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Proceedings Paper

Temporal and spatial air quality monitoring using internet protocol camera and LANSAT5 satellite image
Author(s): C. J. Wong; H. S. Lim; M. Z. MatJafri; K. Abdullah; T. S. Chin
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Paper Abstract

Atmospheric fine particles with diameter less than 10 micron (PM10) have already become a major public health concern in any part of the world. These particles can be breathed more deeply into the lungs to cause adverse health effects. In order to prevent long exposure to these harmful atmospheric particles, this motivates a growing interest in developing efficient methods of fine particles monitoring. In this study, we proposed that an internet protocol camera and LANDSAT5 satellite image be used to monitor the temporal and spatial air quality. We developed an algorithm to converts multispectral image pixel values acquired from digital images into quantitative values of the concentrations of PM10. This algorithm was developed based on the regression analysis of relationship between the measured reflectance and the reflected components from a surface material and the ambient air. The computed PM10 values were compared to other standard values measured by a DustTrak meter. The correlation results showed that the newly develop algorithm produced a high degree of accuracy as indicated by high correlation coefficient (R2) and low root-mean-square-error (RMS). This study indicates that the temporal and spatial development of air quality can be monitored by using internet protocol camera and LANDSAT5 images.

Paper Details

Date Published: 11 May 2009
PDF: 9 pages
Proc. SPIE 7336, Signal Processing, Sensor Fusion, and Target Recognition XVIII, 73361P (11 May 2009); doi: 10.1117/12.820322
Show Author Affiliations
C. J. Wong, Univ. Sains Malaysia (Malaysia)
H. S. Lim, Univ. Sains Malaysia (Malaysia)
M. Z. MatJafri, Univ. Sains Malaysia (Malaysia)
K. Abdullah, Univ. Sains Malaysia (Malaysia)
T. S. Chin, Univ. Sains Malaysia (Malaysia)

Published in SPIE Proceedings Vol. 7336:
Signal Processing, Sensor Fusion, and Target Recognition XVIII
Ivan Kadar, Editor(s)

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