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

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Total 4.656% 2 35 34.577% 2 1 The threshold of BTD (3.7, 12) is 15 K for pixels over land and 9 K for pixels over ocean. 2 The total errors of both over land and over ocean are not equal to the summation of errors from each test because the overlap exists among tests. 3 The pseudo-NDVI and NDDI is only applied over land. 3.3.2 Flowchart Fig. 3.8 is the flowchart of smoke detection algorithm. The whole swath of L1B measurements is input and divided into two branches with land/sea mask product stored in L1A file: smoke over land and smoke over ocean. In land branch, the process is comprised with four tests, orderly for classifying vegetation, soil, cloud, and noise (including water). The first test employs a pseudo-NDVI to examine vegetated pixel. The NDDI is applied in the second test for differentiating smoke from bright surface. In the third test, the BT11 and BTD (3.7, 11) are used to discriminate smoke from cloud, as well as the reflectance at the 1.38μm band. The goal of last module is to filter out the noise pixels (mainly water pixels) with the normalized Ratio (R3, R8) and single of reflectance of band 8. In ocean branch, the process is relatively easy, which is comprised of two steps only. At the end of process, an additional test named “noise-elimination test” is executed to further filter noise pixels. In view of the smoke continuity, although a pixel is identified as smoke pixel but it is not close to other smoke pixels, this pixel will be considered as noise pixels and deleted from smoke images.
MODIS L1B measurements Pixels over land (R2-R3)/(R3+R2)≤0.30 Y (R3-R7)/(R3+R7)≥0.10 Y Pixels of smoke or cloud Y R26≤0.03 & BT3.7-BT11≤15K & BT11≥285K Y Y Smoke & noise Y R8≥0.17 & (R8-R3)/(R8+R3)≤0.15 Y Discrete pixel? N Y N N N Vegetation pixels Bare soil pixels Cloud pixels N Figure 3.8: Flowchart of the multi-threshold method for smoke detection. 36 Smoke pixels N Noise pixels Land/sea mask product Pixels over ocean R26≤0.03 & BT3.7-BT11≤9K & BT11≥285K
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 and 46: all pixels over both land and ocean
Page 47: NDDI 1 0.8 0.6 0.4 0.2 0 -0.2 Figur
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
Page 111 and 112:
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
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
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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
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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