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利用深蓝算法从HJ-1数据反演陆地气溶胶

         

摘要

大气气溶胶是环境空气污染监测的重要指标,在利用环境一号卫星CCD相机进行气溶胶监测时,暗目标法和结构函数法都有相应的不足.本文从Hsu等人(2004)提出的深蓝算法出发,以MODIS的地表反射率产品为基础建立反射率库,并利用地面观测数据分析了各种典型地物在CCD相机与MODIS蓝波段反射率之间关系,提出了将MODIS地表反射率修正到CCD相机的方法,进而实现地气解耦,反演气溶胶光学厚度.选择北京地区为实验区,进行了算法实验,并用AERONET/PHOTONS北京站的数据进行了验证,结果表明,(1)光学厚度较大时(>0.5),深蓝算法精度能够较好的满足环境一号卫星CCD相机对气溶胶日常监测的要求;(2)气溶胶模式会对结果产生较大的影响,尤其是城市型气溶胶.%Aerosol is an important index in atmosphere monitoring. Disadvantages exist when monitoring aerosol from HJ-1 data by dark dense vegetation (DDV) or contrast reduction algorithm. In this paper, based on the algorithm which was developed by Hsu, et al.(2004), the deep blue algorithm is applied to CCD/HJ-1. First, the database of land surface reflectance is built from MODerate-resolution Imaging Spectroradiometer (MODIS) spectral reflectance product. Second, after analyzing relationship between CCD camera reflectance and MODIS, the reflectance of MODIS are corrected to CCD camera of HJ-1. Third, aerosol optical depth (AOD) is retrieved from apparent reflectance in the first band of CCD/HJ-1. Finally, AODs over Beijing area are retrieved from December 2008 to October 2009, and the results are validated by ground-based measurement of Beijing station in the PHOtometrie pour le Traitement Operational de Normalisation Satellitaire (PHOTONS) network included in the worldwide Aerosol Robotic Network (AERONET). The validation and discussions show that, when AODs are greater than 0.5, the accuracy of deep blue algorithm can satisfy the aerosol monitoring using HJ-1 data, and aerosol model can greatly influence the results.

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