IEEE Geoscience and Remote Sensing Magazine - June 2019 - 31

Atmospheric
Compensation of
Hyperspectral Data
IMAGE LICENSED BY INGRAM PUBLISHING

An overview and review of in-scene and physics-based approaches

EMMETT J. IENTILUCCI
AND STEVEN ADLER-GOLDEN

I

n this tutorial overview, we examine atmospheric compensation of hyperspectral data in the visible and nearinfrared (VNIR)-short-wave infrared (SWIR) region. The
background is discussed, including the motivation for and
a brief history of image compensation. Atmospheric characteristics are presented to highlight important optical effects that must be mitigated (i.e., atmospheric absorption
and scattering). A full radiative transfer (RT) expression
with simplifications is presented, resulting in formulations
that are solved in terms of reflectance. Commonly used
methods to retrieve reflectance are presented, including
four scene-based algorithms,
◗ dark-object subtraction (DOS)
◗ internal average reflectance (IAR)
Digital Object Identifier 10.1109/MGRS.2019.2904706
Date of publication: 18 June 2019

JUNE 2019

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

◗ empirical line method (ELM)
◗ quick atmospheric correction (QUAC),

and six physics-based algorithms,
◗ atmospheric removal (ATREM)
◗ the algorithm formerly known as ATREM (TAFKAA)
◗ high-accuracy atmospheric correction for hyperspectral
data (HATCH)
◗ atmospheric correction now (ACORN)
◗ fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH)
◗ atmospheric correction (ATCOR).
Results are summarized from past reviews on the subject, and new analyses are presented using the Rochester Institute of Technology's (RIT's) SpecTIR Hyperspectral Airborne Experiment (SHARE 2012) and self-test programs.
REMOTE SENSING
Remote sensing, for all practical purposes, is the field of
study associated with extracting information about an
object without coming into physical contact with it. This
definition can include many disciplines, such as medical
0274-6638/19©2019IEEE

31



IEEE Geoscience and Remote Sensing Magazine - June 2019

Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - June 2019

Contents
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