Review of remote sensing-based methods for forest aboveground biomass estimation: Progress, challenges, and prospects
Quantifying forest aboveground biomass (AGB) is essential for elucidating the global carbon
cycle and the response of forest ecosystems to climate change. Over the past five decades …
cycle and the response of forest ecosystems to climate change. Over the past five decades …
Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms
Y Li, M Li, C Li, Z Liu - Scientific reports, 2020 - nature.com
Forest aboveground biomass (AGB) plays an important role in the study of the carbon cycle
and climate change in the global terrestrial ecosystem. AGB estimation based on remote …
and climate change in the global terrestrial ecosystem. AGB estimation based on remote …
[HTML][HTML] Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the …
Accurately estimating aboveground biomass (AGB) in forest ecosystems facilitates efficient
resource management, carbon accounting, and conservation efforts. This study examines …
resource management, carbon accounting, and conservation efforts. This study examines …
Aboveground mangrove biomass estimation in Beibu Gulf using machine learning and UAV remote sensing
On the basis of canopy height variables, vegetation index, texture index, and laser point
cloud index measured with unmanned aerial vehicle (UAV) low altitude remote sensing, we …
cloud index measured with unmanned aerial vehicle (UAV) low altitude remote sensing, we …
Improved estimation of aboveground biomass in wheat from RGB imagery and point cloud data acquired with a low-cost unmanned aerial vehicle system
Background Aboveground biomass (AGB) is a widely used agronomic parameter for
characterizing crop growth status and predicting grain yield. The rapid and accurate …
characterizing crop growth status and predicting grain yield. The rapid and accurate …
An evaluation of eight machine learning regression algorithms for forest aboveground biomass estimation from multiple satellite data products
Y Zhang, J Ma, S Liang, X Li, M Li - Remote sensing, 2020 - mdpi.com
This study provided a comprehensive evaluation of eight machine learning regression
algorithms for forest aboveground biomass (AGB) estimation from satellite data based on …
algorithms for forest aboveground biomass (AGB) estimation from satellite data based on …
Influence of variable selection and forest type on forest aboveground biomass estimation using machine learning algorithms
Y Li, C Li, M Li, Z Liu - Forests, 2019 - mdpi.com
Forest biomass is a major store of carbon and plays a crucial role in the regional and global
carbon cycle. Accurate forest biomass assessment is important for monitoring and mapping …
carbon cycle. Accurate forest biomass assessment is important for monitoring and mapping …
Estimation of forest above-ground biomass by geographically weighted regression and machine learning with sentinel imagery
Accurate forest above-ground biomass (AGB) is crucial for sustaining forest management
and mitigating climate change to support REDD+ (reducing emissions from deforestation …
and mitigating climate change to support REDD+ (reducing emissions from deforestation …
Aboveground biomass and carbon stock estimation using UAV photogrammetry in Indonesian mangroves and other competing land uses
Mangrove ecosystem is one of coastal wetlands that have experienced significant
anthropogenic driven degradation and conversion, which have resulted in substantial …
anthropogenic driven degradation and conversion, which have resulted in substantial …
A brief overview and perspective of using airborne Lidar data for forest biomass estimation
Lidar data have been regarded as the most important data source for accurate forest
biomass estimation. Different platforms such as terrestrial Laser scanning, unmanned aerial …
biomass estimation. Different platforms such as terrestrial Laser scanning, unmanned aerial …