Paper Info
Title
Full Spectrum Modeling Of At-Sensor Spectral Radiance Variability Due To Surface Variability
Abstract
In support of hyperspectral sensor system design and parameter tradeoff investigations, an analytical end-to-end remote sensing system performance forecasting model hits been extended to cover the visible and near infrared through longwave infrared portion of the optical spectrum (0.4 to 14 mum). The model takes statistical descriptions of surface spectral reflectances 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.This paper presents the theory for analytically transforming 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's predictions with measurements from an airborne hyperspectral sensor are presented. An example is included to show the model's utility in understanding the magnitude of full spectrum radiance Components.
Year
DOI
Venue
2004
10.1109/IGARSS.2004.1368704
IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET
Keywords
Field
DocType
speetral imaging, full spectrum modeling
Spectral imaging,Image sensor,Computer science,Remote sensing,Near-infrared spectroscopy,Optics,Image processing,Hyperspectral imaging,Longwave,Infrared,Radiance
Conference
ISSN
Citations 
PageRank 
2153-6996
0
0.34
References 
Authors
4
2
Name
Order
Citations
PageRank
John P. Kerekes119435.38
Jerrold E. Baum2355.56