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A simple and efficient approach for coarse segmentation of Moroccan coastal upwelling

机译:一种简单有效的摩洛哥沿海上升流粗分割方法

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In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evaluation and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the applicability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remaining ocean waters. The algorithm has been applied and validated by an oceanographer over a database of 66 SST images corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reliable on different upwelling scenarios and for a wide variety of oceanographic conditions.
机译:在这项工作中,我们的目标是使用图像分割中的常规方法开发一种简单快速的算法,以从海面温度(SST)卫星图像中自动检测和提取摩洛哥沿海地区的上升流区域。我们的方法基于Otsu和Fuzzy C-means这两种无监督分类方法的评估和比较,并探讨了这些方法在分类问题中的适用性。后者包括对主要热锋的粗探测,将沿海冷上升流水与其余海水分开。该算法已由海洋学家在与2004年,2005年,2007年和2009年的摩洛哥南部沿海上升流相对应的66张SST图像的数据库上应用和验证。结果表明,所提出的算法在不同的上升流情况下是有希望且可靠的并适用于各种各样的海洋学条件。

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