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Multitemporal Spectral Analysis for Algae Detection in an Eutrophic Lake using Sentinel 2 Images

机译:利用Sentinel 2图像对富营养化湖泊中藻类进行多时相光谱分析

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Eutrophication is characterized by excessive plant and algal growth due to the increased of organic matter, carbon dioxide and nutrients in water body. Although eutrophication naturally occurs over centuries as lakes age, human activities have accelerated it processes and caused dramatic changes to the aquatic ecosystems including elevated algae blooms and risk for hypoxia as well as degradation in the quality of drinking water and fisheries. Monitoring eutrophic processes is therefore highly important to human health and to the aquatic environment. However, the spatial and seasonal distribution of the phenomena and its dynamic are difficult to be resolved using conventional methods as water sampling or sparse acquisition of remote sensing data. This research work proposes a methodology that takes advantage of the high temporal resolution of Sentinel-2 (S2) for monitoring eutrophic reservoir. Specifically, it uses large temporal series of S2 images and advanced temporal unmixing model to estimate the abundance of [Chl-a] and algae species in San Roque reservoir, Argentina, in the period August 2016 to August 2019. The spatial patterns and the temporal tendencies of these aquatic indicators, that have a direct link to Eutrophication, were analysed and evaluated using in situ data in order to assess their contribution to the local water management.
机译:富营养化的特征是由于水体中有机物,二氧化碳和养分的增加,植物和藻类过度生长。尽管随着湖泊的老化,富营养化自然发生了几个世纪,但人类活动加速了富营养化的进程,并引起了水生生态系统的急剧变化,包括藻类大量繁殖,缺氧风险以及饮用水和渔业质量的下降。因此,监测富营养化过程对人类健康和水生环境极为重要。但是,使用常规方法如水采样或稀疏采集遥感数据很难解决该现象的空间和季节分布及其动态问题。这项研究工作提出了一种方法,该方法利用了Sentinel-2(S2)的高时间分辨率来监测富营养化储层。具体而言,它使用S2图像的大时空序列和高级时空分解模型来估计2016年8月至2019年8月期间阿根廷圣罗克水库中[Chl-a]和藻类的丰度。空间格局和时空这些与富营养化直接相关的水生指标的趋势已通过实地数据进行了分析和评估,以评估它们对当地水管理的贡献。

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