In recent years, the automatic analysis of natural environment images acquired with
unmanned aerial vehicles (UAV) has rapidly gained popularity. UAVs are specially …

Natural forests are complex ecosystems whose tree species distribution and their ecosystem
functions are still not well understood. Sustainable management of these forests is of high …

Automatic classification of trees using remotely sensed data has been a dream of many
scientists and land use managers. Recently, Unmanned aerial vehicles (UAV) has been …

Unmanned Aerial Vehicles (UAV) are becoming an essential tool for evaluating the status
and the changes in forest ecosystems. This is especially important in Japan due to the sheer …

Tree species classification at individual tree level is a challenging problem in forest
management. Deep learning, a cutting-edge technology evolved from Artificial Intelligence …

Identifying tree species from the air has long been desired for forest management. Recently,
combination of UAV RGB image and deep learning has shown high performance for tree …

To effectively classify tree species within datasets characterized by limited samples, we
introduced a novel approach named DenseNetBL, founded upon the fusion of the DenseNet …

The classification of savanna woodland tree species from high-resolution Remotely Piloted
Aircraft Systems (RPAS) imagery is a complex and challenging task. Difficulties for both …

Aims Taxon identification is an important step in many plant ecological studies. Its efficiency
and reproducibility might greatly benefit from partly automating this task. Image-based …

Data on the distribution of tree species are often requested by forest managers, inventory
agencies, foresters as well as private and municipal forest owners. However, the automated …