利用社交媒体数据模拟城市空气质量趋势面
【摘要】近年来,随着城市的发展,空气污染日益严重。目前,我国城市空气质量监测主要依靠空气质量监测站,但监测站数量有限,并且空气质量在一个城市的不同区域会出现较大起伏,单一利用监测站不易发现城市所有位置的空气质量起伏变化。对此,利用带有地理位置信息的新浪微博数据,分析空气污染相关主题微博与空气质量监测站点空气质量指数(air quality index,AQI)数据的相关性,建立两者间的函数关联,提出了一种建立城市空气质量趋势面的方法。实验结果表明,该方法不仅能定性地表现出城市不同区域的相对空气质量,也可定量、细粒度地展示城市空气质量情况。
【关键词】 社交媒体; 新浪微博; 城市空气质量; 趋势面;
【DOI】
【基金资助】
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ISSN:1671-8860
CN: 42-1676/TN
Vol 42, No. 01, Pages 14-20
January 2017
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