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

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0.7 a NDVI value for smoke and dark land pixel Smoke pixel 0.5 b 0.6 Dark land pixel 0.45 NDVI BT11 0.5 0.4 0.3 0.2 0.1 0 -0.1 0.1 320 0.15 0.2 0.25 0.3 0.35 0.4 R8 BT11 value for smoke pixel over land and cloud pixel 0.45 Smoke pixel over land Cloud pixel 300 c d 280 260 240 220 200 0 10 20 30 40 50 BT3.7 - BT12 60 70 80 BTD (3.7, 12) for value smoke pixel over land and cloud pixel 80 70 Smoke pixel over land Cloud pixel e f BT3.7 - BT12 60 50 40 30 20 10 0 200 220 240 260 280 300 320 BT11 R8 BT11 33 0.4 0.35 0.3 0.25 0.2 0.15 R8 value for smoke and dark land pixels Smoke pixel Dark land pixel 0.1 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 NDVI BT11 value for smoke pixel over ocean and cloud pixel 300 Smoke pixel over ocean 290 Cloud pixel 280 270 260 250 240 230 220 210 200 0 10 20 30 40 50 60 70 80 BT3.7 - BT12 BTD (3.7, 12) value for smoke pixel over ocean and cloud pixel 80 Smoke pixel over ocean 70 Cloud pixel BT3.7 - BT12 60 50 40 30 20 10 0 210 220 230 240 250 260 270 280 290 300 BT11
NDDI 1 0.8 0.6 0.4 0.2 0 -0.2 Figure 3.7: Statistical analyses of training data for deciding the threshold. Table 3.2: The threshold tests and thresholds used for classification of four surface types and sensitivity analysis based on the selected cases in Georgia area during last five years. Class type Threshold test Value Error (Land) Error (Ocean) Vegetation (B2-B3) / (B2+B3) 0.30 0.045% N.A. 3 Soil (B3-B7) / (B3+B7) 0.10 3.047% N.A. 3 Cloud Water & Noise B26 & BTD (3.7, 12) & BT11 (B3-B8) / (B8+B3) & B8 Smoke pixel Bright land pixel -0.4 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 R8 (B3 - B8) / (B3 + B8) value for smoke and dark land pixels 0.15 Smoke pixel Dark land pixel 0.1 g h (R3 - R8) / (R3 + R8) 0.05 0 -0.05 -0.1 -0.15 -0.2 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 R8 34 0.03 15(9)K 1 285K 0.15 0.17 0.007% 1.745% 0.212% 0.007% 0.000% 0.084% 17.937% 0.683% 18.665% 1.453%
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 and 42: Reflectance Reflectance Response cu
Page 43 and 44: Figure 3.6: The normalized ratio of
Page 45: all pixels over both land and ocean
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,
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
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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 and 130:
spatial characterization, the bigge
Page 131 and 132:
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
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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