Supplementary Material for "Revealing Spatiotemporal Deformation Patterns through Time-Dependent Clustering of GNSS Data in the Japanese Islands"
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| Format: | Recurso digital |
| Language: | English |
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2025
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| _version_ | 1866901983523241984 |
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| author | Gabsatarov, Yurii Vladimirova, Irina Ignatev, Dmitrii Scheveva, Nadezhda |
| author_facet | Gabsatarov, Yurii Vladimirova, Irina Ignatev, Dmitrii Scheveva, Nadezhda |
| contents | <p>Supplementary Material for the article<br>Gabsatarov, Y.; Vladimirova, I.; Ignatyev, D.; Scheveva, N.<br><em>“Revealing Spatiotemporal Deformation Patterns through Time-Dependent Clustering of GNSS Data in the Japanese Islands”</em><br>submitted to <em>MDPI Machine Learning and Knowledge Extraction (MAKE)</em>.</p> <p>This archive contains figures and analysis outputs related to the clustering of Japanese GNSS (GEONET) data, including:</p> <ol> <li> <p>Results of clustering analysis of the steady-state velocity field (Figures S1–S5).</p> </li> <li> <p>Results of clustering analysis of regression-derived parameters (Figures S6–S10).</p> </li> <li> <p>Calculated plate motion velocities.</p> </li> </ol> <p>Data and figures include feature correlation heatmaps, PCA explained variance, cluster evaluation metrics, pairwise ARI heatmaps, and ARI-based stability analyses for different feature sets.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17575754 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supplementary Material for "Revealing Spatiotemporal Deformation Patterns through Time-Dependent Clustering of GNSS Data in the Japanese Islands" Gabsatarov, Yurii Vladimirova, Irina Ignatev, Dmitrii Scheveva, Nadezhda GNSS Japanese Islands Unsupervised Machine Learning Clustering <p>Supplementary Material for the article<br>Gabsatarov, Y.; Vladimirova, I.; Ignatyev, D.; Scheveva, N.<br><em>“Revealing Spatiotemporal Deformation Patterns through Time-Dependent Clustering of GNSS Data in the Japanese Islands”</em><br>submitted to <em>MDPI Machine Learning and Knowledge Extraction (MAKE)</em>.</p> <p>This archive contains figures and analysis outputs related to the clustering of Japanese GNSS (GEONET) data, including:</p> <ol> <li> <p>Results of clustering analysis of the steady-state velocity field (Figures S1–S5).</p> </li> <li> <p>Results of clustering analysis of regression-derived parameters (Figures S6–S10).</p> </li> <li> <p>Calculated plate motion velocities.</p> </li> </ol> <p>Data and figures include feature correlation heatmaps, PCA explained variance, cluster evaluation metrics, pairwise ARI heatmaps, and ARI-based stability analyses for different feature sets.</p> |
| title | Supplementary Material for "Revealing Spatiotemporal Deformation Patterns through Time-Dependent Clustering of GNSS Data in the Japanese Islands" |
| topic | GNSS Japanese Islands Unsupervised Machine Learning Clustering |
| url | https://doi.org/10.5281/zenodo.17575754 |