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Retrieval of aerosol optical thickness from HJ-1 CCD data based on MODIS-derived surface reflectance

机译:基于MODIS的表面反射率从HJ-1 CCD数据反演气溶胶光学厚度

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摘要

The successfully launched Huanjing-1 (HJ-1) satellite by China in 2008 provides a new source of data for monitoring the environment. In this article, we develop a new algorithm for retrieving the aerosol optical thickness (AOT) using HJ-1 charge-coupled device (CCD) data with the assistance of the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data and the bidirectional reflectance distribution function (BRDF) data products. This algorithm is then used to retrieve AOT in a delta region of the Yangtze River. The retrieved results are assessed for their accuracy by comparison with ground-measured data using sun photometers. Comparison of such derived AOT with in situ AOT measured using sun photometers indicates a root mean squared error (RMSE) of 0.123, and their regression relation has a correlation coefficient of 0.896 that is statistically significant at the 0.01 level. Such a relatively high level of retrieval accuracy suggests that HJ-1 CCD data can be used competently and effectively to retrieve AOT with the assistance of MODIS products that are used to construct the surface reflectance model. This study successfully demonstrates the feasibility of synergistically retrieving AOT from data acquired by different sensors. The lower dependence on data from a sole source means that the retrieval is less restrictive by data availability.
机译:中国于2008年成功发射的Huanjing-1(HJ-1)卫星为监测环境提供了新的数据来源。在本文中,我们开发了一种新算法,该算法使用HJ-1电荷耦合器件(CCD)数据和中等分辨率成像光谱仪(MODIS)表面反射率数据以及双向反射率分布来检索气溶胶光学厚度(AOT)功能(BRDF)数据产品。然后,该算法用于检索长江三角洲地区的AOT。通过与使用太阳光度计的地面测量数据进行比较,评估了检索结果的准确性。将此类派生的AOT与使用太阳光度计测量的原位AOT进行比较表明,均方根误差(RMSE)为0.123,它们的回归关系的相关系数为0.896,在0.01的水平上具有统计学意义。如此高的检索精度表明,在用于构建表面反射率模型的MODIS产品的辅助下,HJ-1 CCD数据可以有效而有效地用于检索AOT。这项研究成功地证明了从不同传感器获取的数据协同检索AOT的可行性。对单一来源数据的依赖性较低,这意味着检索不受数据可用性的限制。

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  • 来源
    《International journal of remote sensing》 |2015年第4期|882-898|共17页
  • 作者单位

    Nanjing Normal Univ, Coll Geog Sci, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Key Lab Virtual Geog Environm,Minist Educ, Nanjing 210097, Jiangsu, Peoples R China|Shijiazhuang Univ, Dept Resources & Environm, Shijiazhuang 050035, Peoples R China;

    Nanjing Normal Univ, Coll Geog Sci, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Key Lab Virtual Geog Environm,Minist Educ, Nanjing 210097, Jiangsu, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China;

    Univ Auckland, Sch Environm, Auckland 1008, New Zealand;

    Nanjing Normal Univ, Coll Geog Sci, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Key Lab Virtual Geog Environm,Minist Educ, Nanjing 210097, Jiangsu, Peoples R China;

    Nanjing Normal Univ, Coll Geog Sci, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Key Lab Virtual Geog Environm,Minist Educ, Nanjing 210097, Jiangsu, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
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  • 正文语种 eng
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