| 利用社交媒体数据模拟城市空气质量趋势面 |
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| 引用本文： | 王艳东,荆彤,姜伟,王腾,付小康.利用社交媒体数据模拟城市空气质量趋势面[J].武汉大学学报(信息科学版),2017,42(1):14-20. |
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| 作者姓名： | 王艳东 荆彤 姜伟 王腾 付小康 |
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| 作者单位： | 1.武汉大学测绘遥感信息工程国家重点实验室, 湖北 武汉, 430079 |
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| 基金项目： | 国家自然科学基金41271399测绘地理信息公益性行业科研专项经费201512015高等学校博士学科点专项科研基金20120141110036国家科技支撑计划2012BAH35B03 |
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| 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。
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| 关 键 词： | 社交媒体 新浪微博 城市空气质量 趋势面 |
| 收稿时间： | 2015-10-20 |
Modeling Urban Air Quality Trend Surface Using Social Media Data |
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| Institution: | 1.State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
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| Abstract: | Air pollution is getting worse with the development of cities in recent years. Urban air quality is mainly monitored by air quality monitoring stations at present. However, the number of stations is limited and the air quality fluctuates in different urban areas. So it is unefficient to detect air quality's distribution in a city by air quality monitoring stations only. Based on Sina Weibo data with location information, we propose an urban air quality trend surface modeling method by analysing the correlation between air pollution related topic microblogs and air quality monitoring station AQI data. The study reveals that our method not only qualitatively shows the relative air quality in diffferent regions of the city, but also demonstrations the urban air quality in a quantitative and fine-grained way. The findings of this study evaluate the feasibility of using a new type of large-scale data source for research on air quality estimation of any location in a city, and are of great significance when reflecting air quality distribution and finding areas where are relatively air polluted. |
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