Results 141 to 150 of about 5,361 (218)
ABSTRACT Uncrewed underwater vehicles (UUVs) have transformed oceanographic research through autonomous data gathering. Similarly, lake and other aquatic research can potentially be automated and transformed. However, UUVs would need to be smaller, lighter, less complex, and cheaper than currently available to make them more practical and user‐friendly
James M Rand +3 more
wiley +1 more source
ABSTRACT Flow velocity measurement is fundamental to hydrological and hydraulic studies, providing essential data for streamflow estimation and river dynamics analysis. Traditional in situ methods like propeller gauges and acoustic Doppler current profilers are accurate but intrusive and labour‐intensive, while non‐intrusive image processing methods ...
Ghazaleh Nassaji Matin +4 more
wiley +1 more source
This research established a new object detection model based on YOLOv11 to recognise benthic organisms, specifically sea cucumbers, by utilising high‐resolution photogrammetric‐based orthomosaics acquired along infralittoral Mediterranean Sea beds. The model demonstrated impressive performance metrics and, when combined with the Deepness plugin for the
Gian Mario Sangiovanni +9 more
wiley +1 more source
This study presents a semi‐automated, rule‐based image analysis pipeline to detect ice seals in aerial surveys of the Western Antarctic Peninsula during an unusually low sea ice year. By using simple hierarchical clustering instead of deep learning, the method substantially reduced human annotation effort while achieving 82% recall, identifying 758 ...
Claire McGinnity +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
Accounting for animal movement during aerial imaging surveys
Animals are not stationary during aerial surveys; if their movements are related to the movement of the aerial platform, then bias can be introduced into subsequent population count estimates. We sought to establish a framework for assessing the impacts of animal movement on count error and platform bias by comparing aggregated counts and relative ...
Rowan L. Converse +5 more
wiley +1 more source
Cycles of dieback and recovery drove mangrove forest dynamics at the Albert and Leichhardt Rivers (Gulf of Carpentaria, Queensland, Australia) over 36 years (1987–2023). Landward margins were the most affected by reduced tidal inundation when the alignment of low lunar declination suppressed tidal range and extreme El Niño phases lowered mean sea level.
Rogerio Victor S. Gonçalves +4 more
wiley +1 more source
This study evaluates the performances of synchronous aerial visible (VIS) and thermal infrared (TIR) imagery for detecting great blue heron (Ardea herodias) nests and individuals using a YOLO11n model. VIS and TIR images were automatically aligned using deep learning, and both early and late fusion approaches were tested.
Camille Dionne‐Pierre +6 more
wiley +1 more source
Drones and computer vision offer an efficient way to estimate animal populations over localized areas, but surveys often require stitching many overlapping images together. If animals move during the survey, traditional orthomosaic‐based counting methods become unreliable, with some animals appearing in multiple locations while others appear not at all,
Benjamin Koger +5 more
wiley +1 more source
ABSTRACT The integration of low Earth orbit (LEO) satellite constellations with commercial aircraft communication systems presents critical challenges in maintaining continuous connectivity during dynamic flight conditions. Current geostationary satellite systems suffer from high round‐trip latency (>$$ > $$ 500 ms) and inadequate coverage at high ...
Raúl Parada +4 more
wiley +1 more source

