Snow particle analyzer for simultaneous measurements of snow density and morphology
Jiaqi Li, Michele Guala, and Jiarong Hong

TL;DR
This paper introduces a novel snow particle analyzer that simultaneously measures snow density, size, shape, and concentration using holography and machine learning, enabling real-time, field-deployable snow characterization.
Contribution
The study presents a new integrated system combining digital holography and machine learning for comprehensive, real-time snow particle analysis in field conditions.
Findings
Achieved <5% error in density measurement using calibration with known particles.
Successfully deployed the system for 4 hours during a snow event, demonstrating real-time monitoring capabilities.
System provides high-resolution, multi-property data of snow particles in various environmental conditions.
Abstract
The detailed characterization of snow particles is critical for understanding the snow settling behavior and modeling the ground snow accumulation for various applications such as prevention of avalanches and snowmelt-caused floods, etc. In this study, we present a snow particle analyzer for simultaneous measurements of various properties of fresh falling snow, including their concentration, size, shape, type, and density. The analyzer consists of a digital inline holography module for imaging falling snow particles in a sample volume of 88 cm3 and a high-precision scale to measure the weight of the same particles in a synchronized fashion. The holographic images are processed in real-time using a machine learning model and post-processing to determine snow particle concentration, size, shape, and type. Such information is used to obtain the estimated volume, which is subsequently…
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Taxonomy
TopicsCryospheric studies and observations · Winter Sports Injuries and Performance · Landslides and related hazards
