引用本文:牛志春1,姜晟1,李旭文1,姚凌2.江苏省霾污染遥感监测业务化运行研究[J].环境监控与预警,2014,6(5):15-18
NIU Zhi chun1,JIANG Sheng1,LI Xu wen1,YAO Lin2.The Remote Sensing Monitoring Operational System of Haze Pollution in Jiangsu Province[J].Environmental Monitoring and Forewarning,2014,6(5):15-18
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江苏省霾污染遥感监测业务化运行研究
牛志春1,姜晟1,李旭文1,姚凌21,2
1.江苏省环境监测中心,江苏 南京 210036;2.中国科学院地理科学与资源研究所,北京 100101
摘要:
从霾污染遥感监测业务化流程出发,选取EOS/MODIS为主要数据源,MODIS气溶胶产品及气象数据为辅,在数据预处理的基础上,利用LM-BP人工神经网络模型算法反演区域大气颗粒物浓度,分析了可获取的遥感监测指标及气象指标对霾污染的贡献率,筛选出可业务化的霾污染遥感评价指标。对2013年1月江苏省2次典型的霾污染进行了星地同步分析,从分析结果来看,霾污染遥感监测结果与地面实测结果基本一致,霾污染遥感监测可以作为地面监测的有效补充,宏观反映区域霾污染空间分布,为大气污染防治提供有力的技术支撑。
关键词:  江苏省    遥感  监测  业务化
DOI:
分类号:X87
基金项目:江苏省环保科研课题项目(201130);江苏省环境监测科研基金项目(1217)
The Remote Sensing Monitoring Operational System of Haze Pollution in Jiangsu Province
NIU Zhi chun1,JIANG Sheng1,LI Xu wen1,YAO Lin2
The Remote Sensing Monitoring Operational System of Haze Pollution in Jiangsu Province
Abstract:
On the basis of the remote sensing monitoring operational processes of haze pollution, EOS/ MODIS and MODO4_L2 product were chosen as the main data and the secondary data, respectively. The LM-BP artificial neural network was used to retrieve the mass concentration of regional atmospheric particles. The contribution rate of the remote sensing monitoring index and the meteorological index on the haze pollution were analyzed. The operational remote sensing evaluation index of haze pollution was selected. Based on the synchronously analysis of two typical haze pollution cases in Jiangsu Province in January 2013,the remote sensing result was basically consistent with the ground measured result. Haze pollution remote sensing monitoring can be used as an effective supplement to the ground monitoring, macroscopically reflecting the spatial regional distribution of haze pollution. 
Key words:  Jiangsu Province  Haze  Remote sensing  Monitoring  Operational application