Results 191 to 200 of about 14,844 (255)

Validation of a Particle Image Velocimetry Algorithm Through Comparative Field and Laboratory Analysis

open access: yesRiver Research and Applications, Volume 42, Issue 8, Page 1654-1672, October 2026.
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

Restoring Lateral Connectivity to Anthropogenic Riverscapes: Six Lessons From Stage Zero

open access: yesRiver Research and Applications, Volume 42, Issue 8, Page 1799-1817, October 2026.
ABSTRACT Centuries of river modification, particularly straightening and incision, have severely reduced lateral connectivity between rivers and their floodplains. As a result, Stage 0 riverscapes, characterised by high lateral connectivity (e.g., anastomosing or wetland riverscapes), are now rare in anthropogenic landscapes.
Richard J. Mason   +8 more
wiley   +1 more source

Intelligent identification of rock mass discontinuities based on the MK‐Means algorithm

open access: yesRiver, Volume 5, Issue 3, Page 419-431, August 2026.
Abstract Rock mass discontinuities govern the mechanical properties and engineering stability of rock masses. Conventional clustering algorithms typically require manual specification of the number of clusters or initial parameters, rendering the results sensitive to empirical judgment and initial conditions.
Wei Yang   +7 more
wiley   +1 more source

A review of the research and advancements in MSDF monitoring for the remote sensing of soil and water conservation in China

open access: yesRiver, Volume 5, Issue 3, Page 351-368, August 2026.
Abstract With the advancement of remote sensing technology, the accuracy of satellite remote sensing data has continuously improved, and the precision of large‐scale soil and water conservation monitoring has steadily increased. However, owing to differences in sensor acquisition and processing methods, monitoring data obtained through various ...
Wenxiang Liu   +4 more
wiley   +1 more source

Assessing Deep Learning Segmentation Models for Mapping Landslides From LiDAR‐Based Elevation Data

open access: yesEarth and Space Science, Volume 13, Issue 10, October 2026.
Abstract Robust landslide inventories are critical for characterizing landslide hazard and helping reduce societal vulnerability. For this study, LiDAR‐derived digital elevation models (DEMs), their derivatives, and a landslide inventory were used to train different deep learning segmentation models to assess the functionality of automatic segmentation
Hudson J. Koch   +4 more
wiley   +1 more source

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