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

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idges to determine the modulation transfer function for the Hyperion sensor. Nevertheless, these kinds of small ground targets are not appropriate for the MODIS spatial characterization in view of its moderate spatial resolution. Consequently, a desert area with a series of regularly arranged dark targets is chosen in this study for the MODIS on-orbit spatial characterization. Compared to the approach of using its on-board calibrator, this approach can provide more frequent characterization of the MODIS BBR as it requires no light sources. The deficiency is that it cannot provide spatial characterization for all bands, only for some RSBs (bands 1-11 and 17-19) and TEBs (bands 20, 22, 23, 29, 31, and 32). 7.1.3.1 Site for Spatial Characterization Using Ground Measurements The ground targets selected for sensor spatial characterization must have high contrast features. Therefore, different types of ground targets could be used for measuring the BBR shift, such as a dark target, water body, coastline, snow coverage, and island. The site selected for the MODIS on-orbit spatial characterization is located at the Sahara desert in Libya, Africa. The latitude of this site is from 26.5 0 North to 28.0 0 North and the longitude is from 21.5 0 East to 22.5 0 East. Within this area, more than one hundred dark targets are arranged regularly in several rows. Each dark target has a circular shape with a diameter of approximately 1 km. The RGB image of this site from MODIS remote sensing measurements is shown in Fig. 7.4(a). The other three images, Figs. 7.4(b), (c), and (d), are taken from Google images with different spatial enlargements. 101
7.1.3.2 Date Source MODIS L1B data at three spatial resolutions are used to calculate the spatial deviation: 250 m for band 2 (40 detectors / band), 500 m for band 3-7 (20 detectors / band), and 1 km for other bands (10 detectors / band). The L1B data used is the version 5 issued by NASA. Each MODIS L1B data set (referred to as a “granule”) collects consecutive measurements within five minutes, typically 203 scans. In each scan, 1,354 data frames are recorded for each detector. For 500 m resolution band, 2 sub-frames or samples per frame (1 km) are recorded for its 20 detectors, and 4 sub-frames for each 250 m band and its 40 detectors (Xiong et al., 2003). Thus, each granule typically contains 2030 rows (along-track) × 1354 columns (along-scan) for 1 km resolution bands, 8120 rows × 5416 columns for 250 m resolution bands, and 4060 rows ×2708 columns for 500 m resolution bands. 102
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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
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: Figure 7.3: SRCA spatial mode retic
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 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
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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