CAJ | 학술논문

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。
종매오염요감감측업무화류정출발，선취 EOS／MODIS 위주요수거원，MODIS 기용효산품급기상수거위보，재수거예처리적기출상，이용 LM－BP인공신경망락모형산법반연구역대기과립물농도，분석료가획취적요감감측지표급기상지표대매오염적공헌솔，사선출가업무화적매오염요감평개지표。대2013년1월강소성2차전형적매오염진행료성지동보분석，종분석결과래간，매오염요감감측결과여지면실측결과기본일치，매오염요감감측가이작위지면감측적유효보충，굉관반영구역매오염공간분포，위대기오염방치제공유력적기술지탱。
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 re-trieve 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 se-lected.Based on the synchronously analysis of two typical haze pollution cases in Jiangsu Province in January 2013,the remote sens-ing result was basically consistent with the ground measured result.Haze pollution remote sensing monitoring can be used as an ef-fective supplement to the ground monitoring,macroscopically reflecting the spatial regional distribution of haze pollution.