Good surface water quality is critical to human health and ecology. Land use determines the
surface water heat and material balance, which cause climate change and affect water …

Tree biomass is typically estimated using statistical models. This review highlights five
limitations of most tree biomass models, which include the following:(1) biomass data are …

Abstract Knowledge on forest structure is vital for sustainable forest management decisions.
Currently, Airborne Laser Scanning (ALS) has been well established as an effective tool to …

Gathering information about forest variables is an expensive and arduous activity. As such,
directly collecting the data required to produce high-resolution maps over large spatial …

Lidar provides critical information on the three-dimensional structure of forests. However,
collecting wall-to-wall laser altimetry data at regional and global scales is cost prohibitive. As …

Forest canopy height is an essential parameter in estimating forest aboveground biomass
(AGB), growing stock volume (GSV), and carbon storage, and it can provide necessary …

Many studies and production inventory systems have shown the utility of coupling covariates
derived from Light Detection and Ranging (LiDAR) data with forest variables measured on …

We develop and present a novel Bayesian hierarchical geostatistical model for the
prediction of plantation forest carbon stock (C stock) in the eastern highlands of Zimbabwe …

Combining spatially-explicit long-term forest inventory and remotely sensed information from
Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful …

Spectral, temporal and spatial dimensions are difficult to model together when predicting in
situ plant traits from remote sensing data. Therefore, machine learning algorithms solely …