Haixia Huang Bo Zhong Qinhuo Liu and Lin Sun Presented by Bo Zhong bzhong1gmailcom Institute of Remote Sensing Applications Chinese Academy of Sciences IGRSS 2011 Vancouver ID: 239969
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Slide1
RETRIEVING BRDF OF DESERT USING TIME SERIES OF MODIS IMAGERY
Haixia Huang, Bo Zhong, Qinhuo Liu, and Lin SunPresented by Bo Zhongbzhong1@gmail.comInstitute of Remote Sensing Applications, Chinese Academy of Sciences
IGRSS 2011, Vancouver , CandaSlide2
Outline
BackgroundMethodologyPreliminary resultsApplicatoinsConclusions Slide3
Background
BRDF is the key parameter for:Quantitative remote sensingErath radiation budgetMoreDesert is one of the main landcover typesStrongly reflecting the solar radiation
More Slide4
Problem There is no “good” BRDF product of desert Slide5
Methodology-flowchart
MODIS imagery
Converting DN to TOA reflectance
Identifying the
“
clearest
”
of each observations
Retrieving reflectance of
“
clearest
”
observations
Fitting to Staylor-Suttles BRDF model
Lookup Tables
BRDF of desert Slide6
Methodology- site choosing
Location of the experimental site
(MODIS imagery color composite)
Cole view of the site
(TM imagery color composite)Slide7
Methodology- site choosing
It is stable, so it can be seen as an invariant object;There are a lot of lakes within the calibration site, which are seldom polluted, so the lowest AOD of calibration site can be determined by Dark Object (DO) method using Landsat TM and ETM+ data.Slide8
8
（a
）Mar. 3, 2000 （
b）Feb. 3, 2010
Methodology- site choosingSlide9
AOD retrieval using DO method
ETM+ imaging date
Aerosol optical depth
TM imaging date
Aerosol optical depth
2000.03.03
0.1543
2006.09.20
0
2000.04.29
0
2006.10.31
0.0440
2001.10.16
0.0218
2007.05.18
0.1536
2001.11.17
0
2007.06.03
0
2002.01.04
0.0657
2009.06.17
0.4279
2002.03.18
0.2801
2009.08.11
0.05444
2002.05.28
0.3274
2009.08.27
0.0043
2002.09.17
0.1058
2009.09.28
0.0096
2002.11.04
0.3633
2010.02.03
0.07676
2002.11.13
0.0286
2010.06.04
0.254
2002.12.15
0.1195
2010.07.29
0.3552
2003.03.28
0.4273
2010.08.14
0
2010.08.23
0.2178Slide10
Original method
Time series of MODIS imagery
Identifying clear pixels
Reflectance of clear pixels
BRDF fitting
Reflectance of hazy pixels
AOD of hazy pixels
LUT
MODIS
surface reflectanceSlide11
Modifications for the original method
AOD determination for the “clearest” days;Shrinking the use of the algorithm from globe to the desert calibration site, which is stable;Identifying the “clearest” observations for every 10 degrees in view zenith angles from 0-50 degree (0-10, 11-20, 21-30, 31-40, and 41-50);Using
Staylor-Suttles BRDF model instead of Walthall BRDF.Slide12
MODIS-B3:
Staylor-Suttles
coefficients
Preliminary resultsSlide13
MODIS-B1:
Staylor-Suttles coefficientsSlide14
MODIS-B2:
Staylor-Suttles
coefficientsSlide15
Comparison with MODIS productsSlide16
R
2 much higher
RMSE is lowerSlide17
Applications I: inter-calibration of AVHRR using retrieve BRDF
Spectral matching of AVHRR and MODISAVHRR data simulation using the new methodInter-calibrationValidationSlide18
Spectral matching
AVHRR 1 (0.645 μ
m)
AVHRR 2 (0.865
μ
m)
AVHRR 3 (1.6
μ
m)
a
i
0.9885
1.0105
1.0004Slide19Slide20
Applications II: global desert BRDF retrieval
Mapping of the desertBRDF and AOD retrieval simultaneously using the new methodPreliminary validationSlide21
The chosen desert sites Slide22
The geolocations of the deserts
Desert
Name
Lat
（°
）
Lon
（°
）
Altitude
（
m
）
Duration
(
yyyy.mm.d
)
Taklimakan
39.0°N-40°N
84°E-85°E
10502009.10.1-210.10.1
Rabal-Khali
18.8°
N-19.8°
N
45.5
°E-46.5°
E700
2009.10.1-210.10.1
Lybia
24
°
N-25
°
N
12
°
E-13
°
E
740
2009.10.1-210.10.1
Sahara
19.5
°
N-20.5
°
N
8
°
W-9
°
W
260
2009.10.1-210.10.1Slide23
Taklimakan desert
Slide24
Rabal
-Khali desert
Slide25
Lybia
desert
Slide26
Sahara
desert
Slide27
Conclusions
The new method is able to catch the BRDF characterization of desertsThis method can be used for inter-calibration of reflective bands of moderate satellite data like AVHRRThis method is helpful for researches on earth radiation budgetSlide28
Thank you for your attention!