swissSimilarityMatrix

<p>as defined by Lehning et al (2001). A similarity of 1 represents identity, 0 represents total dissimilarity.</p>

type

similarity

Grain

Snow profiles describe the vertical (1D) stratigraphy of layered
snow with different layer characteristics, such as grain type, hardness,
deposition date, and many more. Hence, they represent a data format similar
to multivariate time series containing categorical, ordinal, and numerical
data types. Use this package to align snow profiles by matching their
individual layers based on Dynamic Time Warping (DTW). The aligned profiles
can then be assessed with an independent, global similarity measure that is
geared towards avalanche hazard assessment. Finally, through exploiting data
aggregation and clustering methods, the similarity measure provides the
foundation for grouping and summarizing snow profiles according to similar
hazard conditions. In particular, this package allows for averaging large
numbers of snow profiles with DTW Barycenter Averaging and thereby
facilitates the computation of individual layer distributions and summary
statistics that are relevant for avalanche forecasting purposes.
For more background information refer to Herla, Horton, Mair,
and Haegeli (2021) <doi:10.5194/gmd-14-239-2021>, Herla, Mair, and Haegeli
(2022) <doi:10.5194/tc-16-3149-2022>, and Horton, Herla, and Haegeli (2024)
<doi:10.5194/egusphere-2024-1609>.

Florian Herla

sarp.snowprofile.alignment

Snow Profile Alignment, Aggregation, and Clustering

Pascal Haegeli

Simon Horton

Paul Billecocq

SFU Avalanche Research Program 

swissSimilarityMatrix function

Format

Similarity Matrix of Snow Grain Types — swissSimilarityMatrix

Similarity Matrix of Snow Grain Types

swissSimilarityMatrix: Similarity Matrix of Snow Grain Types

Description

Usage

Arguments

Format

Examples