基于多源大数据的长三角城市群AQI遥感估算

Remote Estimation of AQI in the Yangtze River Delta Urban Agglomeration Based on Multi-source Big Data

长三角城市群的大气污染情况备受关注,本研究基于哨兵五号(Sentinel-5P)卫星遥感数据、地面大气污染国控点监测数据、气象数据、道路交通图层等多源大数据,首先定量获取研究区O_(3)、CO、NO_(2)、SO_(2)等要素的污染情况,并基于XGBoost机器学习模型定量估算研究区的大气颗粒物浓度,最后基于所有大气污染要素选择模型综合评判研究区空气质量指数(AQI)。本研究建立的大气污染各要素的遥感估算方法及AQI的综合评判方法可为区域大气污染的评定提供方法上的支持,并服务于大气污染综合治理、人民生产生活指引及健康防护等诸多方面。

The air pollution of the Yangtze River Delta urban agglomeration has attracted much attention.Based on Sentinel-5P satellite data,ground air pollution monitoring data,meteorological data,road traffic layers and other multi-source big data,this study quantitatively estimates the pollution of O_(3),CO,NO_(2),SO_(2)and other parameters in the study area,and quantitatively retrievals the atmospheric particles in the study area based on XGBoost machine learning model,Finally,the Air Pollution Index(AQI)of the study area is comprehensively evaluated based on the selection model of the utilization conditions of all air pollution parameters.The remote sensing inversion method of various elements of air pollution and the comprehensive evaluation method of AQI established in this study can provide methodological support for the assessment of regional air pollution,and serve the comprehensive treatment of air pollution,people s production and life,health protection and many other aspects.