IEEE Geoscience and Remote Sensing Magazine - June 2019 - 8
©ISTOCKPHOTO.COM/MARY WANDLER
Causes, models, and
strategies for mitigation
and robust exploitation
Spectral Variability of Remotely
Sensed Target Materials
JAMES THEILER, AMANDA ZIEMANN, STEFANIA MATTEOLI, AND MARCO DIANI
T
he central problem in hyperspectral remote sensing
is characterizing the material components of a scene
based on the spectral radiance observed in the image pixels. What makes this challenging is the fact that the spectral
response for a given material exhibits considerable variability from a variety of causes: intrinsic (depending on
the composition or morphology of the material), extrinsic
(depending on the size of an object or the concentration of
the material), or environmental (due to illumination, atmospheric distortion, and so on). In this article, we survey
many of the causes of spectral variability, describe spectral
models for this variability, and outline some signal processing and target detection strategies for analyzing hyperspectral data in a way that is more robust to this variability.
Digital Object Identifier 10.1109/MGRS.2019.2890997
Date of publication: 18 June 2019
8
0274-6638/19©2019IEEE
HYPERSPECTRAL IMAGING
Many remote sensing applications require locating a specific
target object or material within a scene, which may then be
further identified, characterized, or quantified. A geologist
might care about a particular mineral, a forester might want
to identify and monitor certain vegetation species, a publichealth agent might want to know about particular pollutants and dangerous toxins in the environment, a climate
scientist might want to locate sources of methane or carbon
dioxide, or a government might want information about
nuclear proliferation activities in another country.
With its exquisite discrimination ability, enabled by upward of hundreds of distinct spectral channels in every pixel,
hyperspectral imaging has the potential to solve all of these
problems. Underlying the many algorithms developed for
exploiting hyperspectral imagery is the notion that each material is unequivocally characterized by its unique spectral
signature [embodied by the spectral reflectance in the visible
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
JUNE 2019
http://www.ISTOCKPHOTO.COM/MARY
IEEE Geoscience and Remote Sensing Magazine - June 2019
Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2019
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