基于NPP-VIIRS卫星数据的渤黄海浊度反演算法研究
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摘要
浊度是水环境和水质状况的重要监测指标。卫星遥感技术具有宏观的空间覆盖性和重复的定期采样性,是一种有效的监测水体浊度的方法。基于NPP-VIIRS卫星的遥感反射率,建立了一个适用于渤黄海的水体浊度遥感反演算法,并将其应用到VIIRS卫星图像上,研究了渤黄海水体浊度的时空分布特征。结果表明:该算法具有较高的反演精度(决定系数R~2为0.97,均方根误差为16 NTU,平均绝对误差为23 NTU,平均相对误差为34.63%)。渤黄海水体浊度在空间尺度上基本呈现近岸高、远岸低的分布特征;在时间尺度上,冬季浊度维持在一个较高的水平,春季浊度高值区逐渐收缩,夏季达到最低,只在沿岸区域仍有较高的浊度,而秋季浊度又逐渐升高。
Turbidity is an important indicator for monitoring water environment and water quality, and the satellite remote sensing technology has the advantages of macroscopic spatial coverage and repeated sampling, which is an effective way of monitoring water turbidity. Based on the remote sensing reflectivity of NPP-VIIRS satellite, a water turbidity remote sensing inversion algorithm is developed and applied to the VIIRS satellite data to obtain a long-time series of satellite-derived water turbidity in the Bohai and Yellow seas. The results indicate that the proposed algorithm has a high accuracy with the R~2 of 0.97, the root mean square error of 16 NTU, the mean absolute deviation of 23 NTU, and the mean relative error of 34.63%. On a spatial scale, the turbidity distributions are generally high in the near-shore areas and low in the offshore areas. In contrast in the time scale, the water turbidity is at a high level in winter, but the regions with high turbidity shrink in spring. The turbidity is generally at the lowest level in summer and only the coastal waters show high turbidity values. In autumn, the turbidity gradually increases.
Turbidity is an important indicator for monitoring water environment and water quality, and the satellite remote sensing technology has the advantages of macroscopic spatial coverage and repeated sampling, which is an effective way of monitoring water turbidity. Based on the remote sensing reflectivity of NPP-VIIRS satellite, a water turbidity remote sensing inversion algorithm is developed and applied to the VIIRS satellite data to obtain a long-time series of satellite-derived water turbidity in the Bohai and Yellow seas. The results indicate that the proposed algorithm has a high accuracy with the R~2 of 0.97, the root mean square error of 16 NTU, the mean absolute deviation of 23 NTU, and the mean relative error of 34.63%. On a spatial scale, the turbidity distributions are generally high in the near-shore areas and low in the offshore areas. In contrast in the time scale, the water turbidity is at a high level in winter, but the regions with high turbidity shrink in spring. The turbidity is generally at the lowest level in summer and only the coastal waters show high turbidity values. In autumn, the turbidity gradually increases.
引文
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[22] Chen Y H,Qiu Z F,Sun D Y,et al.Remote sensing of suspended particle size in Yellow Sea and Bohai Sea[J].Acta Optica Sinica,2015,35(9):0901008.陈亚慧,丘仲锋,孙德勇,等.黄渤海悬浮颗粒物粒径的遥感反演研究[J].光学学报,2015,35(9):0901008.
[23] Qiu Z F,Wu T T,Su Y Y.Retrieval of diffuse attenuation coefficient in the China seas from surface reflectance[J].Optics Express,2013,21(13):15287-15297.
[24] Qiu Z F,Su Y Y,Yang A N,et al.An approach for estimating absorption and backscattering coefficients from MERIS in the Bohai Sea[J].International Journal of Remote Sensing,2014,35(24):8169-8187.
[25] Chen J,Cui T W,Tang J W,et al.Remote sensing of diffuse attenuation coefficient using MODIS imagery of turbid coastal waters:a case study in Bohai Sea[J].Remote Sensing of Environment,2014,140:78-93.
[26] Bailey S W,Franz B A,Werdell P J.Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing[J].Optics Express,2010,18(7):7521-7527.
[27] He X Q,Bai Y,Pan D L,et al.Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters[J].Remote Sensing of Environment,2013,133:225-239.
[2] Friedl G,Wüest A.Disrupting biogeochemical cycles-consequences of damming[J].Aquatic Sciences,2002,64(1):55-65.
[3] Ren Y Q,Wang S Z.A seawater turbidity sensor[J].Ocean Technology,2004,23(4):29-31.任永琴,王世忠.海水浊度测量传感器研究[J].海洋技术,2004,23(4):29-31.
[4] Nechad B,Ruddick K G,Neukermans G.Calibration and validation of a generic multisensor algorithm for mapping of turbidity in coastal waters[J].Proceedings of SPIE,2009,7473:74730H.
[5] Shi W,Wang M H.Characterization of global ocean turbidity from Moderate Resolution Imaging Spectroradiometer ocean color observations[J].Journal of Geophysical Research,2010,115(C11):C11022.
[6] Juda L.The European union and the marine strategy framework directive:continuing the development of European ocean use management[J].Ocean Development & International Law,2010,41(1):34-54.
[7] Pyh?l? M.HELCOM Baltic Sea action plan:an ecosystem approach to the management of human activities[M]//Brander K,MacKenzie B,Omstedt A.Climate Impacts on the Baltic Sea:From Science to Policy.Berlin,Heidelberg:Springer,2012:45-69.
[8] Constantin S,Constantinescu ?,Doxaran D.Long-term analysis of turbidity patterns in Danube Delta coastal area based on MODIS satellite data[J].Journal of Marine Systems,2017,170:10-21.
[9] Caballero I,Navarro G.Application of extended full resolution MERIS imagery to assist coastal management of the area adjacent to the Guadalquivir estuary[J].Progress in Oceanography,2018,165:215-232.
[10] Zhu L Y.Remote sensing monitoring and assessment of water quality for lakes[D].Beijing:Graduate University of the Chinese Academy of Sciences,2006.祝令亚.湖泊水质遥感监测与评价方法研究[D].北京:中国科学院研究生院,2006.
[11] Goodin D G,Harrington J A,Jr,Nellis M D,et al.Mapping reservoir turbidity patterns using SPOT-HRV data[J].Geocarto International,1996,11(4):71-78.
[12] Feng Q,Cheng X J,Shen X,et al.Inland riverine turbidity estimation for Hanjiang River with Landsat 8 OLI imager[J].Geomatics and Information Science of Wuhan University,2017,42(5):643-647.冯奇,程学军,沈欣,等.利用Landsat 8 OLI进行汉江下游水体浊度反演[J].武汉大学学报(信息科学版),2017,42(5):643-647.
[13] Wang J G,Chen S G,Zhang T L,et al.Remote sensing retrieval algorithm for the turbidity in coastal waters using MODIS land band data[J].Journal of Ocean Technology,2016,35(4):20-25..王建国,陈树果,张亭禄,等.基于MODIS陆地波段的近岸水体浊度遥感方法[J].海洋技术学报,2016,35(4):20-25.
[14] Joshi I D,D′Sa E J,Osburn C L,et al.Turbidity in Apalachicola Bay,Florida from Landsat 5 TM and field data:seasonal patterns and response to extreme events[J].Remote Sensing,2017,9(4):367.
[15] Qiu Z F,Zheng L F,Zhou Y,et al.Innovative GOCI algorithm to derive turbidity in highly turbid waters:a case study in the Zhejiang coastal area[J].Optics Express,2015,23(19):A1179-A1193.
[16] Yu Y,Hu X Q,Min M,et al.NPP/visible infrared image radiometer suite low-light image fusion algorithm for city lights in mid-eastern China[J].Laser & Optoelectronics Progress,2018,55(10):102804.余越,胡秀清,闵敏,等.NPP/VIIRS微光图像融合中国中东部城市灯光算法[J].激光与光电子学进展,2018,55(10):102804.
[17] Li J,Zhu J H,Han B,et al.Validation of the VIIRS radiometric products with MODIS and in-situ data in the Bohai Sea[J].Journal of Ocean Technology,2016,35(2):27-33.李军,朱建华,韩冰,等.VIIRS在中国渤海的遥感反射率产品验证[J].海洋技术学报,2016,35(2):27-33.
[18] Li X W,Niu Z C,Jiang S,et al.Operational characteristics of environmental monitoring satellite Suomi NPP and usage in ecological environment monitoring[J].Environmental Monitoring and Forewarning,2014,6(3):1-6.李旭文,牛志春,姜晟,等.环境监测卫星 Suomi NPP业务特性及生态环境监测应用[J].环境监控与预警,2014,6(3):1-6.
[19] Ding Y,Huang J,Cui T W,et al.The decomposition method of MODIS images Enteromorpha mixed pixels based on the relation of NDVI to abundance[J].Acta Oceanologica Sinica,2015,37(7):123-131.丁一,黄娟,崔廷伟,等.基于NDVI与丰度关系的MODIS影像浒苔混合像元分解方法[J].海洋学报,2015,37(7):123-131.
[20] Huang C,Chen Y,Wu J P,et al.An evaluation of Suomi NPP-VIIRS data for surface water detection[J].Remote Sensing Letters,2015,6(2):155-164.
[21] Hillger D,Seaman C,Liang C,et al.Suomi NPP VIIRS imagery evaluation[J].Journal of Geophysical Research:Atmospheres,2014,119(11):6440-6455.
[22] Chen Y H,Qiu Z F,Sun D Y,et al.Remote sensing of suspended particle size in Yellow Sea and Bohai Sea[J].Acta Optica Sinica,2015,35(9):0901008.陈亚慧,丘仲锋,孙德勇,等.黄渤海悬浮颗粒物粒径的遥感反演研究[J].光学学报,2015,35(9):0901008.
[23] Qiu Z F,Wu T T,Su Y Y.Retrieval of diffuse attenuation coefficient in the China seas from surface reflectance[J].Optics Express,2013,21(13):15287-15297.
[24] Qiu Z F,Su Y Y,Yang A N,et al.An approach for estimating absorption and backscattering coefficients from MERIS in the Bohai Sea[J].International Journal of Remote Sensing,2014,35(24):8169-8187.
[25] Chen J,Cui T W,Tang J W,et al.Remote sensing of diffuse attenuation coefficient using MODIS imagery of turbid coastal waters:a case study in Bohai Sea[J].Remote Sensing of Environment,2014,140:78-93.
[26] Bailey S W,Franz B A,Werdell P J.Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing[J].Optics Express,2010,18(7):7521-7527.
[27] He X Q,Bai Y,Pan D L,et al.Using geostationary satellite ocean color data to map the diurnal dynamics of suspended particulate matter in coastal waters[J].Remote Sensing of Environment,2013,133:225-239.