Results 201 to 210 of about 65,417 (304)

Quantification of ground surface movements on sorted circles using time‐lapse structure‐from‐motion photogrammetry in a karst cave, Slovenia

Earth Surface Processes and Landforms, Volume 51, Issue 6, June 2026.
We present ground surface movements on sorted circles in a karst cave using time‐lapse photogrammetry with accuracies of up to ±2 mm. Data with 3‐hourly resolution revealed average vertical movements of up to 50 mm and horizontal movements of up to 15 mm during individual freeze–thaw cycles.
Jaroslav Obu, Matej Blatnik, Julia Boike, Franci Gabrovšek, Luc Girod, Andreas M. Kääb, Norikazu Matsuoka, Paul P. Overduin, Mihaela Triglav Čekada, Marko Zore   +9 more
wiley   +1 more source

UAV-based mangrove biomass estimation and carbon potential valuation in North Sumatra, Indonesia. [PDF]

Carbon Balance Manag
Basyuni M, Tanjung IL, Slamet B, Ritonga FN, Al Mustaniroh SS, Larekekng SH, Arifanti VB, Iryanthony SB, Sumarga E, Baba S, Salmo Iii SG, Ginting E, Kusumawardani N, Omoto R.   +13 more
europepmc   +1 more source

Climatic, lithologic and topographic control on alpine rock fracturing and talus evolution

Earth Surface Processes and Landforms, Volume 51, Issue 6, June 2026.
Investigating Holocene rockwall–talus systems in an Alpine valley revealed that lithologic and topographic conditions in concert with climatic‐driven stresses and time since deglaciation result in rockwall fracture patterns that control rockfall size, erosion rates and the characteristics and evolution of talus.
Daniel Draebing, Sterre A. M. Brouns, Steven A. Binnie, Tjalling de Haas, Samuel T. McColl   +4 more
wiley   +1 more source

Experimental study of fluid-thermal-structural interactions in a Mach-10 compression corner using super-ellipse-based photogrammetry. [PDF]

Exp Fluids
Duchene TA, Schöneich AG, Bathel BF, Weisberger JM, Buck GM, Bodony DJ, Laurence SJ.   +6 more
europepmc   +1 more source

Optimizing Skull Base Anatomy Education: Qualitative Insights From Learner Interaction With 2D, Monoscopic 3D, and Virtual Reality Models

Laryngoscope Investigative Otolaryngology, Volume 11, Issue 3, June 2026.
ABSTRACT Objective Several models are currently employed to teach anatomy to medical students and residents, including cadaveric, two‐dimensional (2D), monoscopic three‐dimensional (3D), and virtual reality (VR) models. While many studies have focused on measuring how much and how quickly each model can help residents and medical students attain and ...
Elizabeth N. Liao, Nina W. Zhao, Kendyl Naugle, Katrin Jaradeh, Roberto Rodriguez Rubio, Ivan El‐Sayed   +5 more
wiley   +1 more source

A Case Report: Immediate Implant Placement with PRF, Photogrammetry-Guided Workflow, and Monolithic Zirconia Full-Arch Restoration. [PDF]

Reports (MDPI)
Grzesiak PB, Nowicki AA.
europepmc   +1 more source

Red, green, blue color indices as proxy for Symbiodiniaceae cell density and chlorophyll content during coral bleaching

Limnology and Oceanography: Methods, Volume 24, Issue 6, June 2026.
Abstract Coral bleaching, the breakdown of the symbiosis between the coral host and endosymbiotic microalgae, is the main cause of widespread coral reef degradation. Current visual assessment methods for coral health, including color reference cards, are constrained by subjective human color perception and limited resolution.
Erik Francesco Ferrara, Lavinia Bauer, Giulia Puntin, Friederike Bautz, Sibel Celayir, Marie‐Sa Do, Frederik Eck, Melissa Heider, Pia Wissel, Angelina Arnold, Thomas Wilke, Jessica Reichert, Maren Ziegler   +12 more
wiley   +1 more source

Smartphone-based Structure-from-Motion for the remote assessment of trunk rotation in spine deformity. [PDF]

N Am Spine Soc J
Suresh S, Suhr AE, De Gavelle De Roany P, Kok L, Morsch E, Stubbs A, Izatt MT, Labrom RD, Askin GN, Little JP.   +9 more
europepmc   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, Volume 12, Issue 3, Page 349-367, June 2026.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source