首页> 外文期刊>International journal of remote sensing >Validation of MERIS sensor's CoastColour algorithm for waters off the west coast of India
【24h】

Validation of MERIS sensor's CoastColour algorithm for waters off the west coast of India

机译:MERIS传感器的CoastColour算法在印度西海岸水域的验证

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Chlorophyll-a (chl-a) retrieved using the MERIS CoastColour (CC) algorithm was evaluated for the coastal waters of the west coast of India, against in situ observations made as part of the Satellite Coastal and Oceanographic Research (SATCORE) programme. These observations include profiles of surface solar irradiance (Es) along with those of upwelling radiance and downwelling irradiance, measured using hyperspectral radiometry. Chl-a was also estimated from water samples. Furthermore, remote-sensing reflectance (R-rs) and chl-a were retrieved from MODIS-Aqua using the OC3M algorithm, and from MERIS using the OC4E algorithm. In addition, to understand the long-term seasonal variability, chl-a retrieved from the MERIS-CC algorithm was overlaid on monthly mean chl-a time series data from MODIS. Comparison of chl-a using MERIS-CC to that measured in situ showed wide scatter around the linear trend line. We observed that chl-a from MERIS-CC was underestimated for two-thirds of the observations, whereas with MODIS and MERIS it was 51% and 44%, respectively. Statistical analysis showed an improved performance in chl-a retrieval using the operational OC4E algorithm as compared to that of MERIS-CC. The time series analysis showed a good match between in situ chl-a and that derived from MODIS using the OC3M algorithm, whereas the MERIS-CC algorithm showed inconsistency in match-up with regard to both magnitude and trend. This inconsistency was more prominent during the low-chl-a scenario during the northern winter. We infer that algorithms such as OC4E and OC3M that use bands from the blue and green regions of the spectrum offer better chlorophyll retrieval in high-TSM or -CDOM concentration waters in comparison with CoastColour, which uses all bands across the spectrum.
机译:使用MERIS CoastColour(CC)算法检索的叶绿素a(chl-a)已针对卫星西海岸和海洋学研究(SATCORE)计划的一部分进行的原位观测,对印度西海岸的沿海水域进行了评估。这些观察结果包括使用高光谱辐射测定法测量的表面太阳辐照度(Es)以及上升流辐射和下降流辐照度的轮廓。还可以从水样中估计Chl-a。此外,使用OC3M算法从MODIS-Aqua中检索遥感反射率(R-rs)和chl-a,使用OC4E算法从MERIS中检索遥感反射率。此外,为了了解长期的季节性变化,将从MERIS-CC算法检索到的chl-a覆盖在MODIS的每月平均chl-a时间序列数据上。使用MERIS-CC的chl-a与现场测量的chl-a的比较显示,线性趋势线周围分布较广。我们观察到,三分之二的观察结果低估了来自MERIS-CC的chl-a,而使用MODIS和MERIS的chl-a分别为51%和44%。统计分析表明,与MERIS-CC相比,使用可操作的OC4E算法在chl-a检索中的性能有所提高。时间序列分析显示原位chl-a与使用OC3M算法从MODIS导出的chl-a之间具有良好的匹配,而MERIS-CC算法在幅度和趋势方面显示出不一致的匹配。在北部冬季的低Chl-a情景中,这种矛盾更加突出。我们推断,与使用沿光谱所有波段的CoastColour相比,使用OC4E和OC3M之类的算法使用光谱中蓝色和绿色区域的波段,可在高TSM或-CDOM浓度水中提供更好的叶绿素检索。

著录项

  • 来源
    《International journal of remote sensing》 |2016年第9期|2066-2076|共11页
  • 作者单位

    Indian Natl Ctr Ocean Informat Serv, Hyderabad 500090, Andhra Pradesh, India;

    Indian Natl Ctr Ocean Informat Serv, Hyderabad 500090, Andhra Pradesh, India;

    Indian Natl Ctr Ocean Informat Serv, Hyderabad 500090, Andhra Pradesh, India;

  • 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
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号