Results 171 to 180 of about 200,823 (294)
Impact of UK Weather on Autonomous Vehicle Radar, LiDAR and Camera Vision Systems. [PDF]
Smith J +18 more
europepmc +1 more source
Imaging spectroscopy enables large‐scale biodiversity assessment, yet spectral diversity metrics are scale dependent. Across 15 NEON ecosystems, we find that spectral richness increases sub‐linearly from 3600 m2 to 4 km2, whereas spectral divergence shows weak or inconsistent scaling with area, underscoring the importance of scale‐aware interpretation ...
Meghan T. Hayden +8 more
wiley +1 more source
Master Mix Localization Algorithm for Autonomous Systems in Indoor Environments. [PDF]
Ezzouine Z +5 more
europepmc +1 more source
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 +5 more
wiley +1 more source
A Hybrid Frequency Estimation Framework for Long-Range FMCW LiDAR Under Low-SNR Conditions. [PDF]
Fang Y +6 more
europepmc +1 more source
Ground‐based robotic remote sensing for standardized biodiversity monitoring in coastal habitats
Illustrated workflow of the proposed citizen‐to‐robot monitoring pipeline: (i) expert‐validated citizen observations are translated into AI models, (ii) deployed on a ground‐based robotic platform for proximal sensing of coastal dune habitats, (iii) enabling standardized detection of ecological targets (e.g., Pancratium maritimum & Brithys crini), and (
Giovanni Di Lorenzo +5 more
wiley +1 more source
UAV LiDAR point cloud and ground measurement dataset for assessing the impact of flight parameters over a poplar plantation. [PDF]
Baup F, Battista C, Frappart F.
europepmc +1 more source
High‐resolution visible‐light imagery from low‐altitude unmanned aerial vehicles, combined with superpixel segmentation and a Random Forest classifier, provides an efficient and scalable framework for mapping and monitoring crustose coralline algae and reef habitats.
Po‐Chien Lin +2 more
wiley +1 more source

