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Integrating multi-source remote sensing data with field-based national forest inventory (NFI) measurements to model and monitor forest structural dynamics

Domain:

geospatialenvironment and energy

Record type:

dataset
Creator:
The
Host:avatar

National forest inventory (NFI) dataset underpinning MSc dissertation titled "Mapping tree canopy height and aboveground biomass in the Kavango region using multi-scale remote sensing data." This study addressed challenges by integrating multi-source remote sensing data with field-based National forest inventory (NFI) measurements to model and monitor forest structural dynamics in the Kavango Region of northern Namibia in 2015, 2018, 2021 and 2024. The study combined spaceborne LiDAR data from NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission with Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical imagery to estimate TCH and AGB across the Hamoye State Forest and three surrounding community forests. GEDI-derived canopy metrics (RH95–RH100) were validated using field data, with RH98 showing the strongest correlation (R² = 0.412).


Tasks

computer vision

Tags

Conservation and biodiversityNatural resource managementWoodlandsDry forestsAboveground biomassTree canopy heightNational forest inventory (NFI) measurementsForest structural dynamicsMulti-source remote sensingGlobal ecosystem dynamics investigation (GEDI) L2A+1

Licenses

CC BY 4.0

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