Youssouf El Jarjini, Moad Morarech, V. Vallès, Abdessamad Touiouine, M. Touzani, Y. Arjdal, Abdoul Azize Barry, L. Barbiero
{"title":"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","authors":"Youssouf El Jarjini, Moad Morarech, V. Vallès, Abdessamad Touiouine, M. Touzani, Y. Arjdal, Abdoul Azize Barry, L. Barbiero","doi":"10.3390/soilsystems7020033","DOIUrl":null,"url":null,"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.","PeriodicalId":21908,"journal":{"name":"Soil Systems","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2023-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Surface Formations Salinity Survey in an Estuarine Area of Northern Morocco, by Crossing Satellite Imagery, Discriminant Analysis, and Machine Learning\",\"authors\":\"Youssouf El Jarjini, Moad Morarech, V. Vallès, Abdessamad Touiouine, M. Touzani, Y. Arjdal, Abdoul Azize Barry, L. Barbiero\",\"doi\":\"10.3390/soilsystems7020033\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":21908,\"journal\":{\"name\":\"Soil Systems\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2023-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soil Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/soilsystems7020033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOIL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soil Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/soilsystems7020033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
Surface Formations Salinity Survey in an Estuarine Area of Northern Morocco, by Crossing Satellite Imagery, Discriminant Analysis, and Machine Learning
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.