大太阳天顶角下水色卫星叶绿素遥感探测能力研究
|
摘要
本文利用考虑地球曲率的矢量辐射传输模型PCOART-SA,对大太阳天顶角下叶绿素浓度的卫星遥感探测极限能力进行了模拟研究。结果表明:太阳-传感器几何参数,尤其是太阳天顶角对叶绿素浓度变化的探测极限能力影响较大;大太阳天顶角下,卫星对叶绿素浓度变化的探测能力下降十几倍。在典型陆架水体(叶绿素浓度为1μg/L),低太阳天顶角(30°)时,叶绿素浓度变化探测极限为0.012 8μg/L(约为原浓度的1.2%),而大太阳天顶角(80°)时,探测极限为0.136μg/L(约为原浓度的13.6%)。相比于太阳天顶角,观测天顶角增大造成的叶绿素浓度探测能力衰减较小。叶绿素浓度越高,吸收作用越强,对卫星遥感器的辐射探测灵敏度、定标及大气校正精度的要求越高。
The detection limit of satellite chlorophyll algorithm at large solar zenith angles(SZA) in polar regions was assessed using the vector radiative transfer model of PCOART-SA which has accounted for the spherical-shell atmosphere. It was found that the geometric parameters between sun and sensor, particularly the solar zenith angle, have significant influence in the detection limit of satellite chlorophyll algorithm. The minimum chlorophyll concentration detected by satellite is about 0.136 μg/L at large SZA of 80°, while the minimum value is 0.012 8 μg/L at 30°. Because of the high absorption resulted by chlorophyll, the satellite detection at large SZA is difficult, and thus requires high radiometric sensitivity sensor, more accurate calibration and atmospheric correction.
The detection limit of satellite chlorophyll algorithm at large solar zenith angles(SZA) in polar regions was assessed using the vector radiative transfer model of PCOART-SA which has accounted for the spherical-shell atmosphere. It was found that the geometric parameters between sun and sensor, particularly the solar zenith angle, have significant influence in the detection limit of satellite chlorophyll algorithm. The minimum chlorophyll concentration detected by satellite is about 0.136 μg/L at large SZA of 80°, while the minimum value is 0.012 8 μg/L at 30°. Because of the high absorption resulted by chlorophyll, the satellite detection at large SZA is difficult, and thus requires high radiometric sensitivity sensor, more accurate calibration and atmospheric correction.
引文
[1] 刘良明, 祝家东. 海洋水色遥感器发展趋势初探[J]. 遥感信息, 2011(2): 111-119. Liu Liangming, Zhu Jiadong. Preliminary study on trend of ocean color sensor development[J]. Remote Sensing Information, 2011(2): 111-119.
[2] 陈淼. 海洋水色卫星遥感算法综述[D]. 青岛: 中国海洋大学, 2005. Chen Miao. Summarization of algorithms of ocean color remote sensing[D]. Qingdao: Chinese Marine University, 2005.
[3] 潘德炉, 白雁. 我国海洋水色遥感应用工程技术的新进展[J]. 中国工程科学, 2008, 10(9): 14-24, 46. Pan Delu, Bai Yan. Advances on the application of ocean color remote sensing engineering in China[J]. Engineering Sciences, 2008, 10(9): 14-24,46.
[4] Choi J K, Park Y J, Ahn J H, et al. GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity[J]. Journal of Geophysical Research: Oceans, 2012, 117(C9): C09004.
[5] Ryu J H, Han H J, Cho S, et al. Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)[J]. Ocean Science Journal, 2012, 47(3): 223-233.
[6] Stamnes K, Tsay S C, Wiscombe W, et al. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media[J]. Applied Optics, 1988, 27(12): 2502-2509.
[7] Mobley C D. Light and Water: Radiative Transfer in Natural Waters[M]. New York: Academic Press, 1994.
[8] 项文华. 基于辐射传输模拟的太湖蓝藻水华遥感识别模式研究[D]. 南京: 南京大学, 2012. Xiang Wenhua. Study on the remote sensing detection of cyanobacteria blooms in lake taihu based on Radiative Transfer Model (RTM)[D]. Nanjing: Nanjing University, 2012.
[9] Chami M, Santer R, Dilligeard E. Radiative transfer model for the computation of radiance and polarization in an ocean-atmosphere system: polarization properties of suspended matter for remote sensing[J]. Applied Optics, 2001, 40(15): 2398-2416.
[10] Jin Zhonghai, Stamnes K. Radiative transfer in nonuniformly refracting layered media: atmosphere-ocean system[J]. Applied Optics, 1994, 33(3): 431-442.
[11] Fell F, Fischer J. Numerical simulation of the light field in the atmosphere-ocean system using the matrix-operator method[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2001, 69(3): 351-388.
[12] 何贤强, 潘德炉, 白雁, 等. 基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型[J]. 中国科学: 地球科学, 2006, 36(9): 860-870. He Xianqiang, Pan Delu, Bai Yan, et al. Vector radiative transfer numerical model of coupled ocean-atmosphere system using matrix-operator method[J]. Science in China Series D: Earth Sciences, 2007, 50(3): 442-452.
[13] He Xianqiang, Bai Yan, Zhu Qiankun, et al. A vector radiative transfer model of coupled ocean-atmosphere system using matrix-operator method for rough sea-surface[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2010, 111(10): 1426-1448.
[14] 何贤强, 潘德炉, 白雁, 等. 海洋-大气耦合矢量辐射传输粗糙海面模型[J]. 光学学报, 2010, 30(3): 618-624. He Xianqiang, Pan Delu, Bai Yan, et al. Rough sea-surface model for vector radiative transfer of coupled ocean-atmosphere system[J]. Acta Optica Sinica, 2010, 30(3): 618-624.
[15] 高永刚. MODTRAN和HYDROLIGHT辐射传输模型的耦合研究[D]. 北京: 北京师范大学, 2006. Gao Yonggang. Study on the coupling of MODTRAN and HYDROLIGHT radiation transmission models[D]. Beijing: Beijing Normal University, 2006.
[16] Mobley C D. Hydrolight 4.0 Users Guide[M]. Hydrolight Users Guide, 1998.
[17] Montes M J, Rhea J. Advice on selecting output depths when using fluorescence or Raman scattering in Hydrolight 4. 2[J]. 2006.
[18] 赵广志, 李晓威. 相对误差计算方法的理论探讨[J]. 计量技术, 2001(7): 47. Zhao Guangzhi, Li Xiaowei. Theoretical discussion on the calculation method of relative error[J]. Measurement Technique, 2001(7): 47.
[19] Pahlevan N, Lee Z, Hu Chuanmin, et al. Diurnal remote sensing of coastal/oceanic waters: a radiometric analysis for Geostationary Coastal and Air Pollution Events[J]. Applied Optics, 2014, 53(4): 648-665.
[20] Pahlevan N, Lee Z, Hu Chuanmin, et al. Analyzing radiometric requirements for diurnal observations of coastal/oceanic waters from geostationary orbits[C]//Proceedings of the Volume 8724, Ocean Sensing and Monitoring V. Baltimore, Maryland, United States: SPIE, 2013, 8724: 87240K, doi: 10.1117/12.2016279.
[21] Schott J R, Keller T E. Remote sensing the image chain approach[J]. Optics & Photonics News, 2001, 12(5): 57.
[22] 仲波. 大气气溶胶光学厚度遥感反演与遥感图像大气校正[D]. 北京: 中国科学院遥感应用研究所, 2004. Zhong Bo. Atmospheric aerosol optical depth remote sensing inversion algorithm and remote sensing image atmospheric correction[D]. Beijing: Institute of Remote Sensing Applications of the Chinese Academy of Sciences, 2004.
[2] 陈淼. 海洋水色卫星遥感算法综述[D]. 青岛: 中国海洋大学, 2005. Chen Miao. Summarization of algorithms of ocean color remote sensing[D]. Qingdao: Chinese Marine University, 2005.
[3] 潘德炉, 白雁. 我国海洋水色遥感应用工程技术的新进展[J]. 中国工程科学, 2008, 10(9): 14-24, 46. Pan Delu, Bai Yan. Advances on the application of ocean color remote sensing engineering in China[J]. Engineering Sciences, 2008, 10(9): 14-24,46.
[4] Choi J K, Park Y J, Ahn J H, et al. GOCI, the world's first geostationary ocean color observation satellite, for the monitoring of temporal variability in coastal water turbidity[J]. Journal of Geophysical Research: Oceans, 2012, 117(C9): C09004.
[5] Ryu J H, Han H J, Cho S, et al. Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)[J]. Ocean Science Journal, 2012, 47(3): 223-233.
[6] Stamnes K, Tsay S C, Wiscombe W, et al. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media[J]. Applied Optics, 1988, 27(12): 2502-2509.
[7] Mobley C D. Light and Water: Radiative Transfer in Natural Waters[M]. New York: Academic Press, 1994.
[8] 项文华. 基于辐射传输模拟的太湖蓝藻水华遥感识别模式研究[D]. 南京: 南京大学, 2012. Xiang Wenhua. Study on the remote sensing detection of cyanobacteria blooms in lake taihu based on Radiative Transfer Model (RTM)[D]. Nanjing: Nanjing University, 2012.
[9] Chami M, Santer R, Dilligeard E. Radiative transfer model for the computation of radiance and polarization in an ocean-atmosphere system: polarization properties of suspended matter for remote sensing[J]. Applied Optics, 2001, 40(15): 2398-2416.
[10] Jin Zhonghai, Stamnes K. Radiative transfer in nonuniformly refracting layered media: atmosphere-ocean system[J]. Applied Optics, 1994, 33(3): 431-442.
[11] Fell F, Fischer J. Numerical simulation of the light field in the atmosphere-ocean system using the matrix-operator method[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2001, 69(3): 351-388.
[12] 何贤强, 潘德炉, 白雁, 等. 基于矩阵算法的海洋-大气耦合矢量辐射传输数值计算模型[J]. 中国科学: 地球科学, 2006, 36(9): 860-870. He Xianqiang, Pan Delu, Bai Yan, et al. Vector radiative transfer numerical model of coupled ocean-atmosphere system using matrix-operator method[J]. Science in China Series D: Earth Sciences, 2007, 50(3): 442-452.
[13] He Xianqiang, Bai Yan, Zhu Qiankun, et al. A vector radiative transfer model of coupled ocean-atmosphere system using matrix-operator method for rough sea-surface[J]. Journal of Quantitative Spectroscopy and Radiative Transfer, 2010, 111(10): 1426-1448.
[14] 何贤强, 潘德炉, 白雁, 等. 海洋-大气耦合矢量辐射传输粗糙海面模型[J]. 光学学报, 2010, 30(3): 618-624. He Xianqiang, Pan Delu, Bai Yan, et al. Rough sea-surface model for vector radiative transfer of coupled ocean-atmosphere system[J]. Acta Optica Sinica, 2010, 30(3): 618-624.
[15] 高永刚. MODTRAN和HYDROLIGHT辐射传输模型的耦合研究[D]. 北京: 北京师范大学, 2006. Gao Yonggang. Study on the coupling of MODTRAN and HYDROLIGHT radiation transmission models[D]. Beijing: Beijing Normal University, 2006.
[16] Mobley C D. Hydrolight 4.0 Users Guide[M]. Hydrolight Users Guide, 1998.
[17] Montes M J, Rhea J. Advice on selecting output depths when using fluorescence or Raman scattering in Hydrolight 4. 2[J]. 2006.
[18] 赵广志, 李晓威. 相对误差计算方法的理论探讨[J]. 计量技术, 2001(7): 47. Zhao Guangzhi, Li Xiaowei. Theoretical discussion on the calculation method of relative error[J]. Measurement Technique, 2001(7): 47.
[19] Pahlevan N, Lee Z, Hu Chuanmin, et al. Diurnal remote sensing of coastal/oceanic waters: a radiometric analysis for Geostationary Coastal and Air Pollution Events[J]. Applied Optics, 2014, 53(4): 648-665.
[20] Pahlevan N, Lee Z, Hu Chuanmin, et al. Analyzing radiometric requirements for diurnal observations of coastal/oceanic waters from geostationary orbits[C]//Proceedings of the Volume 8724, Ocean Sensing and Monitoring V. Baltimore, Maryland, United States: SPIE, 2013, 8724: 87240K, doi: 10.1117/12.2016279.
[21] Schott J R, Keller T E. Remote sensing the image chain approach[J]. Optics & Photonics News, 2001, 12(5): 57.
[22] 仲波. 大气气溶胶光学厚度遥感反演与遥感图像大气校正[D]. 北京: 中国科学院遥感应用研究所, 2004. Zhong Bo. Atmospheric aerosol optical depth remote sensing inversion algorithm and remote sensing image atmospheric correction[D]. Beijing: Institute of Remote Sensing Applications of the Chinese Academy of Sciences, 2004.