Bare ground classification using a spectral index ensemble and machine learning models optimized across 12 international study sites

Bare ground classification using a spectral index ensemble and machine learning models optimized across 12 international study sites

This research investigates a global approach to map bare ground across diverse geographies with an ensemble of spectral indices using optimal thresholds identified in testing to train and evaluate machine learning models to extract bare ground pixels from Sentinel-2 imagery. Twelve locations in four...

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Bibliographic Details
Main Authors: Sarah J. Becker, Megan C. Maloney, Andrew W. H. Griffin, Kristofer Lasko, Heather S. Sussman
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Geocarto International
Subjects:
Bare ground classification
random forest
support vector machine
spectral index thresholds
texture
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2025.2465452
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https://www.tandfonline.com/doi/10.1080/10106049.2025.2465452

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