{
  "annotation_id": "1190656f-3d86-46f8-97f2-533ad6967162",
  "date_created": "2026-03-02T18:01:07.464000Z",
  "date_modified": "2026-03-02T18:01:07.464000Z",
  "file_hash": "1b28de1c99c2eac5e2bee65002cb4a079b1a72bd8817b355b7ba3045eadc595a",
  "private": false,
  "record": {
    "abstract": "Landslide inventories show that the statistical distribution of the area of\nrecorded events is well described by a power law over a range of decades. To\nunderstand these distributions, we consider a cellular automaton to model a\ntime and position dependent factor of safety. The model is able to reproduce\nthe complex structure of landslide distribution, as experimentally reported. In\nparticular, we investigate the role of the rate of change of the system\ndynamical variables, induced by an external drive, on landslide modeling and\nits implications on hazard assessment. As the rate is increased, the model has\na crossover from a critical regime with power-laws to non power-law behaviors.\nWe suggest that the detection of patterns of correlated domains in monitored\nregions can be crucial to identify the response of the system to perturbations,\ni.e., for hazard assessment.",
    "arxiv_id": "physics/0603094",
    "authors": [
      "E. Piegari",
      "V. Cataudella",
      "R. Di Maio",
      "L. Milano",
      "M. Nicodemi"
    ],
    "categories": [
      "physics.geo-ph"
    ],
    "doi": "10.1029/2005GL024759",
    "journal_ref": "Geophys. Rev. Lett. 33, L01403 (2006)",
    "title": "A cellular automaton for the factor of safety field in landslides   modeling",
    "url": "https://arxiv.org/abs/physics/0603094"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "5d006f15-785f-41e9-8890-87a94ed28faf",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}