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Generation of spatially and temporally consistent pollution data over urban areas via unified remote sensing image fusion
Huang, Bo
Institute of Space and Earth Information ScienceDepartment of Geography & Resource Management
The Chinese University of Hong KongE-mail: [email protected]
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Outline
• Remote sensing (RS)• Previous and current work
– Unified RS image fusion– Generation of high resolution air pollution data– Pollution data access using mobile phones
• Future intended work
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NASA’s Polar-Orbiting Satellites
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How much RS data so far?
• NASA’s Earth Observation System (EOS) program has about 4.2 petabytes (2010)– Large Hadron Collider (physics): 10-14 TB in a single year
• Similar sized collections can be expected in Europe and Asia
• EOS contains mostly satellite data…not air photos, map or field data
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Researchers and users often use the data they can get, not the data they truly need.
遙感研究者與使用者只能使用它們能得到的数据,而不是他們真正想要的数据。
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Satellite Sensor Properties
• Spatial resolution (r1)• Temporal resolution (r2)• Spectral resolution (r3)• Angular resolution (r4)
F(r1)*F(r2)*F(r3)*F(r4) Constants.t. on-board storage capacity data transmission rate
Resolution Trade-off
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Unified Fusion
• Blending images with high and low spatial, temporal, spectral, and angular resolutions to resolve their resolution difference and generate simultaneously high resolution Spatial-Temporal-Spectral-Angular (STSA) satellite data.
• Cost-effective solution.
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?
Spatio-temporal Image Fusion
April 2001 July 2001
LANDSAT (Revisit EVERY 16 DAYS; 30m)
MODIS (Revisit EVERY DAY; 500m)
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Land-cover (type) change
?
2000 2002
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Comparison with another algorithm
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……
…36 bands with 500/1000 m spatial resolution
7 bands with 30 m spatial resolution
36 bands with 30 m spatial resolution
Spatial and Spectral Fusion
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(b)(a)
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Fusion Software
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Retrieval of Air Pollutants from Fused Satellite Imagery
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Current MODIS 10km AOD (Aerosol Optical Depth) Product
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2013 年 03 月 05 日深圳 PM2.5 反演图
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2013 年 03 月 06 日深圳 PM2.5 反演图
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2013 年 03 月 07 日深圳 PM2.5 反演图
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智能手机应用程序获取指定位置 PM2.5的值
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2013 年 03 月 05 日深圳 NO₂ 反演图
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2013 年 03 月 06 日深圳 NO₂ 反演图
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2013 年 03 月 07 日深圳 NO₂ 反演图
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2013 年 03 月 05 日深圳 SO₂ 反演图
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2013 年 03 月 06 日深圳 SO₂ 反演图
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2013 年 03 月 06 日深圳 SO₂ 反演图
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2013 年 03 月 05 日深圳 O3 反演图
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2013 年 03 月 06 日深圳 O3 反演图
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2013 年 03 月 07 日深圳 O3 反演图
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Mobile GIS Design and Implementation
Supported by NSERC, Canada
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初始优化路径
改变的路径
050
100150200250300350400450500
5% 10% 20% 30% 40%Percentage of Link Costs Changed
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Static A*
LPA* withoutconstrained ellipse
LPA* withconstrained ellipse
渐进式优化
Traffic Simulation and Route Selection
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Future Work• Improve the air pollution retrieval algorithms
by accounting for more land surface data such as transportation, bldg density, etc.
• Generate long time-series air pollution data– Reconstruct , e.g. PM 2.5 data, when such data
were not available 8 years ago in HK and 2 years ago in mainland China
• Improve the air pollution App software and make it publicly available
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Thank you!