Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …

The ability to use digital remotely sensed data for forest inventory is often limited by the
nature of the measures, which, with the exception of multi-angular or stereo observations …

This study investigates the potential of unmanned aerial vehicles (UAVs) to measure and
monitor structural properties of forests. Two remote sensing techniques, airborne laser …

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission
which will produce near global (51.6° S to 51.6° N) maps of forest structure and above …

Laser scanning from different acquisition platforms enables the collection of 3D point clouds
from different perspectives and with varying resolutions. These point clouds allow us to …

The high dimensionality of data generated by Unmanned Aerial Vehicle (UAV)-Lidar makes
it difficult to use classical statistical techniques to design accurate predictive models from …

Topographic laser scanning is a remote sensing method to create detailed 3D point cloud
representations of the Earth's surface. Since data acquisition is expensive, simulations can …

This paper presents a method for fitting cylinders into a point cloud, derived from a terrestrial
laser-scanned tree. Utilizing high scan quality data as the input, the resulting models …

Remote sensing (RS) studies aiming at map** forest biomass typically rely on ground-
based estimates of biomass for calibration or validation. Whatever the biophysical variable …

Spatially-explicit information on forest structure is paramount to estimating aboveground
carbon stocks for designing sustainable forest management strategies and mitigating …