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Evaluation of four MERIS atmospheric correction algorithms in Lake Kasumigaura, Japan

机译:日本霞浦湖四种MERIS大气校正算法的评估

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摘要

Accurate atmospheric correction for turbid inland waters remains a significant challenge. Several atmospheric correction algorithms have been proposed to address this issue, but their performance is unclear in regard to Asian lakes, some of which have extremely high turbidity and different inherent optical properties from lakes in other continents. Here, four existing atmospheric correction algorithms were tested in Lake Kasumigaura, Japan (an extremely turbid inland lake), using in situ water-leaving reflectance and concurrently acquired medium resolution imaging spectrometer (MERIS) images. The four algorithms are (1) GWI (the standard Gordon and Wang algorithm with an iterative process and a bio-optical model) (2) MUMM (Management Unit of the North Sea Mathematical Models); (3) SCAPE-M (Self-Contained Atmospheric Parameters Estimation for MERIS Data) and (4) C2WP (Case-2 Water Processor). The results show that all four atmospheric correction algorithms have limitations in Lake Kasumigaura, even though SCAPE-M and MUMM gave acceptable accuracy for atmospheric correction in several cases (relative errors less than 30% for the 2006 and 2008 images). The poor performance occurred because the conditions in Lake Kasumigaura (i.e. the atmospheric state and/or turbidity) did not always meet the assumptions in each atmospheric correction algorithm (e.g. in 2010, the relative errors ranged from 42% to 83%). These results indicate that further improvements are necessary to address the issue of atmospheric correction for turbid inland waters such as Lake Kasumigaura, Japan.
机译:对浑浊的内陆水域进行准确的大气校正仍然是一项重大挑战。已经提出了几种大气校正算法来解决这个问题,但是对于亚洲湖泊,它们的性能尚不清楚,其中一些具有极高的浊度,并且与其他大陆的湖泊具有不同的固有光学特性。在这里,使用原位留水反射率和同时获取的中分辨率成像光谱仪(MERIS)图像,在日本霞浦湖(一个极为浑浊的内陆湖)中测试了四种现有的大气校正算法。这四种算法是(1)GWI(具有迭代过程和生物光学模型的标准Gordon and Wang算法)(2)MUMM(北海数学模型的管理单元); (3)SCAPE-M(用于MERIS数据的自包含大气参数估计)和(4)C2WP(Case-2水处理机)。结果表明,即使在几种情况下SCAPE-M和MUMM给出了可接受的大气校正精度,所有四种大气校正算法在霞浦湖中都有局限性(2006和2008年图像的相对误差小于30%)。之所以表现不佳,是因为霞浦浦湖的条件(即大气状态和/或浊度)并不总是符合每种大气校正算法中的假设(例如,在2010年,相对误差范围为42%至83%)。这些结果表明,需要进一步改善以解决诸如日本霞浦湖之类的内陆混浊水域的大气校正问题。

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  • 来源
    《International journal of remote sensing》 |2013年第24期|8967-8985|共19页
  • 作者单位

    Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan;

    Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan;

    Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan,State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;

    Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan;

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