Results 91 to 100 of about 5,043 (250)

Using Deep Learning AI to Detect Riparian Vegetation Recovery Following a Major Flood in the Brisbane River

River Research and Applications, EarlyView.
ABSTRACT Post‐flood riparian vegetation recovery demands significant attention; however, the complexity of traditional remote sensing methods often hinders environmental managers from implementing rapid vegetation monitoring. This paper developed a model using a Deep Learning Model within ArcGIS to classify and detect recovery of vegetation with high ...
Sydney O'Hare, Jinghan Li, Yongping Wei
wiley   +1 more source

Knee height is often right: evaluating device height effects on camera trapping rate

Remote Sensing in Ecology and Conservation, EarlyView.
Camera trap deployment height can introduce systematic biases in detection trapping rates across species of different body sizes. Combining 172 paired sampling points in five experiments across Europe, North America and Africa, our results show that low cameras significantly increase detections of small‐ and medium‐sized species, whereas high cameras ...
Jorge Sereno‐Cadierno, Tim R. Hofmeester, Marcus Becker, Alice Bernard, Lizette Moolman, Hervé Fritz, Pelayo Acevedo   +6 more
wiley   +1 more source

Semi‐automated seal detection on the Western Antarctic Peninsula: an unsupervised machine learning approach for detecting ice seals in aerial survey data

Remote Sensing in Ecology and Conservation, EarlyView.
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, Connor C.G. Bamford, Nathan Fenney, Andrew Fleming, Jaume Forcada, Michael S. Tift, Luis A. Hückstädt, Daniel P. Costa, Peter T. Fretwell   +8 more
wiley   +1 more source

Monitoring feral pigs (Sus scrofa): Complementarity between autonomous sensing methods increases detection probability

Remote Sensing in Ecology and Conservation, EarlyView.
Invasive alien species are a major threat for biodiversity worldwide and effective monitoring is paramount to inform management. In this study we used a multi‐season occupancy model to assess probability of detection between camera traps and passive acoustic recorders for feral pigs (Sus scrofa) during 1 year of data collection.
Marina D. A. Scarpelli, Stewart Macdonald, Maryam Golchin, Simon Linke, Jens G. Froese   +4 more
wiley   +1 more source

Historical remote sensing highlights long‐term persistence of Emperor Penguin (Aptenodytes forsteri) colonies

Remote Sensing in Ecology and Conservation, EarlyView.
Remote sensing can reveal population dynamics of Antarctic penguin colonies. In this study, we analyze emperor penguin (Aptenodytes forsteri) guano stains in remote sensing imagery and discover colony presence predating known records for 18 colonies across Antarctica.
Martynas Bielinis, Michelle LaRue, Benjamin M. Kraemer, Catalina Munteanu   +3 more
wiley   +1 more source

Habitat selection and abundance of common genets using camera capture-mark-recapture data

, 2009
Using camera-trapping techniques, the present study, conducted from 2005 to 2007, provides common genet abundance estimates in Serra da Malcata Nature Reserve (central-eastern Portugal). We estimated genet abundance using the software CAPTURE. It was possible to obtain a capture success of 1.49 captures/100 trap-nights.
Sarmento, Pedro Bernardo, Cruz, Joana P., Eira, Catarina I., Fonseca, Carlos   +3 more
openaire   +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

Inferring Brown Bear Hair Snare Interactions by Automatically Detecting Bipedalism on Camera Trap Images Using Pose Estimation and a Multilayer Perceptron

Remote Sensing in Ecology and Conservation, EarlyView.
This study proposes an automated method to infer brown bear hair snare interactions by detecting bipedal behavior in camera‐trap images using a pose estimation model and a multilayer perceptron (MLP). A YOLO‐based model, fine‐tuned from humans and dogs to a custom dataset, achieved high performance (≈93% keypoint precision and ≈96% classification ...
Arnau Campanera‐Moliné, Víctor Sazatornil, Lluís Brotons, Felipe Lumbreras Ruiz, Robert Benavente, Maguiña Ramilo‐Henry, Cristina Ramos, Santiago Palazón, Daniel Ponsa   +8 more
wiley   +1 more source

Genotyping validates the efficacy of photographic identification in a capture-mark-recapture study based on the head scale patterns of the prairie lizard (Sceloporus consobrinus). [PDF]

Ecol Evol, 2020
Tomke SA, Kellner CJ.
europepmc   +1 more source

A Comparison of Mobile Laser Scanning Data Acquisition Methods in Closed Forest, Open Woodland and Sub‐Alpine Woodland Ecosystems

Remote Sensing in Ecology and Conservation, EarlyView.
This study demonstrates that the mobile laser scanning (MLS) sampling density required to reliably characterise vegetation structure increases with a site's structural complexity. Applying a five‐level acquisition framework across open woodland, closed forest and sub‐alpine woodland ecosystems, we found that longer scanning paths increased the ...
Johann Tiede, Karin Reinke, Trung H. Nguyen, Simon Jones   +3 more
wiley   +1 more source