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Enhancing the Precision of Forest Growing Stock Volume in the Estonian National Forest Inventory with Different Predictive Techniques and Remote Sensing Data

Estimating forest growing stock volume (GSV) is crucial for forest growth and resource management, as it reflects forest productivity. National measurements are laborious and costly; however, integrating satellite data such as optical, Synthetic Aperture Radar (SAR), and airborne laser scanning (ALS...

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Principais autores: Temitope Olaoluwa Omoniyi, Allan Sims
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-10-01
Serier:Remote Sensing
Fag:
National Forest Inventory
growing stock volume
remote sensing
Sentinel-2
airborne laser scanning
machine learning
Online adgang:https://www.mdpi.com/2072-4292/16/20/3794
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