Transcript No Slide Title

APEIS Capacity Building Workshop on Integrated
Environmental Monitoring of Asia-Pacific Region
20-21 September 2002, Beijing,, China
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Atmospheric Correction of Optical
Remotely Sensed Imagery
Shunlin Liang
Department of Geography
University of Maryland at College Park, USA
Outline
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Introduction
MODIS atmospheric correction algorithms
Other correction methods and examples
Summary
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Atmospheric effects
 Gaseous Absorption
Water vapor
Ozone (O3)
 CO2 and others
 Particle Scattering
Rayleigh (Molecular)
Aerosol (large sizes)
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Water vapor absorption
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Water vapor
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Water Vapor
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Ozone
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Ozone
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CO2
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CO2
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Total transmittance
(mid-latitude summer, nadir viewing)
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Rayleigh Scattering
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* Optical depth decreases quickly as wavelength
* Very stable in both time and space
Aerosol scattering
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Outline
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Introduction
MODIS atmospheric correction algorithms
Other correction methods and examples
Summary
MODIS atmospheric correction
Water absorption estimation and correction
(MOD05) – Dr. Gao Bo-Cai
Aerosol estimation (MOD04) – Dr. Yoram
Kaufman
Surface reflectance retrieval (MOD-09) –
Dr. Eric Vermote
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Differential absorption Methods
for estimating water vapor content
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Two-band ratio:
Three-band ratio:
Differential absorption Methods
for estimating water vapor content
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Aerosol Climatology
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Aerosol climatology
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Estimation of aerosol optical depth
(dark object approach)
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Step 1: low surface reflectance at 2.2 um
Step 2: surface reflectance at red and blue
Step 3: aerosol properties from TOA radiances
Estimation of aerosol optical depth
(dark object approach)
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Estimation of aerosol optical depth
(dark object approach)
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Surface reflectance retrieval
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Major limitations
(dark-object approaches)
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Relies on empirical statistical relations
works only over vegetated surfaces
Outline
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Introduction
MODIS atmospheric correction algorithms
Other correction methods and examples
Summary
Other atmospheric correction methods
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 Invariant object regression method for temporal evaluation (Hall, et al.,
1991):
 find a set of pixels whose reflectance values do not change significantly
under different solar and atmospheric conditions
 simple and easy implementation
 relative correction
 uniform aerosol distribution
Other atmospheric correction methods
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Histogram matching technique (ATCOR2
in ERDAS; Richter, 1996):
identify hazy regions using the Tasseled Cap
transformation
match histograms of both clear and hazy
regions.
Tasseled Cap transformation does not always work
approximate correction, not well for heterogeneous
aerosols
uniform landscape
Other atmospheric correction methods
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 Dark-object algorithms for TM Imagery
Liang S., H. Fallah-Adl, S. Kalluri, J. JaJa, Y. J.
Kaufman, and J. R. G. Townshend, (1997), An
Operational Atmospheric Correction Algorithm
for Landsat Thematic Mapper Imagery over the
Land, J. Geophys. Res. - Atmosphere,102:1717317186.
Atmospheric correction examples (Liang, et al., J. Geophys. Res., 1997)
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Cluster matching method
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Liang, S., H. Fang, M. Chen, (2001), Atmospheric
Correction of Landsat ETM+ Land Surface
Imagery: I. Methods, IEEE Transactions on
Geosciences and Remote Sensing 39:2490-2498.
Liang, S., H. Fang, J. Morisette, M. Chen, C.
Walthall, C. Daughtry, and C. Shuey, (2002),
Atmospheric Correction of Landsat ETM+ Land
Surface Imagery: II. Validation and Applications,
IEEE Transactions on Geosciences and Remote
Sensing, in press
Are near-IR bands hazy
YES
YES
Are bands 4,5 &7 hazy
there
shadows?
oror
there
shadows?
NO
NO
Determining
Determining
clearclear
and
and regions
hazy regions
hazy
Histogram
Histogram
matching
matching
Clustering
analysis
Clustering
analysis
Determining
reflectance
Determining reflectance
of clear
regions
of clear regions
Mean
reflectance
matching
of ineach
Mean
reflectance
matching
of each cluster
both
clear
& hazy
cluster
inregions
both clear & hazy regions
Look-up
tables
searching
for
Look-up
tables
searching
for aerosol
optical
depth
aerosol
optical depth
Spatial
smoothing
of the of the
estimated
Spatial
smoothing
aerosol
optical
depth
estimated aerosol optical depth
Reflectance
retrieval
by considering
Reflectance
retrieval
by
adjacency effects
considering adjacency effects
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ETM+ atmospheric correction: Case1
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ETM+ atmospheric correction: case1
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ETM+ atmospheric correction: Case 2
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ETM+ atmospheric correction: case 2
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ETM+ atmospheric correction: case 3
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ETM+ atmospheric correction: case 3
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AVIRIS
( Airborne Visible InfraRed Imaging Spectrometer)
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AVIRIS Imagery of Parana, Brazil acquired on August 23, 1995
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Band 18 (549nm)
Band 26 (627nm)
Band 34 (673nm)
Atmospheric correction of AVIRIS Imagery
Composite imagery of Parana, Brazil, August 23, 1995
Bands 26 (627nm), 34(673nm) and 46 (788nm)
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Sea-viewing Wide Field-of-view Sensor
(SeaWiFS)
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SeaWiFS imagery of Washington DC
area, Nov. 6, 2000
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SeaWiFS imagery of Washington
DC area, Nov. 6, 2000
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MODIS
(Moderate Resolution Imaging Spectroradiometer)
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MODIS is the key instrument aboard the Terra and Aqua satellites.
Terra/Aqua MODIS is viewing the entire Earth's surface every 1 to 2
days, acquiring data in 36 spectral bands.
MODIS imagery (northeastern coast,
China May 7, 2000)
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MODIS imagery of China northeastern
coast, May 7, 2000
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MODIS imagery of China northeastern
coast, May 7, 2000
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Summary
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Atmospheric correction is very critical in
monitoring land surfaces, particularly for
regions with frequently cloudy and hazy
conditions
There exist many different algorithms, but
further developments are needed for global
applications (inter-comparision, calibration
and validation)
References
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Kaufman, Y, 1989. The Atmospheric Effect
on Remote Sensing and Its Correction, in
Theory and Applications of Optical Remote
Sensing, G. Asrar (Ed.) John Wiley & Sons
Liang, S. Quantitative Remote Sensing of
Land Surfaces, John Wiley & Sons
Ch2: atmospheric radiative transfer modeling
Ch6: atmospheric correction methods
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Thank you !