Modelling soil temperature at multiple depths in Saurashtra region (Junagadh) of Gujarat using machine learning and shapely approach

Abstract Forecasting soil temperature (ST) at multiple depths is crucial for understanding meteorological processes, enhancing agricultural resilience, and assessing ecological and environmental risks. Data driven model represents an alternative tool to the conventional measurement of ST e.g. soil t...

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Principais autores:	Utkarsh Kumar, Rashmi, Ankur Srivastava, H. V. Parmar, H. H. Mashru, P. A. Pandya, G. V. Prajapati, H. D. Rank
Format:	Artigo
Jezik:	Inglês
Izdano:	Springer 2025-08-01
Serija:	Discover Applied Sciences
Teme:	Machine learning Soil temperature Random forest Meteorological data
Online dostop:	https://doi.org/10.1007/s42452-025-07572-3
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