Review on Convolutional Neural Networks (CNN) in vegetation remote sensing
Identifying and characterizing vascular plants in time and space is required in various
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …
disciplines, eg in forestry, conservation and agriculture. Remote sensing emerged as a key …
Deep learning techniques to classify agricultural crops through UAV imagery: A review
During the last few years, Unmanned Aerial Vehicles (UAVs) technologies are widely used
to improve agriculture productivity while reducing drudgery, inspection time, and crop …
to improve agriculture productivity while reducing drudgery, inspection time, and crop …
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks
The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-
flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods …
flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods …
Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN)
Z Hao, L Lin, CJ Post, EA Mikhailova, M Li… - ISPRS Journal of …, 2021 - Elsevier
Tree-crown and height are primary tree measurements in forest inventory. Convolutional
neural networks (CNNs) are a class of neural networks, which can be used in forest …
neural networks (CNNs) are a class of neural networks, which can be used in forest …
Object detection and image segmentation with deep learning on Earth observation data: A review—Part II: Applications
In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …
investigating aggregated classes. The increase in data with a very high spatial resolution …
Current practices in UAS-based environmental monitoring
With the increasing role that unmanned aerial systems (UAS) are playing in data collection
for environmental studies, two key challenges relate to harmonizing and providing …
for environmental studies, two key challenges relate to harmonizing and providing …
Deep learning in forestry using uav-acquired rgb data: A practical review
Forests are the planet's main CO 2 filtering agent as well as important economical,
environmental and social assets. Climate change is exerting an increased stress, resulting …
environmental and social assets. Climate change is exerting an increased stress, resulting …
Individual tree crown segmentation and crown width extraction from a heightmap derived from aerial laser scanning data using a deep learning framework
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 …
data is of great significance to forest resource assessment and smart management. After …
Machine learning for landslides prevention: a survey
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …
severely destructive outcomes to human life and the overall economic system. To reduce its …
[HTML][HTML] Spatially autocorrelated training and validation samples inflate performance assessment of convolutional neural networks
Deep learning and particularly Convolutional Neural Networks (CNN) in concert with remote
sensing are becoming standard analytical tools in the geosciences. A series of studies has …
sensing are becoming standard analytical tools in the geosciences. A series of studies has …