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

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The BT of the 11 µm band (band 31) and the BTD between the 11 µm band and the 3.7 µm band (band 20) (Ackerman et al., 2002) are used to separate smoke aerosol from cloud, as well as the reflectance at the 1.38 µm channel, a spectrum window of water vapor useful for detecting high cirrus cloud (Gao et al., 1993; Gao et al., 2002). The normalized ratio of two blue bands, (R3 - R8) / (R3 + R8), and the single reflectance of band 8 (412 nm) are proposed to filter out the noise pixel (mainly water pixels and coastline pixels). Band 8, the shortest wavelength band within MODIS, is strongly sensitive to the smoke aerosol because of Rayleigh scattering. The average geometrical radii of smoke particle are in the range of 0.01 - 0.05 µm, largely satisfying the Rayleigh scattering limit (Wong and Li, 2002; Remer et al., 2002). Rayleigh scattering is wavelength dependence. Its intensity is inversely proportional to the fourth power of the wavelength. As a result, this ratio of two blue bands is very sensitive to aerosol. Two examples with smoke plumes are shown in Fig. 3.6. The normalized ratio of two blue bands for smoke plumes in both images is relative higher than vegetated and water areas, and the ratio values increases with the plume intensity. For the convenient expression in this dissertation, the single reflectance of certain band is expressed with R (reflectance) plus band number. The BT of certain band is denoted with BT plus CW. The normalized ratio of two bands has the formula like Ratio (Ra, Rb) = (Ra - Rb) / (Ra + Rb), where a and b are band number. The BTD between two bands is given in BTD (CWa, CWb) = BTCWa –BTCWb, where CWa and CWb are CW of band a and band b. 29
Figure 3.6: The normalized ratio of band 3 and band 8 used for identifying smoke plume and corresponding RGB images. The upper row is the case on May 10, 2007, and the bottom row is the case on May 24, 2001. 30
Page 1 and 2: Detection of Smoke and Dust Aerosol
Page 3 and 4: DEDICATION This is dedicated to my
Page 5 and 6: TABLE OF CONTENTS Page LIST OF TABL
Page 7 and 8: LIST OF TABLES Table Page Table 1.1
Page 9 and 10: Figure 6.2 The UVAI images and the
Page 11 and 12: VFM Vertical Feature Mask VIS Visib
Page 13 and 14: are validated not only visually wit
Page 15 and 16: 1.1 Importance of Studying Smoke an
Page 17 and 18: 1.3 Objectives and Scopes The main
Page 19 and 20: originalities, and discussions of f
Page 21 and 22: 1.6 Principal Results The principle
Page 23 and 24: CHAPTER 2 REVIEW OF APPROACHES FOR
Page 25 and 26: cooperatively: the reflectance at 0
Page 27 and 28: more information about dust charact
Page 29 and 30: CHAPTER 3 SMOKE AEROSOL DETECTION W
Page 31 and 32: with a two-side scan mirror which r
Page 33 and 34: 3.1.2 MODIS data The 55 0 scan angl
Page 35 and 36: Sun Satellite Figure 3.2: Basic rad
Page 37 and 38: 1 0 /2 b ( 0 0, 0; , ) k1 e
Page 39 and 40: 3.2.3 Training data collection Surf
Page 41: Reflectance Reflectance Response cu
Page 45 and 46: all pixels over both land and ocean
Page 47 and 48: NDDI 1 0.8 0.6 0.4 0.2 0 -0.2 Figur
Page 49 and 50: MODIS L1B measurements Pixels over
Page 51 and 52: is clear that most of smoke plumes
Page 53 and 54: a b c b Figure 3.10: Smoke images o
Page 55: 3.4.2 California 2007 fire The 2007
Page 58 and 59: The multi-spectral approach is test
Page 60 and 61: 4.1 Physical Principle of Dust Aero
Page 62 and 63: Aqua 2006 102-04/12 04:15 Terra 200
Page 64 and 65: The dust has a high reflectivity at
Page 66 and 67: 0.55 0.5 0.45 0.4 0.35 0.3 0.25 0.2
Page 68 and 69: 7 a Dust pixel 0.5 b 6 Cloud pixel
Page 70 and 71: 4.3 Results Three dust events occur
Page 72 and 73: c c Figure 4.6: Dust storm over TAK
Page 74: 4.4 Chapter Summary In this chapter
Page 77 and 78: 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,
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Altitude (km) 20 15 10 5 UTC: 2006-
Page 105 and 106:
image at the same location. The rea
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accuracy could be increased further
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FPAs and cold FPAs (because of diff
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development of future remote sensin
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Figure 7.3: SRCA spatial mode retic
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7.1.3.2 Date Source MODIS L1B data
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characterization. Only the measurem
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these bands, including reflective s
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different spectral bands are slight
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SZA (Degree) SZA (Degree) 65 60 55
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7.2.1.2 Real Impact on L1B Measurem
Page 127 and 128:
7.2.2.1 Theoretical impact analysis
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spatial characterization, the bigge
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Difference NDDI with spatial correc
Page 133 and 134:
8.1 Conclusions CHAPTER 8 CONCLUSIO
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Based on the detection results, the
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3) Validating aerosol detection qua
Page 139 and 140:
REFERENCES Ackerman, S. A., 1989, U
Page 141 and 142:
imagery, Atmospheric Environment, v
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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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