Monitoring Volcanic and Tectonic Sandbox Analogue Models Using the Kinect v2 Sensor

Abstract

The measurement of surface deformation in analogue models of volcanic and tectonic processes is an area in continuous development. Properly quantifying topography change in analogue models is key for a useful comparison between experiment results and nature. The aim of this work is to evaluate the capabilities of the simple and cheap Microsoft® Kinect v2 sensor for monitoring analogue models made of granular materials. Microsoft® Kinect v2 is a video‐gaming RedGreenBlue‐Depth device combining an optical camera and an infrared distance measurement sensor. The precision of the device for model topography measurements has been quantified using 64 experiments, with variable granular materials materials and distance to the model. Additionally, we tested the capabilities of averaging several distance images to increase the precision. We have developed a specific software to facilitate the acquisition and processing of the Kinect v2 data in experiment monitoring. Our results show that measurement precision is material dependent: with clear‐colored and fine‐grained materials, a precision ∼1.0 mm for digital elevation models with a 1.6 mm pixel size can be obtained. We show that by averaging ≥5 consecutive images the distance precision can reach values as low as 0.5 mm. To show the Kinect v2 capabilities, we present monitoring results from case study experiments modeling tectonics and volcano deformation. The Kinect v2 achieves lower spatial resolutions and precision than more sophisticated techniques such as photogrammetry. However, Kinect v2 provides a cheap, straightforward and powerful tool for monitoring the topography changes in sandbox analogue models.

Morpho-structural criteria for the identification of spreading-induced deformation processes potentially compromising stratovolcano stability

“…Experiments were recorded monitored using the visible and distance images obtained by Microsoft®'s Kinect v2 sensor (Rincón et al 2022). We used the visible images to map deformation structures (faults), and the distance images to quantify topographic changes.…”

“…Microsoft® Kinect v2 combines an optical camera and an infrared distance measurement sensor. The precision of the device has been quantified by Rincón et al (2022) and is ∼1 mm.…”

Digitising sandbox experiments using open-source Structure-from-Motion/photogrammetry/Digital Image Correlation package MicMac

“…Structure-from-Motion and photogrammetry have been implemented in sandbox models to monitor deformation of their surface (Donnadieu et al 2003;Schmiedel et al 2019;Bertelsen et al 2021;Rincón et al 2022). Various software packages are available, either opensource of commercial.…”