深蓝算法应用于FY-3B星数据反演陆地气溶胶
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摘要
利用国产风云三号卫星MERSI传感器监测气溶胶对研究气候变化、监测环境质量等有重要意义.在深蓝算法基础上,利用AQUA星MODIS的蓝光波段地表反射率产品,剔除异常值后作为清晰天的地表反射率,完成地气解耦,实现了FY-3B星MERSI传感器的气溶胶反演算法的构建.误差分析表明,MODIS与MERSI波段响应差异带来的气溶胶反演误差基本控制在0.07以下.针对北京地区,2016年4月至2017年3月的反演实验显示,本文获得的结果能较好地体现气溶胶浓度的空间分布,与MODIS气溶胶产品、AERONET地基观测结果有着较好的一致性;与城市型气溶胶相比,采用大陆型气溶胶能获得更多的有效数据,与地面数据的相关性也更高,相关指数在0.7左右.
The retrieval of aerosol from Chinese Medium Resolution Spectral Image(MERSI) data of FY-3 B satellite is important for climate change, environmental quality and so on. In the paper, based on Deep Blue algorithm which was proposed by Hsu et al, the method of aerosol retrieval from FY-3 B MERSI data was developed as follow, 1) after removing outliers by the average value of 5 points, the reflectance of clear day was received from MOD09 product of MODIS in 2015 in blue band; 2) the relationship between aerosol optical depth(AOD) and atmospheric parameters was calculated by 6 S vector; 3) after removing land surface contribution from MERSI's signal by the reflectance of clear day in blue band, the AOD was received by the atmospheric information of MERSI. Error analyst shows that the AOD error from the difference of filter response between MODIS and MERSI is under 0.07. Aimed to Beijing area, the retrieval experiment from April 2016 to March 2017 showed that removing cloud, rain, fog and so on, there are 60 days which were received AOD from MERSI and AERONET Beijing site.It was shown that 1) our method received aerosol distribution well, and the result has a good agreement with MODIS aerosol products and ground-based measures, and the correlation coefficient was higher than 0.7; 2) compared with urban aerosol, continental aerosol can receive more available data(60 points vs. 16 points), and higher agreement(correlation coefficient: 0.75 vs. 0.62).
The retrieval of aerosol from Chinese Medium Resolution Spectral Image(MERSI) data of FY-3 B satellite is important for climate change, environmental quality and so on. In the paper, based on Deep Blue algorithm which was proposed by Hsu et al, the method of aerosol retrieval from FY-3 B MERSI data was developed as follow, 1) after removing outliers by the average value of 5 points, the reflectance of clear day was received from MOD09 product of MODIS in 2015 in blue band; 2) the relationship between aerosol optical depth(AOD) and atmospheric parameters was calculated by 6 S vector; 3) after removing land surface contribution from MERSI's signal by the reflectance of clear day in blue band, the AOD was received by the atmospheric information of MERSI. Error analyst shows that the AOD error from the difference of filter response between MODIS and MERSI is under 0.07. Aimed to Beijing area, the retrieval experiment from April 2016 to March 2017 showed that removing cloud, rain, fog and so on, there are 60 days which were received AOD from MERSI and AERONET Beijing site.It was shown that 1) our method received aerosol distribution well, and the result has a good agreement with MODIS aerosol products and ground-based measures, and the correlation coefficient was higher than 0.7; 2) compared with urban aerosol, continental aerosol can receive more available data(60 points vs. 16 points), and higher agreement(correlation coefficient: 0.75 vs. 0.62).
引文
[1] KAUFMAN Y J,TANRE D,REMER L A,et al.Operational Remote Sensing of tropospheric aerosol over the land form EOS moderate resolution imaging spectroradiometer[J].Journal of Geophysical Research-Atmospheres,1997,102(14):17050-17068.
[2] LEVY R C,REMER L A,MATTOO S,et al.Second-generation operational algorithm:Retrieval of aerosol properties over land from inversion of moderate resolution imaging spectroradiometer spectral reflectance[J].Journal of Geophysical Research D.Atmosphere,2007,112(13):D13211,doi:10.1029/2006JD007811.
[3] 王中挺,辛金元,贾松林,等.利用暗目标法从高分一号卫星16 m相机反演气溶胶光学厚度[J].遥感学报,2015,19(3):530-538.WANG Z T,XIN J Y,JIA S L,et al.Retrieval of AOD from GF-1 16 m camera via DDV algorithm[J].Journal of Remote Sensing,2015,19(3):530-538.
[4] 许研,张炜.基于MODIS数据的中原经济区气溶胶时空分布特征[J].河南大学学报(自然科学版),2015,45(3):308-314.XU Y,ZHANG W.Study on long-term aerosol distribution over Central Plains Economic Region using MODIS data[J].Journal of Henan University(Natural Science),2015,45(3):308-314.
[5] 朱文德,徐澍,郑逢斌,等.基于MODIS数据的郑州地区PM2.5时空分布特征分析[J].河南大学学报(自然科学版),2018,2(48):172-178.ZHU W D,XU S,ZHENG F B,et al.Analysis of the spatial-temporal PM2.5 distribution over Zhengzhou area using MODIS data[J].Journal of Henan University(Natural Science),2018,2(48):172-178.
[6] DINER D J ,MARTONCHIK J V,KAHN R,et al.Using angular and spectral shape similarity constraints to improve MISR aerosol and surface retrievals over land[J].Remote Sensing of Environment,2005,94:155-171.
[7] HSU N C,TSAY S C,KING M D,et al.Aerosol properties over bright-reflecting source regions[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(3):557-569.
[8] HSU C N,TSAY S C,KING M D.Deep blue retrievals of asian aerosol properties during ACE-Asia[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(11):557-569.
[9] HSU N,JEONG M J,BETTENHAUSEN C,et al.Enhanced deep blue aerosol retrieval algorithm:The second generation[J].Journal of Geophysical Research:Atmospheres,2013,118(16):9296-9315.
[10] 杨忠东,卢乃锰,施进明,等.风云三号卫星有效载荷与地面应用系统概述[J].气象科技进展,2013,3(4):6-12.YANG Z D,LU N M,SHI J M,et al.Overview FY-3Payload ground application system[J].Meteorological Science Technology,2013,3(4):6-12.
[11] 杨军,董超华,卢乃锰,等.中国新一代极轨气象卫星:风云三号[J].气象学报,2009,67(4):501-509.YANG J,DONG C H,LU N M,et al.FY-3A:The new generation polar-orbiting meteorological satellite China[J].Acta Meteorologica Sinica,2009,67(4):501-509.
[12] 李晓静,张鹏,邱红,等.MERSI/FY-3A 陆上气溶胶产品介绍[C].北京:中国气象学会2008年年会,2008.LI X J,ZHANG P,QIU H,et al.The introduction of MERSI/FY-3A aerosol product over land surface[C].Beijing:Annual Meeting of Chinese Meteorological Society,2008.
[13] 滕维远.北京及其周边地区MERSI与MODIS数椐气溶胶光学厚度反演研究[D].北京:首都师范大学,2013.TENG W Y.The study of aersol optical depth over Beijing and around area based on MERSI and MODIS data[D].Beijing:Capital Normal University,2013.
[14] 张婕,刘昊野,辛金元,等.沈阳地区MODIS与MERSI气溶胶产品对比研究[J].遥感学报,2016,20(4):549-560.ZHANG J,LIU H Y,XIN J Y,et al.The comparison of MODIS and MERSI aerosol products in Shenyang[J].Journal of Remote Sensing,2016,20(4):549-560.
[15] TANRé D,HERMAN M,DESCHAMPS P Y,et al.Atmospheric modeling for space measurements of ground reflectances,including bidirectional properties[J].Applied Optics,1979,18(21):3587-3594.
[16] 王莉莉,辛金元,王跃思,等.CSHNET观测网评估MODIS气溶胶产品在中国区域的适用性[J].科学通报,2007,52(4):477-486.WANG L L,XIN J Y,WANG Y S,et al.Validation of MODIS aerosol products by CSHNET over China[J].Chinese Science Bulletin,2007,52(4):477-486.
[17] KOTCHENOVA S Y,VERMOTE E F,MATARRESE R,et al.Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data.Part I:Path radiance[J].Applied Optics,2006,45(26):6762-6774.
[18] 王中挺,厉青,陈良富,等.从MODIS数据反演粗细粒子气溶胶[J].光谱学与光谱分析.2011,31(10):2809-2813.WANG Z T,LI Q,CHEN L F,et al.The retrieval of fine and coarse aerosol from MODIS[J].Spectroscopy and Spectral Analysis,2011,31(10):2809-2813.
[19] 魏鹏,李正强,王堰,等.灰霾污染状况下气溶胶组分及辐射效应的遥感估算[J].遥感学报,2013,17(4):1021-1031.WEI P,LI Z Q,WANG Y,et al.Remote sensing estimation of aerosol composition and radiative effects in haze days[J].Journal of Remote Sensing,2013,17(4):1021-1031.
[20] 谢东海,程天海,吴俣,等.耦合京津冀气溶胶模式的HJ-1卫星CCD数据大气校正[J].光谱学与光谱分析,2016,36(5):1284-1290.XIE D H,CHENG T H,WU Y,et al.Atmospheric correction for HJ-1CCD data coupling with aerosol models of Beijing-Tianjin-Hebei Region[J].Spectroscopy and Spectral Analysis,2016,36(5):1284-1290.
[21] 任团伟,郭照冰,刘唯佳.2009-2011年北京地区大气气溶胶光学特性季节变化规律研究[J].环境化学,2015,34(12):2239-2247.REN T W,GUO Z B,LIU W J.Seasonal variation atmospheric aerosol optical properties Beijing during 2009-2011[J].Environmental Chemistry,2015,34(12):2239-2247.
[22] VERMOTE E F,KOTCHENOVA S Y.MOD09 user’s guide[EB/OL].http://modis-sr.ltdri.org,2008,/2018-12-12.
[23] 王中挺,厉青,王桥,等.利用深蓝算法从HJ-1数据反演陆地气溶胶[J].遥感学报,2012,16(3):615-629.WANG Z T,LI Q,WANG Q,et al.The retrieval of terrestrial aerosol from HJ-1 using deep blue algorithm[J].Journal of Remote Sensing,2012,16(3):615-629.
[24] HOLBEN B N,ECK T F,SLUTSKER I,et al.AERONET’s version 2.0 quality assurance criteria[C]//Remote Sensing of the Atmosphere and Clouds.International Society for Optics and Photonics,2006,6408:64080Q.
[2] LEVY R C,REMER L A,MATTOO S,et al.Second-generation operational algorithm:Retrieval of aerosol properties over land from inversion of moderate resolution imaging spectroradiometer spectral reflectance[J].Journal of Geophysical Research D.Atmosphere,2007,112(13):D13211,doi:10.1029/2006JD007811.
[3] 王中挺,辛金元,贾松林,等.利用暗目标法从高分一号卫星16 m相机反演气溶胶光学厚度[J].遥感学报,2015,19(3):530-538.WANG Z T,XIN J Y,JIA S L,et al.Retrieval of AOD from GF-1 16 m camera via DDV algorithm[J].Journal of Remote Sensing,2015,19(3):530-538.
[4] 许研,张炜.基于MODIS数据的中原经济区气溶胶时空分布特征[J].河南大学学报(自然科学版),2015,45(3):308-314.XU Y,ZHANG W.Study on long-term aerosol distribution over Central Plains Economic Region using MODIS data[J].Journal of Henan University(Natural Science),2015,45(3):308-314.
[5] 朱文德,徐澍,郑逢斌,等.基于MODIS数据的郑州地区PM2.5时空分布特征分析[J].河南大学学报(自然科学版),2018,2(48):172-178.ZHU W D,XU S,ZHENG F B,et al.Analysis of the spatial-temporal PM2.5 distribution over Zhengzhou area using MODIS data[J].Journal of Henan University(Natural Science),2018,2(48):172-178.
[6] DINER D J ,MARTONCHIK J V,KAHN R,et al.Using angular and spectral shape similarity constraints to improve MISR aerosol and surface retrievals over land[J].Remote Sensing of Environment,2005,94:155-171.
[7] HSU N C,TSAY S C,KING M D,et al.Aerosol properties over bright-reflecting source regions[J].IEEE Transactions on Geoscience and Remote Sensing,2004,42(3):557-569.
[8] HSU C N,TSAY S C,KING M D.Deep blue retrievals of asian aerosol properties during ACE-Asia[J].IEEE Transactions on Geoscience and Remote Sensing,2006,44(11):557-569.
[9] HSU N,JEONG M J,BETTENHAUSEN C,et al.Enhanced deep blue aerosol retrieval algorithm:The second generation[J].Journal of Geophysical Research:Atmospheres,2013,118(16):9296-9315.
[10] 杨忠东,卢乃锰,施进明,等.风云三号卫星有效载荷与地面应用系统概述[J].气象科技进展,2013,3(4):6-12.YANG Z D,LU N M,SHI J M,et al.Overview FY-3Payload ground application system[J].Meteorological Science Technology,2013,3(4):6-12.
[11] 杨军,董超华,卢乃锰,等.中国新一代极轨气象卫星:风云三号[J].气象学报,2009,67(4):501-509.YANG J,DONG C H,LU N M,et al.FY-3A:The new generation polar-orbiting meteorological satellite China[J].Acta Meteorologica Sinica,2009,67(4):501-509.
[12] 李晓静,张鹏,邱红,等.MERSI/FY-3A 陆上气溶胶产品介绍[C].北京:中国气象学会2008年年会,2008.LI X J,ZHANG P,QIU H,et al.The introduction of MERSI/FY-3A aerosol product over land surface[C].Beijing:Annual Meeting of Chinese Meteorological Society,2008.
[13] 滕维远.北京及其周边地区MERSI与MODIS数椐气溶胶光学厚度反演研究[D].北京:首都师范大学,2013.TENG W Y.The study of aersol optical depth over Beijing and around area based on MERSI and MODIS data[D].Beijing:Capital Normal University,2013.
[14] 张婕,刘昊野,辛金元,等.沈阳地区MODIS与MERSI气溶胶产品对比研究[J].遥感学报,2016,20(4):549-560.ZHANG J,LIU H Y,XIN J Y,et al.The comparison of MODIS and MERSI aerosol products in Shenyang[J].Journal of Remote Sensing,2016,20(4):549-560.
[15] TANRé D,HERMAN M,DESCHAMPS P Y,et al.Atmospheric modeling for space measurements of ground reflectances,including bidirectional properties[J].Applied Optics,1979,18(21):3587-3594.
[16] 王莉莉,辛金元,王跃思,等.CSHNET观测网评估MODIS气溶胶产品在中国区域的适用性[J].科学通报,2007,52(4):477-486.WANG L L,XIN J Y,WANG Y S,et al.Validation of MODIS aerosol products by CSHNET over China[J].Chinese Science Bulletin,2007,52(4):477-486.
[17] KOTCHENOVA S Y,VERMOTE E F,MATARRESE R,et al.Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data.Part I:Path radiance[J].Applied Optics,2006,45(26):6762-6774.
[18] 王中挺,厉青,陈良富,等.从MODIS数据反演粗细粒子气溶胶[J].光谱学与光谱分析.2011,31(10):2809-2813.WANG Z T,LI Q,CHEN L F,et al.The retrieval of fine and coarse aerosol from MODIS[J].Spectroscopy and Spectral Analysis,2011,31(10):2809-2813.
[19] 魏鹏,李正强,王堰,等.灰霾污染状况下气溶胶组分及辐射效应的遥感估算[J].遥感学报,2013,17(4):1021-1031.WEI P,LI Z Q,WANG Y,et al.Remote sensing estimation of aerosol composition and radiative effects in haze days[J].Journal of Remote Sensing,2013,17(4):1021-1031.
[20] 谢东海,程天海,吴俣,等.耦合京津冀气溶胶模式的HJ-1卫星CCD数据大气校正[J].光谱学与光谱分析,2016,36(5):1284-1290.XIE D H,CHENG T H,WU Y,et al.Atmospheric correction for HJ-1CCD data coupling with aerosol models of Beijing-Tianjin-Hebei Region[J].Spectroscopy and Spectral Analysis,2016,36(5):1284-1290.
[21] 任团伟,郭照冰,刘唯佳.2009-2011年北京地区大气气溶胶光学特性季节变化规律研究[J].环境化学,2015,34(12):2239-2247.REN T W,GUO Z B,LIU W J.Seasonal variation atmospheric aerosol optical properties Beijing during 2009-2011[J].Environmental Chemistry,2015,34(12):2239-2247.
[22] VERMOTE E F,KOTCHENOVA S Y.MOD09 user’s guide[EB/OL].http://modis-sr.ltdri.org,2008,/2018-12-12.
[23] 王中挺,厉青,王桥,等.利用深蓝算法从HJ-1数据反演陆地气溶胶[J].遥感学报,2012,16(3):615-629.WANG Z T,LI Q,WANG Q,et al.The retrieval of terrestrial aerosol from HJ-1 using deep blue algorithm[J].Journal of Remote Sensing,2012,16(3):615-629.
[24] HOLBEN B N,ECK T F,SLUTSKER I,et al.AERONET’s version 2.0 quality assurance criteria[C]//Remote Sensing of the Atmosphere and Clouds.International Society for Optics and Photonics,2006,6408:64080Q.