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• W2912703139 abstract "Dykes play a major role in transporting magma through the crust to subsurface storage reservoirs or eruption sites at the surface. The geometry, connectivity, and internal textures of dykes preserve an important record of dyke emplacement, linkage, and magma flow dynamics. Unravelling these facets of dyke evolution is critical to interpreting signals of magma migration in active volcanoes as well as tectonic processes, including crust formation and continental break-up during hazard assessment. Unfortunately, our ability to develop new insights is limited by the continuity of high precision data that can be extracted from the field. The emergence of Unmanned Aerial Vehicles (UAVs, a.k.a. drones), photogrammetry and other sensor techniques are set to greatly improve our field capabilities by collecting data at higher density and with greater precision. Here we present a workflow emphasising best-practise in UAV survey design, the construction of photogrammetric models and standardised reporting of those models. Emphasis is given to the factors that should be considered in order to resolve the geological features of interest in any study (e.g. wall rock fractures, chilled margins, magmatic breccias, dyke apertures etc.). A point-to-raster technique is documented that measures spatial error in the rasters that are derived from photogrammetric models (e.g. orthomosaics and digital elevation models). Using three case studies, we show how dyke swarms can be mapped accurately over areas approaching 1 km2, at sub-centimetre resolution. The data illustrate how questions about dyke-induced deformation, host rock controls on segmentation and aperture variation may be addressed, and we present a method for the high density, high precision measurement of dyke apertures in 3D. We also review semi-automated mapping tools and emerging UAV sensing techniques, including hyperspectral and aeromagnetic sensors, and the potentially important contributions they will make to the study of intrusive systems and volcanology more broadly." @default.
• W2912703139 created "2019-02-21" @default.
• W2912703139 creator A5014435568 @default.
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• W2912703139 date "2019-03-01" @default.
• W2912703139 modified "2023-10-06" @default.
• W2912703139 title "Review of drones, photogrammetry and emerging sensor technology for the study of dykes: Best practises and future potential" @default.
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• W2912703139 doi "https://doi.org/10.1016/j.jvolgeores.2019.01.018" @default.
• W2912703139 hasPublicationYear "2019" @default.
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