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.
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
IEEE Transactions on Systems, Man and Cybernetics 21N1 (1991) 125-133
RIT – Main Campus