文章基本信息

标题：Remote sensing of pm10 concentration measurement by internet protocol camera
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作者：Sultan Alsultan ; C.J. Wong ; H.S. Lim 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2006
卷号：XXXVI Part 7
出版社：Copernicus Publications
摘要：Due to the high cost and limited number of the air pollutant stations in the each area, they cannot provide a good spatial distribution of the air pollutant reading over a city. The objective of this study was to test the potential of an internet protocol (IP) camera digital camera for determination of particulate matter less than 10 micron (PM10). This study provided information on air quality over USM campus area. In situ data were measured simultaneously with the acquisition of IP camera data for algorithm regression analysis. The digital image was separated into three bands assigned as red, green and blue for multispectral algorithm regression. The digital numbers were extracted corresponding to the ground-truth locations for each band and then converted to radiance and reflectance values. The digital numbers of the three bands were converted into irradiance and then reflectance. The atmospheric reflectance values was extracted from the satellite observation reflectance values subtrated by the amount given by the surface reflectance. The relationship between the atmospheric reflectance and the corresponding air quality data was determined using regression analysis. A new algorithm was developed for detecting air pollution from the digital camera images chosen based on the highest correlation coefficient, R and lowest root mean square error, RMS for PM10. The algorithm produced a high correlation coefficient, R and low root-mean-square error, RMS, between the measured and estimated air quality measurements. The preliminary results demonstrated that the IP digital camera imageries can be use to estimate PM10 measurements accurately at a relatively much cheaper cost compared with other techniques
关键词：PM10; Internet Protocol; USM Campus; Multispectral Algorithm; Root-Mean-Square Error