Deriving individual tree crown (ITC) information from light detection and ranging (LiDAR)
data is of great significance to forest resource assessment and smart management. After …

Automatic and accurate instance segmentation of street trees from point clouds is a
fundamental task in urban green space research. Previous studies have achieved …

In recent years, forest-fire monitoring methods represented by deep learning have been
developed rapidly. The use of drone technology and optimization of existing models to …

Mangrove forests are vulnerable ecosystems that require broad-scale monitoring. Various
solutions based on satellite imagery have emerged for this purpose but still suffer from the …

Detecting and mapping individual trees accurately and automatically from remote sensing
images is of great significance for precision forest management. Many algorithms, including …

Forested environments feature a highly complex radiation regime, and solar radiation is
hindered from penetrating into the forest by the 3D canopy structure; hence, canopy …

The continuous and extensive pinewood nematode disease has seriously threatened the
sustainable development of forestry in China. At present, many studies have used high …

Unmanned aerial vehicles (UAVs) are widely used for small target detection of forest fires
due to its low-risk rate, low cost and high ground coverage. However, the detection accuracy …

This study evaluates the skills of two types of drone-based point clouds, derived from LiDAR
and photogrammetric techniques, in estimating ground elevation, vegetation height, and …

Light detection and ranging (LiDAR) data can provide 3D structural information of objects
and are ideal for extracting individual tree parameters, and individual tree segmentation …