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Remote estimation of chl-a concentration in turbid productive waters - Return to a simple two-band NIR-red model?

机译:远程估算混浊生产水中的chl-a浓度-返回简单的两波段NIR-red模型吗?

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摘要

Today the water quality of many inland and coastal waters is compromised by cultural eutrophication in consequence of increased human agricultural and industrial activities. Remote sensing is widely applied to monitor the trophic state of these waters. This study investigates the performance of near infrared-red models for the remote estimation of chlorophyll-a concentrations in turbid productive waters and evaluates several near infrared-red models developed within the last 34years. Three models were calibrated for a dataset with chlorophyll-a concentrations from 0 to 100mgm~(-3) and validated for independent and statistically different datasets with chlorophyll-a concentrations from 0 to 100mgm~(-3) and 0 to 25mgm~(-3) for the spectral bands of the MEdium Resolution Imaging Spectrometer (MERIS) and MODerate resolution Imaging Spectroradiometer (MODIS). The MERIS two-band model estimated chlorophyll-a concentrations slightly more accurately than the more complex models, with mean absolute errors of 2.3mgm~(-3) for chlorophyll-a concentrations from 0 to 100mgm~(-3) and 1.2mgm~(-3) for chlorophyll-a concentrations from 0 to 25mgm~(-3). Comparable results from several near infrared-red models with different levels of complexity, calibrated for inland and coastal waters around the world, indicate a high potential for the development of a simple universally applicable near infrared-red algorithm.
机译:今天,由于人类农业和工业活动的增加,文化富营养化损害了许多内陆和沿海水域的水质。遥感被广泛应用于监测这些水域的营养状态。这项研究调查了近红外红色模型对浊度生产水中叶绿素a浓度的远程估计的性能,并评估了过去34年中开发的几种近红外红色模型。针对叶绿素a浓度为0至100mgm〜(-3)的数据集校准了三个模型,并针对叶绿素a浓度为0至100mgm〜(-3)和0至25mgm〜(-)的独立且统计上不同的数据集进行了验证。 3)适用于中等分辨率成像光谱仪(MERIS)和中等分辨率成像光谱仪(MODIS)的光谱带。 MERIS两波段模型估计叶绿素a的浓度比更复杂的模型更为准确,对于0至100 mgm〜(-3)和1.2mgm〜的叶绿素a浓度,平均绝对误差为2.3mgm〜(-3)。 (-3)的叶绿素a浓度为0至25mgm〜(-3)。针对世界各地的内陆和沿海水域进行校准的几种具有不同复杂程度的近红外红色模型的可比较结果表明,开发简单通用的近红外红色算法具有很大的潜力。

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