Surface Formations Salinity Survey in an Estuarine Area of Northern Morocco, by Crossing Satellite Imagery, Discriminant Analysis, and Machine Learning

IF 2.9 Q2 SOIL SCIENCE
Youssouf El Jarjini, Moad Morarech, V. Vallès, Abdessamad Touiouine, M. Touzani, Y. Arjdal, Abdoul Azize Barry, L. Barbiero
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Abstract

The salinity of estuarine areas in arid or semi-arid environments can reach high values, conditioning the distribution of vegetation and soil surface characteristics. While many studies focused on the prediction of soil salinity as a function of numerous parameters, few attempted to explain the role of salinity and its distribution within the soil profile in the pattern of landscape units. In a wadi estuary in northern Morocco, landscape units derived from satellite imagery and naturalistic environmental analysis are compared with a systematic survey of salinity by means of apparent electrical conductivity (Eca) measurements. The comparison is based on the allocation of measurement points to an area of the estuary from Eca measurements alone, using linear discriminant analysis and four machine learning methods. The results show that between 57 and 66% of the points are well-classified, highlighting that salinity is a major factor in the discrimination of estuary zones. The distribution of salinity is mainly the result of the interaction between capillary rise and flooding by the tides and the wadi. The location of the misclassified points is analysed and discussed, as well as the possible causes of the confusions.
摩洛哥北部河口地区地表地层盐度测量,基于交叉卫星图像、判别分析和机器学习
在干旱或半干旱环境中,河口地区的盐度可以达到很高的值,调节植被分布和土壤表面特征。虽然许多研究侧重于预测土壤盐度作为众多参数的函数,但很少有人试图解释盐度在景观单元格局中的作用及其在土壤剖面中的分布。在摩洛哥北部的一个瓦底河口,通过卫星图像和自然环境分析得出的景观单元与通过表观电导率(Eca)测量进行的盐度系统调查进行了比较。比较是基于Eca测量数据在河口区域的测量点分配,使用线性判别分析和四种机器学习方法。结果表明,57% ~ 66%的点分类良好,表明盐度是河口带区分的主要因素。盐度的分布主要是毛细上升、潮汐泛滥和河道相互作用的结果。分析和讨论了错误分类点的位置,以及造成混淆的可能原因。
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来源期刊
Soil Systems
Soil Systems Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
5.30
自引率
5.70%
发文量
80
审稿时长
11 weeks
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