Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning

European spruce bark beetle ( Ips typographus, L.) green attack affects foliar reflectance and biochemical properties

(2018) Haidi Abdullah et al.   International Journal of Applied Earth Observation and Geoinformation

Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

(2018) Roope Näsi et al.   URBAN FORESTRY & URBAN GREENING

Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data

(2017) Nataliia Kussul et al.   IEEE Geoscience and Remote Sensing Letters

A snapshot of image pre-processing for convolutional neural networks: case study of MNIST

(2017) Siham Tabik et al.   International Journal of Computational Intelligence Systems

Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

(2017) Jonathan P. Dash et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest

(2017) Midhun Mohan et al.   Forests

Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study

(2017) Emilio Guirado et al.   Remote Sensing

Plant species classification using deep convolutional neural network

(2016) Mads Dyrmann et al.   BIOSYSTEMS ENGINEERING

Regional atmospheric cooling and wetting effect of permafrost thaw-induced boreal forest loss

(2016) Manuel Helbig et al.   GLOBAL CHANGE BIOLOGY

Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images

(2016) Weijia Li et al.   Remote Sensing

Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

(2016) Martin Längkvist et al.   Remote Sensing

Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

(2015) Jan Lehmann et al.   Forests

Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level

(2015) Roope Näsi et al.   Remote Sensing

Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality

(2014) Lars Waser et al.   Remote Sensing

Evaluating methods to detect bark beetle-caused tree mortality using single-date and multi-date Landsat imagery

(2013) Arjan J.H. Meddens et al.   REMOTE SENSING OF ENVIRONMENT

High-Resolution Global Maps of 21st-Century Forest Cover Change

(2013) M. C. Hansen et al.   SCIENCE

Early Detection of Bark Beetle Green Attack Using TerraSAR-X and RapidEye Data

(2013) Sonia Ortiz et al.   Remote Sensing

Object-orientated image analysis for the semi-automatic detection of dead trees following a spruce bark beetle (Ips typographus) outbreak

(2009) Marco Heurich et al.   EUROPEAN JOURNAL OF FOREST RESEARCH

Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests

(2008) G. B. Bonan   SCIENCE