The field of optical remote sensing for the analysis of Earth’s resources has grown tremendously over the past 20 years. With increasing societal concern over such problems as ozone layer depletion and global warming, political support is likely to continue that growth. NASA has recently begun a program that will use state of the art sensor technology and processing algorithms to gain ever more detailed data about our Earth. To better understand the remote sensing process, research has begun on modeling the process as a system and investigating the interrelationships of system components. This paper presents a system model for the remote sensing process and some results that yield insight into its understanding. Key results include interrelationships between the atmosphere, sensor noise, sensor view angle, and scattered path radiance and their influence on classification accuracy of the ground cover type. Also included are results indicating the trade-offs in ground cell size and surface spatial correlation and their effect on classification accuracy.

Publication Date



©1991 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 would like to thank Larry L. Biehl of LARS for his assistance in obtaining the reflectance and image data used in these investigations. In addition, the comments and the suggestions of the anonymous reviewers were greatly appreciated.ISSN:0018-9472 Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2014.

Document Type


Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


RIT – Main Campus