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Applying Artificial Neural Networks and Remote Sensing to Estimate Chlorophyll-a Concentration in Water Body

机译:应用人工神经网络和遥感来估算水体中叶绿素的浓度

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The artificial neural networks (ANNs) were adopted to improve the monitoring capability of water quality in a reservoir using remote sensing images. Simultaneous measurement of chlorophyll-a concentration along the Feitsui Reservoir, the primary water supply of Taipei City, was conducted by ferryboat. Those ground measured values were used to calibrate empirical functions with multiple spectral parameters from Landsat 7 satellite images. The predictive capability of ANNs approach was evaluated and showed satisfied results.
机译:采用人工神经网络(ANNS)通过遥感图像改善水库水质的监测能力。沿着Feitsui水库,台北市初级供水的同时测量叶绿素浓度,由Ferryboat进行。这些地面测量值用于校准具有来自Landsat 7卫星图像的多谱参数的经验函数。评估ANNS方法的预测能力,并显示出满意的结果。

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