30 The Highest and the Deepest: the U.S. Frontier of Cave and Karst Research

Thursday, 16 May 2024
1:30 PM - 5:30 PM
Meeting Room 2

MORPHOMETRIC ANALYSIS OF APE CAVE (WA, USA) FROM A HIGH-RESOLUTION 3D MODEL BASED ON HANDHELD LIDAR IMAGING

Paper number: 30-3
Program: Theme Sessions
Time: 2:00 PM – 2:20 PM

Authors

Abstract

Over the last century, lava tubes have been extensively studied as volcanic structures which preserve important elements to understand the emplacement processes of lava flows. However, there is often a misconception in the literature regarding their inherent complexity, with their morphology tending to be oversimplified and in some cases leading to incorrect approximations.

One of the most interesting lava cave systems is located in Washington State, USA and forms part of the Cave Basalt flow, south of Mt. St. Helens. It is of particular interest as 9 km of the 14 km length corresponds to a principal lava tube system, comprising Little Red River Cave, Lake Cave, Ole's Cave and Ape Cave. This last is the best-known and, with a length of almost 3.6 km, is one of the longest intact lava caves in the USA. We scanned almost 3.5 km of Ape Cave using a high-resolution handheld LiDAR and created a detailed 3D model (5 cm mesh) from which we extracted 110 cross-sections to conduct a morphometric analysis and characterize its complexity. For each section, we determined the principal dimensions (width, height, area, perimeter) and two shape indices (aspect ratio, circular compactness) to quantitatively describe the geometry.

The results revealed variations in section width (2.83 m to 12.65 m) and height (1.91 m to 11.07 m) and while most sections showed some regularity around mean dimensions, the outliers suggest localized influences. The circular compactness (CC) of the sections revealed a diverse range of geometries from irregular (CC = 0.22) to nearly circular (CC = 0.97). In addition, aspect ratio (AR) values indicated the presence of both verticalized (AR < 1) and laterally elongated (AR > 1) geometries. Although no two sections have the same dimensions, some showed geometric similarities and thus Hierarchical and K-means clustering machine learning algorithms were used to classify them. The spatial distribution of the clusters and morphometric results clearly show the complexity of the processes forming Ape Cave and provide valuable information on the lava tube evolution as a function of distance from source. This research provides quantitative data which shows the importance of more sophisticated lava tube models, particularly when these models are used to support geophysical exploration for new lava tube systems.

Geological Society of America Abstracts with Programs. Vol. 56, No. 4

doi: 10.1130/abs/2024CD-399590

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