Comparison of Machine Learning-Based Prediction of Qualitative and Quantitative Digital Soil-Mapping Approaches for Eastern Districts of Tamil Nadu, India

Comparison of Machine Learning-Based Prediction of Qualitative and Quantitative Digital Soil-Mapping Approaches for Eastern Districts of Tamil Nadu, India

The soil–environmental relationship identified and standardised over the years has expedited the growth of digital soil-mapping techniques; hence, various machine learning algorithms are involved in predicting soil attributes. Therefore, comparing the different machine learning algorithms is essenti...

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Bibliographic Details
Main Authors: Ramalingam Kumaraperumal, Sellaperumal Pazhanivelan, Vellingiri Geethalakshmi, Moorthi Nivas Raj, Dhanaraju Muthumanickam, Ragunath Kaliaperumal, Vishnu Shankar, Athira Manikandan Nair, Manoj Kumar Yadav, Thamizh Vendan Tarun Kshatriya
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Land
Subjects:
digital soil mapping
SCORPAN
soil spatial predictions
machine learning
model comparison
Online Access:https://www.mdpi.com/2073-445X/11/12/2279

Internet

https://www.mdpi.com/2073-445X/11/12/2279

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