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Evaluation of Desertification in the Middle Moulouya Basin (North-East Morocco) Using Sentinel-2 Images and Spectral Index Techniques

机译:Evaluation of Desertification in the Middle Moulouya Basin (North-East Morocco) Using Sentinel-2 Images and Spectral Index Techniques

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This article focuses on the quantitative assessment of desertification in the Middle Moulouya basin located in the North-East of Morocco. Indeed, this study aimed to map the degree of desertification at the level of the basin in 2018 using the Sentinel-2 image. To do this, we have adopted a methodology based on several stages. First, we extracted the spectral indices, in particular, the NDVI, the albedo, the TGSI and the MSAVI. Then, different combinations of these indices were the subject of a linear regression analysis (NDVI-albedo, MSAVI-albedo, albedo-TGSI and TGSI-MSAVI) to use the best correlated combinations to construct the feature space. The results obtained showed that the NDVI-albedo and MSAVI-albedo combinations are the best correlated with respective correlation coefficients of r = - 0.73 and r = - 0.76, respectively. As a result, they were used to propose the desertification degree index (DDI) by exploiting the NDVI-albedo and MSAVI-albedo feature spaces. Finally, a desertification map was generated for the entire basin. It has five degrees of desertification (extreme, severe, moderate, low, non-desertification). According to our results, the situation of desertification in the basin is alarming. Indeed, 86.86% of the study area is located in the moderate to extreme desertification class. While only 12.25% and 0.89% fall in the low and no desertification categories, respectively. The MSAVI-albedo model gave a high overall accuracy of 93.75%, so it is perfectly effective for the quantitative analysis and monitoring of desertification at the level of the basin studied.
机译:本文着重于定量评估荒漠化在中间一直延伸到穆卢耶盆地位于东北部摩洛哥。沙漠化程度的水平盆地2018年使用Sentinel-2形象。这一点,我们采用了一个方法论的基础上几个阶段。指标,特别是,反照率、归一化植被指数TGSI和MSAVI。这些指标是一个线性的主题回归分析(NDVI-albedo MSAVI-albedo,albedo-TGSI和TGSI-MSAVI)使用最好的相关的组合构造特征空间。NDVI-albedo和MSAVI-albedo组合最好与各自的相关性系数r = - 0.73和r = 0.76,分别。提出了荒漠化程度指数(DDI)利用NDVI-albedo MSAVI-albedo功能空间。生成整个盆地。沙漠化的程度(极端严重,温和,低,non-desertification)。我们的研究结果,沙漠化的情况盆地是惊人的。研究区位于中度到极端沙漠化类。下降0.89%的低和沙漠化类别,分别。给93.75%的整体精度高,所以它是完全有效的定量分析和监测沙漠化的程度盆地的研究。

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