32 D28. Volcanology

Monday, 26 October 2020
5:30 PM - 8:00 PM
Meeting Rooms

RECOGNIZING AND QUANTIFYING DIAGNOSTIC MORPHOMETRIC PARAMETERS FOR THE REMOTE IDENTIFICATION OF SMALL VOLUME VOLCANIC LANDFORMS AND RELATED FEATURES

Paper number: 32-3
Program: Technical Sessions
Time: 6:00 PM – 6:15 PM

Authors

Abstract

Remote identification of volcanic features requires the analysis of morphometric parameters. Leveraging UAV photogrammetry, OpenTopography LiDAR, and ArcticDEM datasets 71 small volume monogenetic volcanic landforms were classified. Features include maars, collapse pits, fissure/spatter ramparts, and tuff rings/cones. Features were limited to >1 km3 for scoria cones, tuff rings/cones, and fissure/spatter ramparts, and a major axis of 1250 m or less for collapse and maars. To date 13 maars with diameters 71 - 1153 m, 37 collapse features with diameters 17 - 140 m, and 11 fissure/spatter ramparts 6 - 70 m in diameter have been analyzed for 2-D, 3-D and dimensionless morphometric parameters. An additional 10 eruptive features were classified as compound and will be compared with recognized classes. Scoria cones and tuff cones/rings were classified for future quantification. 2-D parameters include but are not limited to, major/minor axis length and azimuth, area, perimeter, circularity. 3-D parameters include slope angles, minimum and maximum elevations, and slope profiles. An individual parameter will not be diagnostic for recognizing feature types remotely, but it is expected that a suite of parameters will be. Diagnostic parameters for individual features include: raised rims with a crater that cuts below pre-existing topography with internal slopes of 14-27˚ for maars, rimless craters that cut below pre-existing topography and internal slopes of close to 90˚ for collapse features, steep rims with steep sided craters that cut into pre-existing topography for spatter ramparts. This data is being compiled into a terrestrial volcanic landform database, Small-volume Monogenetic Igneous Landforms and Edifices Statistics (SMILES), under development to enable accurate and positive remote identification of volcanic features, both terrestrial and non-terrestrial.

Geological Society of America Abstracts with Programs. Vol. 52, No. 6

doi: 10.1130/abs/2020AM-356423

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