Aspects derived from the geological, geometrical, and statistical analysis of the Ticino landslide inventory
Bibliographic record
Abstract
An inventory of more than 2000 mass movement events from the last 20 years from the canton Ticino, in the south of Switzerland, was analysed. The pre-Alpine to Alpine setting, combined with a mild temperate climate makes for a large number of natural events per year. The inventory consists of entries for spatially located movement types corresponding to rockfalls (43 %), debris flows (28%), landslides (17%), and avalanches (12%), with some recorded variables (date, coordinates, etc.). Additional geometrical data, as well as data from four categories (topography, hydrography, land use, and geology) was collected and pre-processed. Both a simple analysis and a more complex ones were carried out. From the initial statistical analysis, we determined that the relevant controlling parameters in this context are slope, aspect, terrain roughness index, topographic wetness index, and general lithology; while geometrical aspects of importance are area, length, height difference, volume, and angle of reach. We also conclude that the most affected districts are those of Blenio, Mendrisio, Locarno and Bellinzona, where debris flows and avalanches, debris flows, rockfalls and rockfalls prevail, respectively. From the geometrical aspects, we conclude that that rockfalls and landslides tend to have smaller areas and perimeters than avalanches and debris flows, as expected, due to their mobility. However, the deposit lengths, height differences and volumes show similar patterns. The calculated angle of reach shows similar median and mode values at around 26º/30º, 33º, 34º/35º and 41º, for debris flows, avalanches, landslides, and rockfalls and respectively. Significant power law correlations were found between deposit length and the height difference (cf. Corominas, 1996), deposit volume and the movement area (cf. Guzzeti et al., 2009), and the distribution of rockfall volumes (cf. Dussauge et al., 2003). Possible further work with this inventory includes probabilistic approaches and the application of machine learning techniques for the establishment of the precise relationships between the different controlling parameters and each movement type. References Corominas, J. (1996). The angle of reach as a mobility index for small and large landslides. Canadian Geotechnical Journal, 33(2), 260-271. Dussauge, C., Grasso, J. R., & Helmstetter, A. (2003). Statistical analysis of rockfall volume distributions: Implications for rockfall dynamics. Journal of Geophysical Research: Solid Earth, 108(B6). Guzzetti, F., Ardizzone, F., Cardinali, M., Rossi, M., & Valigi, D. (2009). Landslide volumes and landslide mobilization rates in Umbria, central Italy. Earth and Planetary Science Letters, 279(3-4), 222-229.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".