Clustering of Fine-Grained Tropical Soils using Data Science Tools Applied to their Geotechnical Properties

Article ID

58DM2

Detailed analysis of tropical soil clustering and data science applications in environmental studies.

Clustering of Fine-Grained Tropical Soils using Data Science Tools Applied to their Geotechnical Properties

Mayssa Alves Da Silva Sousa
Mayssa Alves Da Silva Sousa State University of Maranhão,
Roberto Quental Coutinho
Roberto Quental Coutinho
Laura Maria Goretti Da Motta
Laura Maria Goretti Da Motta
DOI

Abstract

The characterization of fine-grained tropical soils for use in pavements has evolved since the 1980s, however, even today these soils are still discarded or underused in infrastructure works because they do not fully meet the requirements established by traditional classification methodologies or even by the CBR. Tropical soils present peculiarities of geotechnical behavior regarding elastic and plastic deformability, as many authors have already observed. This article contributes to this distinction by analyzing the grouping of thirteen fine-grained soils from northeastern Brazil through the application of data science tools to the results of geotechnical tests. More than fifty geotechnical parameters obtained in the laboratory were considered. By means of simple and multiple linear regressions, they were analyzed in a hierarchical cluster, using Ward’s linkage method and Euclidean distance. The results showed that the mechanical behavior of soil compaction and the granulometry, especially the quantities of silt and fine sand, were decisive for the initial division of soils into clusters.

Clustering of Fine-Grained Tropical Soils using Data Science Tools Applied to their Geotechnical Properties

The characterization of fine-grained tropical soils for use in pavements has evolved since the 1980s, however, even today these soils are still discarded or underused in infrastructure works because they do not fully meet the requirements established by traditional classification methodologies or even by the CBR. Tropical soils present peculiarities of geotechnical behavior regarding elastic and plastic deformability, as many authors have already observed. This article contributes to this distinction by analyzing the grouping of thirteen fine-grained soils from northeastern Brazil through the application of data science tools to the results of geotechnical tests. More than fifty geotechnical parameters obtained in the laboratory were considered. By means of simple and multiple linear regressions, they were analyzed in a hierarchical cluster, using Ward’s linkage method and Euclidean distance. The results showed that the mechanical behavior of soil compaction and the granulometry, especially the quantities of silt and fine sand, were decisive for the initial division of soils into clusters.

Mayssa Alves Da Silva Sousa
Mayssa Alves Da Silva Sousa State University of Maranhão,
Roberto Quental Coutinho
Roberto Quental Coutinho
Laura Maria Goretti Da Motta
Laura Maria Goretti Da Motta

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Mayssa Alves Da Silva Sousa. 2026. “. Global Journal of Human-Social Science – B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 22 (GJHSS Volume 22 Issue B3): .

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Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

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GJHSS-B Classification: DDC Code: 418.007 LCC Code: P53
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Clustering of Fine-Grained Tropical Soils using Data Science Tools Applied to their Geotechnical Properties

Mayssa Alves Da Silva Sousa
Mayssa Alves Da Silva Sousa State University of Maranhão,
Roberto Quental Coutinho
Roberto Quental Coutinho
Laura Maria Goretti Da Motta
Laura Maria Goretti Da Motta

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