Estimating Forest Aboveground Biomass Density Using Remote Sensing and Machine Learning : A RSME Approach

An accurate estimation of aboveground biomass (AGB) density is essential for effective forest management, carbon stock monitoring, and informed land management decisions. This study employs remote sensing datasets and collaborative efforts with ArcGIS to model AGB density across the Terengganu regio...

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Bibliographic Details

Main Authors:	Yaniza Shaira, Zakaria, Mohd Fadzil, Akhir, Aidy, M Muslim, Nur Afiqah, Ariffin, Azizul, Ahmad
Format:	Article
Language:	en
Published:	John Wiley & Sons Ltd. 2025
Subjects:	G Geography (General) GA Mathematical geography. Cartography GB Physical geography GE Environmental Sciences
Online Access:	http://ir.unimas.my/id/eprint/48892/3/Estimating%20Forest.pdf http://ir.unimas.my/id/eprint/48892/ https://onlinelibrary.wiley.com/doi/10.1002/ldr.70087 https://doi.org/10.1002/ldr.70087
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