Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction.
Details
- Particle Pollution Estimation Based on Image Analysis
- Liu, Chenbin (Author)
- Tsow, Francis (Author)
- Zou, Yi (Author)
- Tao, Nongjian (Author)
- Biodesign Institute (Contributor)
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Digital object identifier: 10.1371/journal.pone.0145955
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Identifier TypeInternational standard serial numberIdentifier Value1045-3830
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Identifier TypeInternational standard serial numberIdentifier Value1939-1560
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The article is published at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0145955
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Liu, C., Tsow, F., Zou, Y., & Tao, N. (2016). Particle Pollution Estimation Based on Image Analysis. Plos One, 11(2). doi:10.1371/journal.pone.0145955