Results 191 to 200 of about 834,631 (325)
VINA-SLAM: A Voxel-Based Inertial and Normal-Aligned LiDAR-IMU SLAM. [PDF]
Zhang R, Sun B.
europepmc +1 more source
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 +10 more
wiley +1 more source
Temperate fens with only incipient, subtle signs of deterioration can be reliably identified using Sentinel‐2 and aerial imagery, which sensitively detect early productivity‐related structural changes. Abstract Small temperate fens rank among the most endangered habitats in temperate Europe.
Lubomír Tichý +9 more
wiley +1 more source
A review of SPAD array chip design for direct time-of-flight LiDAR. [PDF]
Mo L, Huang S, Yang Y, Ren TL.
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
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
Targetless LiDAR-camera extrinsic calibration via semantic distribution alignment. [PDF]
Chen X, Sun B.
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 photogrammetry and lidar integration for high-fidelity 3D campus mapping at KFUPM. [PDF]
Keshk HM +3 more
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

