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View article: Comparing Terrestrial and Mobile Laser Scanning Approaches for Multi-Layer Fuel Load Prediction in the Western United States
Comparing Terrestrial and Mobile Laser Scanning Approaches for Multi-Layer Fuel Load Prediction in the Western United States Open
Effective estimation of fuel load is critical for mitigating wildfire risks. Here, we evaluate the performance of mobile laser scanning (MLS) and terrestrial laser scanning (TLS) to estimate fuel loads across multiple vegetation layers. Da…
View article: Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida
Aboveground biomass density maps for post-hurricane Ian forest monitoring in Florida Open
Hurricane Ian caused aboveground biomass density (AGBD) losses across Florida's forests in the United States, highlighting the need for accurate, large-scale monitoring tools. We combined Global Ecosystem Dynamics Investigation (GEDI) LiDA…
View article: Spatial Characterization of Woody Species Diversity in Tropical Savannas Using GEDI and Optical Data
Spatial Characterization of Woody Species Diversity in Tropical Savannas Using GEDI and Optical Data Open
Developing the capacity to monitor species diversity worldwide is of great importance in halting biodiversity loss. To this end, remote sensing plays a unique role. In this study, we evaluate the potential of Global Ecosystem Dynamics Inve…
View article: Machine Learning-driven Fusion of NASA’s ICESat-2 and Landsat 8 OLI Data for Assessing Forest Recovery Following Hurricane Disturbance in Southern Forests
Machine Learning-driven Fusion of NASA’s ICESat-2 and Landsat 8 OLI Data for Assessing Forest Recovery Following Hurricane Disturbance in Southern Forests Open
The Southern U.S. hosts some of the most productive forests globally, playing a crucial role in the U.S. terrestrial carbon sink and contributing significantly to timber production (over 60% in commercial terms). Despite their importance, …
View article: Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning
Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning Open
Natural disturbances like hurricanes can cause extensive disorder in forest structure, composition, and succession. Consequently, ecological, social, and economic alterations may occur. Terrestrial laser scanning (TLS) and deep learning ha…
View article: <scp>treetop</scp> : A Shiny‐based application and R package for extracting forest information from <scp>LiDAR</scp> data for ecologists and conservationists
<span>treetop</span> : A Shiny‐based application and R package for extracting forest information from <span>LiDAR</span> data for ecologists and conservationists Open
Individual tree detection (ITD) and crown delineation are two of the most relevant methods for extracting detailed and reliable forest information from LiDAR (Light Detection and Ranging) datasets. However, advanced computational skills an…