RETRIEVING BRDF OF DESERT USING TIME SERIES OF MODIS IMAGERY

RETRIEVING BRDF OF DESERT USING TIME SERIES OF MODIS IMAGERY

Haixia Huang, Bo Zhong, Qinhuo Liu, and Lin SunPresented by Bo [email protected]

Institute of Remote Sensing Applications, Chinese Academy of Sciences

IGRSS 2011, Vancouver , Canda

Outline

Background

Methodology

Preliminary results

Applicatoins

Conclusions

Background

BRDF is the key parameter for:Quantitative remote sensingErath radiation budgetMore

Desert is one of the main landcover typesStrongly reflecting the solar radiationMore

Problem

• There is no “good” BRDF product of desert

Methodology-flowchartMODIS 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

Methodology- site choosing

Location of the experimental site(MODIS imagery color

composite)

Cole view of the site(TM imagery color composite)


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.

8

（ a）Mar. 3, 2000 （ b） Feb. 3, 2010


AOD retrieval using DO method

40 60 80 1000

1

2

3

Aer

osol

opt

ical dep

th

Apparent radiance(w/m2/sr/mic)

Aerosol optical depth and radiance curveCorresponding path radiance and aerosol optical depth

52.87

0.43

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 0.2178

Original methodTime series of MODIS imagery

Identifying clear pixels

Reflectance of clear pixels

BRDF fitting

Reflectance of hazy pixels

AOD of hazy pixels

LUT

MODIS surface reflectance

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.

MODIS-B3: Staylor-Suttles coefficients

Preliminary results

Comparison with MODIS products

R2 much

higher RMSE is

lower

Applications I: inter-calibration of AVHRR using retrieve BRDF

Spectral matching of AVHRR and MODIS

AVHRR data simulation using the new method

Inter-calibration

Validation

Spectral matching

AVHRR 1 (0.645 μm)

AVHRR 2 (0.865 μm)

AVHRR 3 (1.6 μm)

ai 0.9885 1.0105 1.0004

Applications II: global desert BRDF retrieval

Mapping of the desert

BRDF and AOD retrieval simultaneously using

the new method

Preliminary validation

The chosen desert sites

The geolocations of the deserts

Desert Name

Lat（ °） Lon（ °） Altitude（ m）

Duration(yyyy.mm.d

)Taklimak

an39.0°N-40°N 84°E-85°E 1050 2009.10.1-

210.10.1

Rabal-Khali

18.8°N-19.8°N 45.5°E-46.5°E 700 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 2009.10.1-210.10.1

Taklimakan desert

Rabal-Khali desert

Lybia desert

Sahara desert

Conclusions

The new method is able to catch the BRDF

characterization of deserts

This method can be used for inter-calibration of

reflective bands of moderate satellite data like

AVHRR

This method is helpful for researches on earth

radiation budget

Thank you for your attention!

RETRIEVING BRDF OF DESERT USING TIME SERIES OF MODIS IMAGERY

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