i Detection of Smoke and Dust Aerosols Using Multi-sensor Satellite ...

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It is worth mentioning that the difference (or uncertainty) varies with the coverage of selected area. The differences are relative small at the homogenous or semi-homogenous area, and large at the non-homogenous areas. Based on this analysis, it is reasonable to conclude that the impacts on most of science products caused by spatial mis-registration are concentrated in the non-homogenous areas or mixed areas. Table 7.3: The difference between dust aerosol detection results with and without spatial correction No correction With correction Dust Cloud Others Dust Cloud Others Classification 15,622 10,697 3,681 15,455 10,721 3,824 r 2 0.9825 0.5636 0.9700 0.9831 0.5811 0.9706 NO correction With correction Dust Cloud Other Dust 15,270 0 352 Cloud 0 10,475 222 Other 185 246 3,250 Pixel number along-track 50 100 150 50 100 150 200 Pixel number along-scan Figure 7.9: The MODIS true color image of selected case with dust plume. 117
Difference NDDI with spatial correction NDDI 20 40 60 80 100 120 140 kcart- gn lo ar eb mu nl e ix P 50 100 150 200 50 100 150 200 50 100 150 200 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 Pixel number along-scan Figure 7.10: NDDI value with and without correction, and their difference. Classification Calssification with spatial correction Difference 118 20 40 60 80 100 120 140 kcart- gn lo ar eb mu nl exi P 50 100 150 200 50 100 150 200 50 100 150 200 pixel number along-scan Figure 7.11: Dust detection product with and without correction, and their difference.
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Detection of Smoke and Dust Aerosol
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DEDICATION This is dedicated to my
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TABLE OF CONTENTS Page LIST OF TABL
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LIST OF TABLES Table Page Table 1.1
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Figure 6.2 The UVAI images and the
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VFM Vertical Feature Mask VIS Visib
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are validated not only visually wit
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1.1 Importance of Studying Smoke an
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1.3 Objectives and Scopes The main
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originalities, and discussions of f
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1.6 Principal Results The principle
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CHAPTER 2 REVIEW OF APPROACHES FOR
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cooperatively: the reflectance at 0
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more information about dust charact
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CHAPTER 3 SMOKE AEROSOL DETECTION W
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with a two-side scan mirror which r
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3.1.2 MODIS data The 55 0 scan angl
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Sun Satellite Figure 3.2: Basic rad
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1 0 /2 b ( 0 0, 0; , ) k1 e
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3.2.3 Training data collection Surf
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Reflectance Reflectance Response cu
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Figure 3.6: The normalized ratio of
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all pixels over both land and ocean
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NDDI 1 0.8 0.6 0.4 0.2 0 -0.2 Figur
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MODIS L1B measurements Pixels over
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is clear that most of smoke plumes
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a b c b Figure 3.10: Smoke images o
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3.4.2 California 2007 fire The 2007
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The multi-spectral approach is test
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4.1 Physical Principle of Dust Aero
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Aqua 2006 102-04/12 04:15 Terra 200
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The dust has a high reflectivity at
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0.55 0.5 0.45 0.4 0.35 0.3 0.25 0.2
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7 a Dust pixel 0.5 b 6 Cloud pixel
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4.3 Results Three dust events occur
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c c Figure 4.6: Dust storm over TAK
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4.4 Chapter Summary In this chapter
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operated in the A-train orbit with
Page 79 and 80: 5.1.2 CALIPSO measurements and VFM
Page 81 and 82: Altitude (km) 20 15 10 5 UTC: 2006-
Page 83 and 84: After spatial registration, the ove
Page 85 and 86: Figure 5.4(a) The MODIS true color
Page 87 and 88: Altitude (km) BTD (K) 20 15 10 15 4
Page 89 and 90: in the same A-train orbit with simi
Page 91 and 92: Aqua spacecrafts are operated in th
Page 93 and 94: the Fig. 6.1a. For easy comparison,
Page 95 and 96: esolutions, the number of smoke pix
Page 97 and 98: 6.1.4 Validation of dust monitoring
Page 99 and 100: Figure 6.3 Validation of dust image
Page 101 and 102: eflectance in red band. Therefore,
Page 103 and 104: Altitude (km) 20 15 10 5 UTC: 2006-
Page 105 and 106: image at the same location. The rea
Page 107 and 108: accuracy could be increased further
Page 109 and 110: FPAs and cold FPAs (because of diff
Page 111 and 112: development of future remote sensin
Page 113 and 114: Figure 7.3: SRCA spatial mode retic
Page 115 and 116: 7.1.3.2 Date Source MODIS L1B data
Page 117 and 118: characterization. Only the measurem
Page 119 and 120: these bands, including reflective s
Page 121 and 122: different spectral bands are slight
Page 123 and 124: SZA (Degree) SZA (Degree) 65 60 55
Page 125 and 126: 7.2.1.2 Real Impact on L1B Measurem
Page 127 and 128: 7.2.2.1 Theoretical impact analysis
Page 129: spatial characterization, the bigge
Page 133 and 134: 8.1 Conclusions CHAPTER 8 CONCLUSIO
Page 135 and 136: Based on the detection results, the
Page 137 and 138: 3) Validating aerosol detection qua
Page 139 and 140: REFERENCES Ackerman, S. A., 1989, U
Page 141 and 142: imagery, Atmospheric Environment, v
Page 143 and 144: Salomonson, V. V., Privette, J. L.,
Page 145 and 146: Martinez, A., and Gros, G., 2007-10
Page 147 and 148: Wang W., Qu, J. J., Liu, Y., Hao, X
Page 149: CURRICULUM VITAE Yong Xie is a Ph.D
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