Automated individual tree crown detection and delineation (ITCD) using remotely sensed
data plays an increasingly significant role in efficiently, accurately, and completely …

Individual mangrove tree parameters are necessary for the efficient management and
protection of this unique ecosystem, but to measure them using remote sensing (RS) is still a …

Using unmanned aerial vehicles (UAV) as platforms for light detection and ranging (LiDAR)
sensors offers the efficient operation and advantages of active remote sensing; hence, UAV …

Individual tree crown detection and delineation (ITCD) mainly depend on high-resolution
aerial photos and satellite images or LiDAR, and these data can be costly to obtain. The …

Tree counts and sizes are important information to apply to crop yield estimation and
agricultural planning. Therefore, obtaining automatic extraction of trees, their locations …

Accurate tree species classification is essential for forest resource management and
biodiversity assessment. However, classifying tree species becomes challenging in natural …

Individual tree crown delineation is of great importance for forest inventory and
management. The increasing availability of high-resolution airborne light detection and …

The ability to automatically delineate individual tree crowns using remote sensing data
opens the possibility to collect detailed tree information over large geographic regions …

Use of 3D sensors in plant phenotyping has increased in the last few years. Various image
acquisition, 3D representations, 3D model processing and analysis techniques exist to help …

This study provides a novel approach to individual tree crown delineation (ITCD) using
airborne Light Detection and Ranging (LiDAR) data in dense natural forests using two main …