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首页> 外文期刊>Environmental earth sciences >Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie
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Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie

机译:经验和半分析算法在MERIS数据中估算伊利湖案例2水域中叶绿素a的应用

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Lake Erie is biologically the most active lake among the Great Lakes of North America, experiencing seasonal harmful algal blooms (HABs). The early detection of HABs in the Western Basin of Lake Erie (WBLE) requires a more efficient and accurate monitoring tool. Remote sensing is an efficient tool with high spatial and temporal coverage that can allow accurate and timely detection of the HABs. The WBLE is heavily influenced by the surrounding terrestrial ecosystem via rivers such as the Sandusky River and the Maumee River. As a result, the optical properties of the WBLE are influenced by multiple color producing agents (CPAs) such as phytoplankton, colored dissolved organic matter (CDOM), organic detritus, and terrigenous inorganic particles. The diversity of the CPAs and their non-linear interactions makes these waters optically complex, and the task of optical remote sensing for retrieving estimates of CPAs more challenging. Chlorophyll a, which is the primary light harvesting pigment in all phytoplankton, is used as a proxy for algal biomass. In this study, several published remote sensing algorithms and band ratio models were applied to the reflectance data from the full resolution MERIS sensor to remotely estimate chlorophyll a concentrations in the WBLE. Efficiency of the sensor and the algorithms performance were tested through a least squares regression and residual analysis. The results indicate that, among the suite of existing bio-optical models, the Simis semi-analytical algorithm provided the best model results for measures of algal biomass in the optically complex WBLE with R~2 of 0.65, RMSE 0.85 μg/l, (n = 71, P < 0.05). The superior results of this model in detecting chlorophyll a are attributed to several factors including optimizing spectral regions that are less sensitive to CDOM and the incorporation of correction factors such as absorption effects due to pure water (a_w), backscatter (b_b) from suspended matter and interference due to phycocyanin (δ), a major accessory pigment in the WBLE.
机译:伊利湖在生物学上是北美五大湖中最活跃的湖,经历了季节性有害藻华(HAB)。要在伊利湖西部盆地(WBLE)中早期检测到HAB,就需要一种更有效,更准确的监测工具。遥感是一种具有高时空覆盖率的有效工具,可以准确,及时地检测到HAB。 WBLE通过诸如桑达斯基河和莫米河之类的河流受到周围陆地生态系统的严重影响。结果,WBLE的光学特性受到多种颜色产生剂(CPA)的影响,例如浮游植物,有色溶解有机物(CDOM),有机碎屑和陆源性无机颗粒。 CPA的多样性及其非线性相互作用使这些水域在光学上变得复杂,而光学遥感技术在检索CPA估计值方面的任务更具挑战性。叶绿素a是所有浮游植物中主要的采光色素,被用作藻类生物量的替代物。在这项研究中,将几种已发布的遥感算法和谱带比模型应用于来自全分辨率MERIS传感器的反射率数据,以远程估计WBLE中的叶绿素a浓度。通过最小二乘回归和残差分析测试了传感器的效率和算法性能。结果表明,在现有的一组生物光学模型中,Simis半分析算法为光学复杂WBLE中藻类生物量的测量提供了最佳模型结果,R〜2为0.65,RMSE为0.85μg/ l,( n = 71,P <0.05)。该模型在检测叶绿素a方面的优异结果归因于几个因素,包括优化对CDOM较不敏感的光谱区域,并纳入校正因子,例如纯水(a_w),悬浮物的反向散射(b_b)引起的吸收效应WBLE中主要的辅助色素藻蓝蛋白(δ)引起的干扰。

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