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基于图像分析的颗粒物污染估计

Particle Pollution Estimation Based on Image Analysis.

作者信息

Liu Chenbin, Tsow Francis, Zou Yi, Tao Nongjian

机构信息

School of Chemistry & Chemical Engineering, Nanjing University, Nanjing, JiangSu, China.

Center for Bioelectronics and Biosensors, Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America.

出版信息

PLoS One. 2016 Feb 1;11(2):e0145955. doi: 10.1371/journal.pone.0145955. eCollection 2016.

DOI:10.1371/journal.pone.0145955
PMID:26828757
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4734658/
Abstract

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.

摘要

接触细颗粒物会引发各种疾病，而一种易于获取的监测颗粒物的方法有助于提高公众意识并减少有害接触。在此，我们报告一种基于对大量可获取的北京、上海（中国）和凤凰城（美国）户外图像进行分析来估算空气中颗粒物污染的方法。从这些图像中提取了六个图像特征，这些特征与其他相关数据（如太阳位置、日期、时间、地理信息和天气状况）一起用于预测PM2.5指数。结果表明，图像分析方法对PM2.5指数具有良好的预测效果，且不同特征在预测中具有不同的显著水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/fb6aff3a61b8/pone.0145955.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/2a8cf9a03d40/pone.0145955.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/b2512b1a9b1a/pone.0145955.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/44378b3a4918/pone.0145955.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/298cfbc3656d/pone.0145955.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/10d4d5b3cd44/pone.0145955.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/f044eabf491f/pone.0145955.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/fcd42aa10625/pone.0145955.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/2ad70a6a4b69/pone.0145955.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/8a085ba1318a/pone.0145955.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/fb6aff3a61b8/pone.0145955.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/2a8cf9a03d40/pone.0145955.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/b2512b1a9b1a/pone.0145955.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/44378b3a4918/pone.0145955.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/298cfbc3656d/pone.0145955.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/10d4d5b3cd44/pone.0145955.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/f044eabf491f/pone.0145955.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/fcd42aa10625/pone.0145955.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/2ad70a6a4b69/pone.0145955.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/8a085ba1318a/pone.0145955.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6f2f/4734658/fb6aff3a61b8/pone.0145955.g010.jpg

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