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Proceedings Paper

A simple method for the detection of PM2.5 air pollutions using MODIS data
Author(s): Yoshinobu Kato
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Paper Abstract

In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients, the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms. In this paper, we examine various images (i.e., single-band images, band-difference images, RGB composite color images) to find a good method for detecting PM2.5 air pollutions by using MODIS data. A good method for the detection of PM2.5 air pollution is {R, G, B = band10, band9, T11}, where T11 is the brightness temperature of band31. In this composite color image, PM2.5 air pollutions are represented by light purple or pink color. This proposed method is simpler than the method by Nagatani et al. (2013), and is useful to grasp the distribution of PM2.5 air pollutions in the wide area (e.g., from China and India to Japan). By comparing AVI image with the image by proposed method, DSS and PM2.5 air pollutions can be classified.

Paper Details

Date Published: 5 May 2016
PDF: 12 pages
Proc. SPIE 9876, Remote Sensing of the Atmosphere, Clouds, and Precipitation VI, 98762X (5 May 2016); doi: 10.1117/12.2223947
Show Author Affiliations
Yoshinobu Kato, Fukui Univ. of Technology (Japan)


Published in SPIE Proceedings Vol. 9876:
Remote Sensing of the Atmosphere, Clouds, and Precipitation VI
Eastwood Im; Raj Kumar; Song Yang, Editor(s)

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