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  • 1
    Publication Date: 2019-07-13
    Description: A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: Technical Symposium East ''82; May 03, 1982 - May 07, 1982; Arlington, VA
    Format: text
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  • 2
    Publication Date: 2019-07-13
    Description: This paper presents a technique for converting spectral radiance to the more fundamental quantity of interest, spectral reflectance. A full implementation of the technique requires the availability of radiative transfer software. However, a set of tables (which allows an approximate derivation of reflectance) is included herein, and covers a representative range of environmental parameter values. An error analysis is performed which gives, for an uncertainty in each of the input parameters (solar zenith angle, visibility, sensor altitude, off-nadir viewing angle, background reflectance and surface elevation), the resulting error in derived reflectance. As a demonstration of the technique, several sets of spectral radiance data from the Imperial Valley, California, are presented as spectral reflectances.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: International Symposium on Remote Sensing of Environment; May 09, 1983 - May 13, 1983; Ann Arbor, MI
    Format: text
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