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Prof Neil Entwistle's Outputs (5)

Evidence of non-contiguous flood driven coarse sediment transfer and implications for sediment management (2019)
Presentation / Conference
Heritage, G., Entwistle, N., & Milan, D. (2019, September). Evidence of non-contiguous flood driven coarse sediment transfer and implications for sediment management. Presented at 38th IAHR World Congress, Panama City, Panama

We investigate gravel redistribution and morphological response of three headwater streams following the Storm
Desmond floods of December 2015. Reactive management of the watercourses following the flooding
concentrated on removal of gravel and cle... Read More about Evidence of non-contiguous flood driven coarse sediment transfer and implications for sediment management.

Small unmanned aerial model accuracy for photogrammetrical fluvial bathymetric survey (2019)
Journal Article
Entwistle, N., & Heritage, G. (2019). Small unmanned aerial model accuracy for photogrammetrical fluvial bathymetric survey. Journal of Applied Remote Sensing, 13(1), 014523. https://doi.org/10.1117/1.JRS.13.014523

Fluvial systems offer a challenging and varied environment for topographic survey, displaying a rapidly varying morphology, vegetation assemblage and degree of submergence. Traditionally theodolite or GPS based systems have been used to capture cross... Read More about Small unmanned aerial model accuracy for photogrammetrical fluvial bathymetric survey.

Multi-Scale detection, mapping, and modelling geomorphic change in gravel-bed rivers with UAV remote sensing (2019)
Thesis
Scott, R. Multi-Scale detection, mapping, and modelling geomorphic change in gravel-bed rivers with UAV remote sensing. (Thesis). University of Salford

Fluvial science is in particular need of surveying tools which can rapidly and accurately capture topographic data. The use of low-cost, consumer grade UAV (unmanned aerial vehicle) systems and Structure from Motion (SfM) processing methods has seen... Read More about Multi-Scale detection, mapping, and modelling geomorphic change in gravel-bed rivers with UAV remote sensing.