Results 101 to 110 of about 48,962 (279)

Meta-analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-environmental Monitoring Using Machine Learning and Statistical Models

Remote Sensing, 2020
Unmanned Aerial Vehicle (UAV) imaging systems have recently gained significant attention from researchers and practitioners as a cost-effective means for agro-environmental applications. In particular, machine learning algorithms have been applied to UAV-
Roghieh Eskandari, Masoud Mahdianpari, Fariba Mohammadimanesh, Bahram Salehi, Brian Brisco, Saeid Homayouni   +5 more
doaj   +1 more source

Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery [PDF]

, 2019
Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time.
Baenziger, P. Stephen, Belamkar, Vikas, Bhatta, Madhav, Garst, Nicholas D., Ge, Yufeng, Howard, Reka, Li, Jiating, Li, Jiating, Stoll, Hannah, Veeranampalayam-Sivakumar, Arun-Narenthiran   +9 more
core   +1 more source

Programmed unmanned aerial vehicles show great potential for monitoring marine megafauna in specific areas of interest

Remote Sensing in Ecology and Conservation, EarlyView.
Targeted conservation measures are contingent on robust knowledge of spatio‐temporal animal distribution in areas of interest. We explore unmanned aerial vehicle (UAV) transect monitoring as a novel method for standardized digital aerial surveys of marine megafauna by investigating the fine‐resolution spatio‐temporal distribution of harbour porpoises ...
Dinah Hartmann, Valdemar Palmqvist, Johanna Stedt   +2 more
wiley   +1 more source

Assessment of seismic intensity in the Pishan earthquake extreme disaster area based on UAV images

地震科学进展, 2020
On July 3, 2015, An earthquake （MS6.5） occurred near Pishan county （37.6°N, 78.2°E）, Hotan Prefecture Xinjiang Uygur Autonomous Region, China, with a focal depth of 10 km.
Jinxiang Li, Shuo Zhao, Xiangde Chang
doaj   +1 more source

On the compatibility of single‐scan terrestrial LiDAR with digital photogrammetry and field inventory metrics of vegetation structure in forest and agroforestry landscapes

Remote Sensing in Ecology and Conservation, EarlyView.
The single‐scan approach to terrestrial laser scanning (TLS) and the self‐terrain‐normalized form of drone‐based digital aerial photogrammetry (DAP) offer practical options for rapid assessment of the vegetation structure in tropical landscapes.
Magnus Onyiriagwu, Nereoh Leley, Caleb W. T. Ngaba, Anthony Macharia, Henry Muchiri, Abdalla Kisiwa, Martin Ehbrecht, Delphine Clara Zemp   +7 more
wiley   +1 more source

Using phenology to improve invasive plant detection in fine‐scale hyperspectral drone‐based images

Remote Sensing in Ecology and Conservation, EarlyView.
Using drone‐based hyperspectral images of mixed temperate successional forests collected over a growing season, detection algorithms were produced for three invasive species of interest, which are not only invasive in Virginia but also much of the U.S.: Ailanthus altissima (tree of heaven), Elaeagnus umbellata (autumn olive), and Rhamnus davurica ...
Kelsey S. Huelsman, Howard E. Epstein, Xi Yang, Roderick Walker   +3 more
wiley   +1 more source

Modelling forest dynamics using integral projection models and repeat lidar

Remote Sensing in Ecology and Conservation, EarlyView.
Forests are facing increasing pressure from climate change and disturbance, yet linking individual tree trajectories to whole‐forest outcomes remains a major challenge. Our study integrates repeat airborne lidar with an Integral Projection Model to analyse demographic processes at the landscape scale.
Alice Rosen, Robin Battison, Christina M. Hernández, Oliver G. Spacey, Jessica McLean, Suzanne M. Prober, Samuel J. L. Gascoigne, Sean McMahon, Tommaso Jucker, Roberto Salguero‐Gómez   +9 more
wiley   +1 more source

An Improved TransMVSNet Algorithm for Three-Dimensional Reconstruction in the Unmanned Aerial Vehicle Remote Sensing Domain

Sensors
It is important to achieve the 3D reconstruction of UAV remote sensing images in deep learning-based multi-view stereo (MVS) vision. The lack of obvious texture features and detailed edges in UAV remote sensing images leads to inaccurate feature point ...
Jiawei Teng, Haijiang Sun, Peixun Liu, Shan Jiang   +3 more
doaj   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

Classification of tree species and standing dead trees in Boreal forests using UAV‐based RGB, multispectral, and LiDAR point clouds

Remote Sensing in Ecology and Conservation, EarlyView.
We evaluated single‐ and multi‐sensor UAV approaches for classifying tree species and standing dead trees in boreal forests, focusing on key biodiversity indicators such as European aspen. Using spectral and structural features extracted from RGB, multispectral (MSP), and LiDAR point clouds for 1,205 field‐measured trees, we compared classification ...
Anton Kuzmin, Lauri Korhonen, Topi Tanhuanpää, Mikko Kukkonen, Matti Maltamo, Timo Kumpula   +5 more
wiley   +1 more source