徐州市GF-1卫星气溶胶光学厚度反演与空间特征分析
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摘要
目前,基于国内外发射的各种卫星传感器观测数据的陆地气溶胶光学厚度(AOD)反演方法与应用研究已相对成熟。然而,针对我国国产高空间分辨率(如高分一号)卫星数据的城市小区域尺度的反演与应用则相对较少。因此,选择使用深蓝算法对我国重要的工业型城市——徐州市进行国产GF-1 WFV数据AOD反演与空间特征分析,并利用地基AERONET同期数据进行反演结果验证。研究结果显示,2015—2017年6期的徐州市AOD整体空间格局稳定,均以人口聚集的城区呈高值分布为特征,不随季节变化,说明该地区空气污染源极可能以城市人为排放为主;与AERONET站点同期数据的相关性分析与时序分析结果表明,基于GF-1WFV高空间分辨率卫星数据的徐州市AOD反演结果质量良好。建议今后在大数据支撑下,应充分利用时空数据融合及机器学习等先进技术手段,弥补受云覆盖影响下单时间窗口GF-1卫星数据AOD反演的缺陷,以期达到国产高分卫星的更高时间、更高空间分辨率以及实时监测与预测的更高业务目标。
At present, research on aerosol optical depth(AOD) retrieval over land and application is relatively mature, based on observational data from various sensors aboard domestic and foreign satellites. However, the studies of domestic satellite data with high spatial resolution(e.g. GF-1) in the urban or small area scale are few. Here, we selected Deep Blue algorithm for AOD retrieval of GF-1 WFV data and analyze AOD spatial characteristics of Xuzhou city which is one of important industrial city in China. Then, AERONET synchronous data were used for verifying retrieval results. The results showed that: the overall spatial pattern of AOD is stable in Xuzhou during six periods from 2015 to 2017 characterized by population in dense, urban areas with high values and does not change with seasons, which indicated that the main source of air pollution in this area is probably urban man-made discharge; Relevance analysis and time series analysis with AERONET data proved that AOD retrieval of GF-1 in Xuzhou city has good quality. Therefore, we suggested that some advanced technologies, such as spatio-temporal data fusion and machine learning, can supply the gap of AOD retrieval of GF-1 in single time window influenced by cloud cover, so that it can be expected to achieve the higher temporal and spatial resolution, real-time monitoring and prediction of domestic high-resolution satellites.
At present, research on aerosol optical depth(AOD) retrieval over land and application is relatively mature, based on observational data from various sensors aboard domestic and foreign satellites. However, the studies of domestic satellite data with high spatial resolution(e.g. GF-1) in the urban or small area scale are few. Here, we selected Deep Blue algorithm for AOD retrieval of GF-1 WFV data and analyze AOD spatial characteristics of Xuzhou city which is one of important industrial city in China. Then, AERONET synchronous data were used for verifying retrieval results. The results showed that: the overall spatial pattern of AOD is stable in Xuzhou during six periods from 2015 to 2017 characterized by population in dense, urban areas with high values and does not change with seasons, which indicated that the main source of air pollution in this area is probably urban man-made discharge; Relevance analysis and time series analysis with AERONET data proved that AOD retrieval of GF-1 in Xuzhou city has good quality. Therefore, we suggested that some advanced technologies, such as spatio-temporal data fusion and machine learning, can supply the gap of AOD retrieval of GF-1 in single time window influenced by cloud cover, so that it can be expected to achieve the higher temporal and spatial resolution, real-time monitoring and prediction of domestic high-resolution satellites.
引文
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[13]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相机数据反演气溶胶光学厚度[J].遥感学报, 2015, 19(3):530-538.
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[15] FEDOSEJEVS G, O'NEILL N, ROYER A, et al. Aerosol optical depth for atmospheric correction of AVHRR composite data[R].Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000.
[16] WANG Z T, CHEN L F, HUI G, et al. Modified DDV method of aerosol optical depth inversion over land surfaces from CBERS02B[J]. J Remote Sens, 2009, 13(6):1053-1066.
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[21] HSU N C, TSAY S C, KING M D, et al. Deep blue retrievals of Asian aerosol properties during ACE-Asia[J]. IEEE Trans Geosci Remote Sensing, 2006, 44(11):3180-3195.
[22] HSU N C, JEONG M J, BETTENHAUSEN C, et al. Enhanced deep blue aerosol retrieval algorithm:the second generation[J]. J Geophys Res Atmos, 2013, 118(16):9296-9315.
[23] LI S S, CHEN L F, TAO J H, et al. Retrieval of aerosol optical depth over bright targets in the urban areas of North China during winter[J]. Sci China Earth Sci, 2012,55(9):1545-1553.
[24]邓孺孺,田国良,王雪梅,等.大气污染定量遥感方法及其在长江三角洲的应用[J].红外与毫米波学报, 2003,22(3):181-185.
[25]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):596-610.
[26] VIDOT J, SANTER R. Sea Wi FS level-3 products over land[J]. Proceedings of SPIE-The International Society for Optical Engineering, 2004, 5235:357-365.
[27] MARTONCHIK J V, DINER D J, CREAN K A, et al. Regional aerosol retrieval results from MISR[J]. IEEE Trans Geosci Remote Sensing,2002, 40(7):1520-1531.
[28] VACHON F, ROYER A, AUBE M, et al. Remote sensing of aerosols over North American land surfaces from POLDER and MODIS measurements[J]. Atmos Environ,2004, 38(21):3501-3515.
[29]李莘莘,陈良富,陶金花,等.基于HJ-1-CCD数据的地表反射率反演与验证[J].光谱学与光谱分析, 2011,31(2):516-520.
[30]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相机数据反演气溶胶光学厚度[J].遥感学报, 2015, 19(3):530-538.
[31]白照广.高分一号卫星的技术特点[J].中国航天,2013(8):5-9.
[32] Ackerman S A, Strabala K I, Menzel W P, et al. Discriminating clear sky from clouds with MODIS[J]. J Geophys RES-SPACE, 1998, 103(D24):32141-32157.
[33]张璐.基于国产遥感卫星数据的北京市气溶胶光学厚度反演研究[D].上海:华东师范大学, 2016.
[34]?NGSTR?M A. The parameters of atmospheric turbidity[J]. Tellus,1964, 16(1):64-75.
[35] VERMOTE E F, TANRéD, DEUZéJ L, et al. Second Simulation of the Satellite Signal in the Solar Spectrum,6S:an overview[M]//The social&economic history of the Hellenistic world, Oxford:Clarendon Press, 1997:675-686.
[36] KAUFMAN Y J, HOLBEN B N, TANRéD, et al. Will aerosol measurements from Terra and Aqua Polar Orbiting satellites represent the daily aerosol abundance and properties?[J]. Geophys Res Lett, 2000, 27(23):3861-3864.
[2]薛文博,武卫玲,王金南,等.中国气溶胶光学厚度时空演变特征分析[J].环境与可持续发展, 2013,38(4):17-20.
[3] GRIGGS M. Measurements of atmospheric aerosol optical thickness over water using ERTS-1 data[J]. Air Repair,1975, 25(6):622-626.
[4] MEKLER Y, QUENZEL H, OHRING G. Relative atmosphere aerosol content from erts observations[M]//Space Research:Elsevier, 1978:57-59.
[5] STOWE L L, JACOBOWITZ H, OHRING G, et al. The advanced very high resolution radiometer(AVHRR)pathfinder atmosphere(PATMOS)climate dataset:initial analyses and evaluations[J]. J Climate, 2002, 15(11):1243-1260.
[6] GORDON H R, WANG M H. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS:a preliminary algorithm[J]. Appl Opt,1994, 33(3):443-452.
[7] KING M D, KAUFMAN Y J, MENZEL W P, et al. Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer(MODIS)[J]. IEEE Trans Geosci Remote Sensing 1992,30(1):2-27.
[8] KAUFMAN Y J, TANRéD, REMER L A, et al. Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer[J]. J Geophys Res,1997, 102(D14):17051-17067.
[9] DINER D J, ABDOU W A, BRUEGGE C J, et al. MISR aerosol optical depth retrievals over southern Africa during the SAFARI-2000 dry season campaign[J]. Geophys Res Lett, 2001, 28(16):3127-3130.
[10] HERMAN M, DEUZéJ L, DEVAUX C, et al. Remote sensing of aerosols over land surfaces including polarization measurements and application to POLDER measurements[J]. J Geophys Res-Atmos, 1997, 102(D14):17039-17049.
[11] DEUZéJ L, BRéON F M, DEVAUX C, et al. Remote sensing of aerosols over land surfaces from POLDER-ADEOS-1 polarized measurements[J]. J Geophys Res, 2001, 106(D5):4913-4926.
[12]孙林,柳钦火,陈良富,等.环境与减灾小卫星高光谱成像仪陆地气溶胶光学厚度反演[J].遥感学报, 2006,10(5):770-776.
[13]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相机数据反演气溶胶光学厚度[J].遥感学报, 2015, 19(3):530-538.
[14] SUN K, CHEN X L, ZHU Z M, et al. High resolution aerosol optical depth retrieval using gaofen-1 WFV camera data[J]. Remote Sens, 2017, 9(1):89.
[15] FEDOSEJEVS G, O'NEILL N, ROYER A, et al. Aerosol optical depth for atmospheric correction of AVHRR composite data[R].Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000.
[16] WANG Z T, CHEN L F, HUI G, et al. Modified DDV method of aerosol optical depth inversion over land surfaces from CBERS02B[J]. J Remote Sens, 2009, 13(6):1053-1066.
[17] NICHOL J, BILAL M. Validation of MODIS 3 km resolution aerosol optical depth retrievals over Asia[J]. Remote Sens, 2016, 8(328).
[18] Levy R C, Remer L A, Kaufman Y J, et al. A New, Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS[J]. American Geophysical Union,2004:20040171556.
[19]李晓静,刘玉洁,邱红,等.利用MODIS资料反演北京及其周边地区气溶胶光学厚度的方法研究[J].气象学报, 2003, 61(5):580-591.
[20] HSU N C, TSAY S C, KING M D, et al. Aerosol properties over bright-reflecting source regions[J]. IEEE T Geosci Remote Sensing, 2004, 42(3):557-569.
[21] HSU N C, TSAY S C, KING M D, et al. Deep blue retrievals of Asian aerosol properties during ACE-Asia[J]. IEEE Trans Geosci Remote Sensing, 2006, 44(11):3180-3195.
[22] HSU N C, JEONG M J, BETTENHAUSEN C, et al. Enhanced deep blue aerosol retrieval algorithm:the second generation[J]. J Geophys Res Atmos, 2013, 118(16):9296-9315.
[23] LI S S, CHEN L F, TAO J H, et al. Retrieval of aerosol optical depth over bright targets in the urban areas of North China during winter[J]. Sci China Earth Sci, 2012,55(9):1545-1553.
[24]邓孺孺,田国良,王雪梅,等.大气污染定量遥感方法及其在长江三角洲的应用[J].红外与毫米波学报, 2003,22(3):181-185.
[25]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):596-610.
[26] VIDOT J, SANTER R. Sea Wi FS level-3 products over land[J]. Proceedings of SPIE-The International Society for Optical Engineering, 2004, 5235:357-365.
[27] MARTONCHIK J V, DINER D J, CREAN K A, et al. Regional aerosol retrieval results from MISR[J]. IEEE Trans Geosci Remote Sensing,2002, 40(7):1520-1531.
[28] VACHON F, ROYER A, AUBE M, et al. Remote sensing of aerosols over North American land surfaces from POLDER and MODIS measurements[J]. Atmos Environ,2004, 38(21):3501-3515.
[29]李莘莘,陈良富,陶金花,等.基于HJ-1-CCD数据的地表反射率反演与验证[J].光谱学与光谱分析, 2011,31(2):516-520.
[30]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相机数据反演气溶胶光学厚度[J].遥感学报, 2015, 19(3):530-538.
[31]白照广.高分一号卫星的技术特点[J].中国航天,2013(8):5-9.
[32] Ackerman S A, Strabala K I, Menzel W P, et al. Discriminating clear sky from clouds with MODIS[J]. J Geophys RES-SPACE, 1998, 103(D24):32141-32157.
[33]张璐.基于国产遥感卫星数据的北京市气溶胶光学厚度反演研究[D].上海:华东师范大学, 2016.
[34]?NGSTR?M A. The parameters of atmospheric turbidity[J]. Tellus,1964, 16(1):64-75.
[35] VERMOTE E F, TANRéD, DEUZéJ L, et al. Second Simulation of the Satellite Signal in the Solar Spectrum,6S:an overview[M]//The social&economic history of the Hellenistic world, Oxford:Clarendon Press, 1997:675-686.
[36] KAUFMAN Y J, HOLBEN B N, TANRéD, et al. Will aerosol measurements from Terra and Aqua Polar Orbiting satellites represent the daily aerosol abundance and properties?[J]. Geophys Res Lett, 2000, 27(23):3861-3864.
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