Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine

Improved mapping of highland bamboo forests using Sentinel-2 time series and machine learning in Google Earth Engine

Recent advances in the application of spectral bands from satellite observations and machine learning algorithms (MLA) in the Google Earth Engine (GEE) cloud-computing platform have been demonstrated to enhance the accuracy of mapping forest resources. This study presents a novel method for mapping...

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Bibliographic Details
Main Authors: Dagnew Yebeyen, Binyam Tesfaw Hailu, Worku Zewdie, Temesgen Abera, Gudeta W. Sileshi, Melaku Getachew, Sileshi Nemomissa
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Geocarto International
Subjects:
Afromontane forests
cloud computing
Oldeania alpina
land cover classification
machine learning
remote sensing
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2024.2364680
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https://www.tandfonline.com/doi/10.1080/10106049.2024.2364680

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