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

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oth figures stands for the MODIS band number. The vertical axes is the responses of different scene types in each band; the reflectance for RSBs in the left side and the BT for TEBs in the right side. 3.2.5 Band selection Generally, the Normalized Difference Vegetation Index (NDDI) (Rouse et al., 1973; Huete et al., 1994) is an ideal index for vegetation classification. However, the conclusion in chapter 3.2.2 illustrates that the short wavelength band is sensitive to smoke and at least one short wavelength band is selected in each test. Consequently, a pseudo-NDVI, the normalized ratio of band 2 and band 3 (469 nm), is introduced to discriminate vegetation and smoke pixels. The reason is that smoke has high reflectivity in band 3 than that in band 1 due to Rayleigh scattering while the vegetation appears dark either in band 3. The NDDI, the normalized ratio of band 7 (2130 nm) and band 3, is an index developed for dust detection (Qu et al., 2006). It is also suitable for soil classification (namely brightly reflecting surface). Normally, the NDDI value is positive for soil or dust but negative for smoke. The inverse value of NDDI is applied for the differentiation smoke from soil surface according to the spectral signature difference. 27
Reflectance Reflectance Response curve of smoke and cloud pixels by statistical analysis 1 Smoke pixel over land 320 Smoke pixel over ocean 0.9 Cloud pixel 310 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.3 0.25 0.2 0.15 0 B8 B3 B4 B1 B2 B7 B20 B29 B31 B32 220 412 469 555 645 858 2130nm; 3.75 8.55 11.03 12.02μm 0.1 Figure 3.4: Response curves of smoke and cloud pixels. Response curve of smoke and land pixels by statistical analysis 0.4 325 Smoke pixel Bright land pixel 320 0.35 Dark land pixel 0.05 275 B8 B3 B4 B1 B2 B7 B20 B29 B31 B32 412 469 MODIS 555 band 645 858 2130nm; 3.75 8.55 11.03 12.02μm Figure 3.5: Response curves of smoke and land pixels. 28 300 290 280 270 260 250 240 230 315 310 305 300 295 290 285 280 BT (K) BT (K)
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: 3.2.3 Training data collection Surf
Page 43 and 44: Figure 3.6: The normalized ratio of
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-
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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
Page 113 and 114:
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
Page 129 and 130:
spatial characterization, the bigge
Page 131 and 132:
Difference NDDI with spatial correc
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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
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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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