A Reproducible Open-Source Machine Learning Framework for Sentinel‑2 Land Use and Land Cover Classification: Comparative Analysis of Random Forest and Support Vector Machine Methods

Kumar Sarker, Pranto

The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.

Conveners will be contacted by the AGU25 Program Committee with any requests for mergers or edits to proposals. Conveners will be notified of the acceptance of their proposal in mid-June.

Abstract submissions will also open in mid-June and the deadline for abstract submissions is 30 July, 2025.

Please visit the AGU25 website for more information or please contact AGU with any questions.

Abstract: A Reproducible Open-Source Machine Learning Framework for Sentinel‑2 Land Use and Land Cover Classification: Comparative Analysis of Random Forest and Support Vector Machine Methods (AGU25)

A Reproducible Open-Source Machine Learning Framework for Sentinel‑2 Land Use and Land Cover Classification: Comparative Analysis of Random Forest and Support Vector Machine Methods

Md. Jubayer Ahamed, Pranto Kumar Sarker and Sujoy Dey, Bangladesh University of Engineering and Technology, Department of Water Resources Engineering, Dhaka, Bangladesh