Visual Analysis of the Air Pollution Visual Analysis of the Air - - PowerPoint PPT Presentation

visual analysis of the air pollution visual analysis of
SMART_READER_LITE
LIVE PREVIEW

Visual Analysis of the Air Pollution Visual Analysis of the Air - - PowerPoint PPT Presentation

Visual Analysis of the Air Pollution Visual Analysis of the Air Pollution Problem in Hong Kong Problem in Hong Kong CHAN Wing Yi, Winnie [Represented by MAK Wai Ho, Wallace] Department of Computer S cience and Engineering The Hong Kong


slide-1
SLIDE 1

CHAN Wing Yi, Winnie [Represented by MAK Wai Ho, Wallace]

Visual Analysis of the Air Pollution Visual Analysis of the Air Pollution Problem in Hong Kong Problem in Hong Kong

Hong Kong ICT Awards 2007: Best Innovation and Research Award ICT07/ IR/ CU-18

Department of Computer S cience and Engineering The Hong Kong University of S cience and Technology (HKUS T)

slide-2
SLIDE 2

2

Preface

  • This is the work of a final year thesis

(research option of final year proj ect)

  • The research paper will appear in

IEEE Transactions on Visualization and

Computer Graphics (TVCG).

Visual Analysis of the Air Pollution Problem in Hong Kong

Huamin Qu, Wing-Yi Chan, Anbang Xu, Kai-Lun Chung, Kai-Hon Lau, Ping Guo

IEEE Transactions on Visualization and Computer Graphics (TVCG), vol.13, no. 6, Nov.-Dec. 2007 (Proceedings of IEEE Visualization/ Information Visualization 2007)

slide-3
SLIDE 3

3

Outline

  • Introduction

▫ Background ▫ Uniqueness of Air Quality Data

  • Visualization Techniques
  • Experimental Results
  • Conclusions and Future Work
slide-4
SLIDE 4

4

Introduction

  • Visualization

▫ Presents data in pictorial form ▫ Visualizes the underlying data

effectively

  • Visual analysis

▫ Is a visual way for data mining

and decision making

▫ Performs analysis on the

visualization result

slide-5
SLIDE 5

5

Hong Kong Air Pollution Problem

  • Hong Kong air quality is

decreasing tremendously

  • Air pollution problem

becomes one of the biggest social issues

  • Causes are still unknown

▫ Many hypotheses are

proposed without any formal proof yet

The spectacular harbor view has been increasingly crippled by massive haze.

slide-6
SLIDE 6

6

Institute for the Environment of HKUST

  • Maintain a comprehensive database on Hong Kong

air quality data

  • Cannot obtain convincing results for high-level

correlations with mathematical techniques

  • Demand visualization techniques for analysis
slide-7
SLIDE 7

7

Uniqueness of Air Quality Data

  • Time-series (hourly-based)
  • Inherited geographic

information

  • Multi-dimensional

(typically >10 attributes)

  • Important vector field –

wind speed and direction

  • 1. Precipitation
  • 2. Wind Direction
  • 3. Air Temperature
  • 4. Wind S

peed

  • 5. Dew Point
  • 6. Relative Humidity
  • 7. S

ea Level Pressure

  • 8. Respirable S

uspended Particulates (RS P)

  • 9. Nitrogen dioxide (NO2)
  • 10. S

ulphur dioxide (S O2)

  • 11. Ozone (O3)
  • 12. Carbon monoxide (CO)
  • 13. S
  • lar Radiation
  • 14. Air Pollution Index (API)
  • 15. Contributed Pollutant to API

(S pans more than 10 years)

slide-8
SLIDE 8

8

Outline

  • Introduction
  • Visualization Techniques

▫ Polar S

ystem

▫ Parallel Coordinates ▫ Weighted Complete Graph

  • Experimental Results
  • Conclusions and Future Work
slide-9
SLIDE 9

9

Outline

  • Introduction
  • Visualization Techniques

▫ Polar S

ystem

▫ Parallel Coordinates ▫ Weighted Complete Graph

  • Experimental Results
  • Conclusions and Future Work
slide-10
SLIDE 10

10

Polar System

  • Is a common vector

representation

  • Is heavily applied by

domain scientists in environmental field

Distance from center Wind S peed Angle from the north Wind Direction Color S calar Attribute

very strong south wind high attribute value weak southwest wind low attribute value

slide-11
SLIDE 11

11

Circular Pixel Bars

  • Users select a sector to plot the inside-sector data

(i.e. of certain wind direction and speed)

  • The corresponding wind direction and wind speed is
  • bvious for rapid comparisons between sectors
slide-12
SLIDE 12

12

Outline

  • Introduction
  • Visualization Techniques

▫ Polar S

ystem

▫ Parallel Coordinates ▫ Weighted Complete Graph

  • Experimental Results
  • Conclusions and Future Work
slide-13
SLIDE 13

13

Parallel Coordinates

  • Parallel Coordinates are well-established visualization

tool for multi-dimensional data

  • Each parallel vertical axis represents an attribute
  • A data item is plotted by a polygonal line intersecting

each axis at the respective attribute data value

slide-14
SLIDE 14

14

S-Shape Axis for Vector

Traditional layout (not intuitive) Circular layout (lots of overlapping) S-style layout An example

slide-15
SLIDE 15

15

Outline

  • Introduction
  • Visualization Techniques

▫ Polar S

ystem

▫ Parallel Coordinates ▫ Weighted Complete Graph

  • Experimental Results
  • Conclusions and Future Work
slide-16
SLIDE 16

16

Weighted Complete Graph

  • It is used for exploring overall relationship

among all data dimensions

  • Each node represents one data dimension
  • Distance between nodes encodes

their correlation

A B C

correlated not really correlated

slide-17
SLIDE 17

17

Outline

  • Introduction
  • Visualization Techniques
  • Experimental Results

▫ Correlation Detection ▫ S

imilarities and Differences

▫ Time-S

eries Trend

  • Conclusions and Future Work
slide-18
SLIDE 18

18

[solar radiation]

Correlation Detection

  • RS

P is correlated with S O2 and O3, but not solar radiation

  • High API value (red pixels) are not found when S

O2 is high, inferring that S O2 contributed little to API

  • API is strongly correlated with O3 which is known to experts
  • S
  • me suspicious clusters are shown in [S

O2] and [O3] - a blue cluster is seen behind a green one

[SO2] [O3]

Color = Air Pollution Index (API)

slide-19
SLIDE 19

19

Similarities and Differences (1)

  • The Hong Kong society mostly weighs external

pollution factors more ▫ Pollutants blown in from factories on the Pearl

River Delta at the northwest of Hong Kong

  • Local pollution is often ignored

▫ Power plants ▫ Vehicles and vessels

slide-20
SLIDE 20

20

  • High S

O2 for most stations:

▫ S

trong wind

▫ Northwest wind ▫ External S

  • urces
  • High S

O2 for Kwai Chung:

▫ All wind speed ▫ S

  • uthwest wind

▫ Internal sources likely due

to cargo ships at Kwai Tsing Container Terminals

Similarities and Differences (2)

9 stat ions of 3 years data Color represents amount of S O2

slide-21
SLIDE 21

21

Time-Series Trend for Tung Chung

  • 2004 and 2005 plots are more similar
  • In 2006 plot, temperature varies dramatically
slide-22
SLIDE 22

22

Positive Feedback from Users

  • Domain scientists found that

the polar system with embedded pixel bar offers easy navigation to explore the data interactively

  • Parallel coordinates show

the general relationship for them to compare different data-sets rapidly

  • Weighted complete graph

provides correlation

  • verview that is useful for

initiating an analysis

slide-23
SLIDE 23

23

Outline

  • Introduction
  • Visualization Techniques
  • Experimental Results
  • Conclusions and Future Work
slide-24
SLIDE 24

24

Conclusions

  • Comprehensive System

▫ The first attempt designed for air quality analysis

  • Novel Techniques

▫ Polar system with circular pixel bars: scalar + vector ▫ Enhanced parallel coordinates: vector + time axes ▫ Weighted complete graph: correlation overview

  • Significant Application

▫ Analyzed Hong Kong air pollution problem ▫ Revealed known findings effectively ▫ Detected unknown patterns by domain scientists

slide-25
SLIDE 25

25

Future Work

  • Continue as a long-term proj ect with ENVF
  • Make the system available to the public on Web
  • Incorporate new datasets for further exploration
  • Add animations and other visual aids
slide-26
SLIDE 26

Thank You!

The End The End

slide-27
SLIDE 27

27

Q & A

Polar system with embedded circular pixel bars Weighted complete graph Enhanced parallel coordinates with S

  • shape vector axis