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 …
UAV-based forest health monitoring: A systematic review
In recent years, technological advances have led to the increasing use of unmanned aerial
vehicles (UAVs) for forestry applications. One emerging field for drone application is forest …
vehicles (UAVs) for forestry applications. One emerging field for drone application is forest …
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 …
Explainable identification and mapping of trees using UAV RGB image and deep learning
M Onishi, T Ise - Scientific reports, 2021 - nature.com
The identification and mapping of trees via remotely sensed data for application in forest
management is an active area of research. Previously proposed methods using airborne …
management is an active area of research. Previously proposed methods using airborne …
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 …
Surveying coconut trees using high-resolution satellite imagery in remote atolls of the Pacific Ocean
Coconut (Cocos nucifera L.) is one of the world's most economically important tree species,
and coconut palm plantations dominate many islands and tropical coastlines. However, the …
and coconut palm plantations dominate many islands and tropical coastlines. However, the …
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 …
Tree species classification of drone hyperspectral and RGB imagery with deep learning convolutional neural networks
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be
captured flexibly and at high spatial and temporal resolutions when needed. In forestry …
captured flexibly and at high spatial and temporal resolutions when needed. In forestry …
A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery
Visual inspection has been a common practice to determine the number of plants in
orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms …
orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms …