Soil salinization poses a multifaceted challenge demanding a comprehensive approach combining environmental science, machine learning, geography, and socio- economic analysis. Our study integrates these disciplines to unravel the complexities of soil salinization and devise effective mitigation strategies. We ground our investigation in understanding the geological and climatic fundamentals governing soil properties and processes, with a focus on the Mediterranean coastal areas. By harnessing the power of machine learning, we navigate the high-dimensionality and non-linearity of soil salinization, incorporating a comprehensive set of variables spanning geological, climatic, human activity, and socio-economic dimensions. Our models, trained on extensive datasets, are robust and capable of capturing intricate patterns associated with soil salinization. The Mediterranean coastal areas, with their unique ecological, climatic, and anthropogenic interactions, serve as a valuable case study for exploring the dynamics of soil salinization. Our approach integrates data on historical geological changes with current climatic and anthropogenic variables, creating a comprehensive model that encapsulates the temporal and spatial dimensions of soil salinization. This study aims to contribute meaningfully to global efforts in sustainable land management and environmental preservation.
University of Florence, Italy - ORCID: 0009-0006-5323-5577
University of Florence, Italy - ORCID: 0000-0002-3142-2543
Chapter Title
Machine learning for sustainable land management: A focus on Italy
Authors
Matteo Dalle Vaglie, Federico Martellozzo
Language
Italian
DOI
10.36253/979-12-215-0556-6.61
Peer Reviewed
Publication Year
2024
Copyright Information
© 2024 Author(s)
Content License
Metadata License
Book Title
Tenth International Symposium Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques
Book Subtitle
Livorno (Italy) 11th-13th June 2024
Editors
Laura Bonora, Marcantonio Catelani, Matteo De Vincenzi, Giorgio Matteucci
Peer Reviewed
Publication Year
2024
Copyright Information
© 2024 Author(s)
Content License
Metadata License
Publisher Name
Firenze University Press
DOI
10.36253/979-12-215-0556-6
eISBN (pdf)
979-12-215-0556-6
eISBN (xml)
979-12-215-0557-3
Series Title
Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques
Series E-ISSN
2975-0288