Paper
7 October 2008 Using visible remotely sensed data for air quality study
H. S. Lim, M. Z. MatJafri, K. Abdullah, K. C. Tan, C. J. Wong, N. Mohd Saleh
Author Affiliations +
Abstract
Nowadays, air quality is a major concern in many countries whether in the developed or the developing countries. Due to the high cost and limited number of air pollutant stations in each area, they cannot provide a good spatial distribution of the air pollutant readings over a city. Satellite observations can give a high spatial distribution of air pollution. The objective of this study is to test the feasibility of using Landsat TM for retrieving the concentration of the particulate matter of size less than 10- micron (PM10). The retrieval of surface reflectance is important to obtain the atmospheric reflectance in remotely sensed data and later used for algorithm calibration. In this study, we retrieve the surface reflectance using the relationship between the two visible bands (blue and red) and the mid infrared data at 2.1 μm. We use the assumption that the mid infrared band data is not significantly affected by atmospheric haze. An algorithm was developed based on the aerosol properties to correlate the atmospheric reflectance and PM10. We also evaluate the used of the thermal band in the air quality study which is added into the proposed regression algorithm. The in situ PM10 data were collected simultaneously with the acquired satellite image. A high correlation coefficient (R) was obtained in this study between the measured and predicted PM10 values. Finally, a PM10 map was generated using the proposed algorithm and geometrically corrected. The generated PM10 was also colour coded for visual interpretation and smoothed using an average filter to minimize the random noise. This study indicated that the Landsat TM can be a very good tool for air quality study.
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H. S. Lim, M. Z. MatJafri, K. Abdullah, K. C. Tan, C. J. Wong, and N. Mohd Saleh "Using visible remotely sensed data for air quality study", Proc. SPIE 7114, Electro-Optical Remote Sensing, Photonic Technologies, and Applications II, 71140T (7 October 2008); https://doi.org/10.1117/12.800163
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KEYWORDS
Reflectivity

Atmospheric particles

Earth observing sensors

Satellites

Aerosols

Algorithm development

Landsat

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