Deep learning, which has exhibited considerable potential and effectiveness in forest
resource assessment, is vital for comprehending and managing forest resources and …

This paper provides a comprehensive literature review on forest aboveground biomass
(AGB) estimation and map** through high-resolution optical satellite imagery (≤ 5 m …

Abstract Changes in soil carbon (C) pools driven by fire in forest ecosystems remain
equivocal, especially at a global scale. In this study we analyzed data from 232 studies …

Accurate assessment of above-ground biomass (AGB) is important for the sustainable
management of forests, especially buffer zone (areas within the protected area, where …

The use of light detection and ranging (LiDAR) techniques for recording and analyzing tree
and forest structural variables shows strong promise for improving established hyperspectral …

Parameters of individual trees can be measured from LiDAR data provided that the laser
points are dense enough to distinguish tree crowns. Retrieving tree parameters for above …

Accurately characterizing carbon stock is vital for reporting carbon emissions from forest
ecosystems. We studied the estimation of biomass using Sentinel-2 remote sensing data in …

Remote sensing (RS) data are often used as a complementary data source to acquire
accurate quantitative estimations of merchantable volume (V) and carbon stock in living …

Tropical forest embraces a large stock of carbon and contributes to the enormous amount of
above-and below-ground biomass and the global carbon cycle. The carbon kept in the …

Crop Leaf area index (LAI), canopy height and above-ground biomass (AGB) are important
structural parameters. Accurate predictions of these three parameters are required for …