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Integration of remote sensing data and in situ measurements to monitor the water quality of the Ismailia Canal, Nile Delta, Egypt

机译:遥感数据的集成以及原位测量监测埃及尼罗河三角洲的伊尔梅利亚运河的水质

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摘要

The Ismailia Canal is one of the most important tributaries of the River Nile in Egypt. It is threatened by extinction from several sources of pollution, in addition to the intersection and nearness of the canal path with the Bilbayes drain and the effluent from the two largest conventional wastewater treatment plants in Greater Cairo. In this study, the integration of remote sensing and geospatial information system techniques is carried out to enhance the contribution of satellite data in water quality management in the Ismailia Canal. A Landsat-8 operational land imager image dated 2018 was used to detect the land use and land cover changes in the area of study, in addition to retrieving various spectral band ratios. Statistical correlations were applied among the extracted band ratios and the measured in situ water quality parameters. The most appropriate spectral band ratios were extracted from the NIR band (near infrared/blue), which showed a significant correlation with eight water quality metrics (CO3, BOD5, COD, TSS, TDS, Cl, NH4, and fecal coliform bacteria). A linear regression model was then established to predict information about these important water quality parameters along Ismailia Canal. The developed models, using linear regression equations for this study, give a set of powerful decision support frameworks with statistical tools to provide comprehensive, integrated views of surface water quality information under similar circumstances.
机译:Ismailia Canal是埃及河河畔最重要的支流之一。除了在大型野原的两大常规废水处理厂的运河路径的交叉口和近乎近的运河路径和近乎河流的近距离,它是由几个污染源的灭绝威胁。在这项研究中,进行了遥感和地理空间信息系统技术的集成,以增强卫星数据在ISMailia运河中水质管理中的贡献。除了检索各种光谱带比外,覆盖2018年日期的土地使用2018年的运营土地成像器图像还用于检测研究领域的土地利用和陆地覆盖变化。在提取的带比和测量的原位水质参数中施加统计相关性。从NIR带(近红外/蓝色)中提取最合适的光谱带比,其显示与八个水质度量(CO3,BOD5,COD,TSS,TDS,Cl,NH 4和粪便大肠杆菌细菌具有显着相关性。然后建立线性回归模型以预测沿着ISMailia Conal的这些重要水质参数的信息。开发的模型,使用这项研究的线性回归方程,给出了一套强大的决策支持框架,统计工具可以在类似情况下提供地面水质信息的全面,集成视图。

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