The dwarf eelgrass Zostera noltei Hornemann (Z. noltei) is the most dominant seagrass in semi-enclosed coastal systems of the Atlantic coast of Morocco. The species is experiencing a worldwide decline and monitoring the extent of its meadows would be a useful approach to estimate the impacts of natural and anthropogenic stressors. Here, we aimed to map the Z. noltei meadows in the Merja Zerga coastal lagoon (Atlantic coast of Morocco) using remote sensing. We used a random forest algorithm combined with field data to classify a SPOT 7 satellite image. Despite the difficulties related to the non-synchronization of the satellite images with the high tide coefficient, our results revealed, with an accuracy of 95%, that dwarf eelgrass beds can be discriminated successfully from other habitats in the lagoon. The estimated area was 160.76 ha when considering mixed beds (Z. noltei-associated macroalgae). The use of SPOT 7 satellite images seems to be satisfactory for long-term monitoring of Z. noltei meadows in the Merja Zerga lagoon and for biomass estimation using an NDVI–biomass quantitative relationship. Nevertheless, using this method of biomass estimation for dwarf eelgrass meadows could be unsuccessful when it comes to areas where the NDVI is saturated due to the stacking of many layers.

中文翻译：

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在SPOT 7卫星图像上使用随机森林算法对矮小鳗Z的变种进行定量和定量

在摩洛哥大西洋沿岸的半封闭沿海系统中，矮鳗鳗草Zostera noltei Hornemann（Z. noltei）是最主要的海草。该物种正在全球范围内减少，监测其草地的面积将是一种评估自然和人为压力源的影响的有用方法。在这里，我们的目标是绘制No.Z. Z.利用遥感技术，在梅尔哈·泽尔加（Merja Zerga）沿海泻湖（摩洛哥大西洋沿岸）的草地上。我们使用随机森林算法结合现场数据对SPOT 7卫星图像进行分类。尽管存在与高潮系数卫星图像不同步相关的困难，但我们的结果显示，以95％的准确度可以成功地将矮鳗草床与泻湖中的其他栖息地区分开。当考虑混合床（Z. noltei相关的大型藻类）时，估计面积为160.76公顷。SPOT 7卫星图像的使用对于长期监测诺氏梭菌似乎令人满意。梅尔哈·泽尔加泻湖中的草地，并使用NDVI-生物量定量关系进行生物量估算。然而，当涉及到由于多层堆积而使NDVI饱和的地区时，使用这种生物量估算方法对矮小鳗草草甸可能是不成功的。