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Liang APEIS Capacity Building Workshop on Integrated Environmental Monitoring of Asia-Pacific Region 20-21 September 2002, Beijing,, China Atmospheric Correction of Optical Remotely Sensed Imagery Shunlin Liang Department of Geography University of Maryland at College Park, USA
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Liang Outline Introduction MODIS atmospheric correction algorithms Other correction methods and examples Summary
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Liang
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Liang Atmospheric effects Gaseous Absorption Water vapor Ozone ( ) and others Particle Scattering Rayleigh (Molecular) Aerosol (large sizes)
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Liang Water vapor absorption
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Liang Water vapor
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Liang Water Vapor
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Liang Ozone
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Liang
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Liang CO2
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Liang
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Liang Total transmittance (mid-latitude summer, nadir viewing)
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Liang Rayleigh Scattering * Optical depth decreases quickly as wavelength * Very stable in both time and space
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Liang Aerosol scattering
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Liang
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Liang Outline Introduction MODIS atmospheric correction algorithms Other correction methods and examples Summary
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Liang 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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Liang Differential absorption Methods for estimating water vapor content Two-band ratio: Three-band ratio:
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Liang Differential absorption Methods for estimating water vapor content
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Liang Aerosol Climatology
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Liang Aerosol climatology
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Liang
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Liang Estimation of aerosol optical depth (dark object approach) Step 1: low surface reflectance at 2.2 um Step 2: surface reflectance at red and blue Step 3: aerosol properties from TOA radiances
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Liang Estimation of aerosol optical depth (dark object approach)
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Liang
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Liang Surface reflectance retrieval
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Liang Major limitations (dark-object approaches) Relies on empirical statistical relations works only over vegetated surfaces
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Liang Outline Introduction MODIS atmospheric correction algorithms Other correction methods and examples Summary
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Liang Other atmospheric correction methods 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
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Liang Other atmospheric correction methods 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
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Liang Other atmospheric correction methods 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,102:17173- 17186.
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Liang Atmospheric correction examples (Liang, et al., J. Geophys. Res., 1997)
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Liang Cluster matching method 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
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Liang Are bands 4,5 &7 hazy or there shadows? Histogram matching Clustering analysis Determining clear and hazy regions Determining reflectance of clear regions Mean reflectance matching of each cluster in both clear & hazy regions Look-up tables searching for aerosol optical depth Spatial smoothing of the estimated aerosol optical depth Reflectance retrieval by considering adjacency effects YES NO Are near-IR bands hazy or there shadows? Histogram matching Clustering analysis Determining clear and hazy regions Determining reflectance of clear regions Mean reflectance matching of each cluster in both clear & hazy regions Look-up tables searching for aerosol optical depth Spatial smoothing of the estimated aerosol optical depth Reflectance retrieval by considering adjacency effects YES NO
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Liang
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Liang ETM+ atmospheric correction: Case1
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Liang ETM+ atmospheric correction: case1
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Liang ETM+ atmospheric correction: Case 2
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Liang ETM+ atmospheric correction: case 2
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Liang ETM+ atmospheric correction: case 3
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Liang
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Liang AVIRIS ( Airborne Visible InfraRed Imaging Spectrometer )
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Liang AVIRIS Imagery of Parana, Brazil acquired on August 23, 1995 Band 18 (549nm)Band 26 (627nm) Band 34 (673nm)
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Liang 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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Liang Sea-viewing Wide Field-of-view Sensor (SeaWiFS)
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Liang SeaWiFS imagery of Washington DC area, Nov. 6, 2000
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Liang
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Liang MODIS (Moderate Resolution Imaging Spectroradiometer) 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.
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Liang MODIS imagery (northeastern coast, China May 7, 2000)
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Liang MODIS imagery of China northeastern coast, May 7, 2000
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Liang
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Liang Summary 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)
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Liang References 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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Liang Thank you !
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