorate). The suggestions of the anonymous reviewers were very much appreciated. Also the first author expresses sincere gratitude and appreciation for the guidance of Prof. David Landgrebe during and in the years following his graduate study.ISSN:0196-2892 Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type

Article

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Campus

RIT – Main Campus

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