Sciamlab/landslide-prevention-italy-2024-blind-test

Pre-Landslide Risk Assessment 2024 Blind Test

Blind test dataset for evaluating VLM-based pre-landslide risk detection on 2024 Italian landslide events. This dataset contains 29 events from January–December 2024 with no ground truth labels — designed for evaluating model predictions against future landslide occurrences.

Generated for evaluating fine-tuned models on LiquidAI/LFM2.5-VL-450M.

Dataset Summary

Dataset Structure

landslide_blind_test_2024/
├── README.md            ← this file
├── metadata.jsonl       ← one row per sample
└── images/              ← 6 input composites per sample
    ├── {id}_rgb.png
    ├── {id}_swir.png
    ├── {id}_nir.png
    ├── {id}_ndmi.png
    ├── {id}_ndvi.png
    └── {id}_bsi.png

{id} follows the pattern {event_id}_{town_slug}_{image_date} — e.g. EIT202400007_Genova_2023-12-22.

Data Fields

Composite Images

Each sample contains 6 spectral composites generated from Sentinel-2 L2A:

Usage

from datasets import load_dataset

# Load blind test dataset
ds = load_dataset("your-username/landslide-prevention-italy-2024-blind-test")

# Each sample has 6 images
sample = ds['test'][0]
print(sample['id'], sample['event_date'], sample['location'])

Evaluation

Use this dataset to evaluate pre-landslide detection models:

python scripts/evaluate.py \
  --hf-dataset your-username/landslide-prevention-italy-2024-blind-test \
  --model outputs/lfm2.5-vl-landslide-v2-Q8_0.gguf \
  --backend local

Source Data

• —Imagery: Sentinel-2 L2A surface reflectance.
• —Event ground-truth: Italian Emergency Events (EIT) database, 2024 landslide records.

Considerations for Using

• —Blind test — ground truth labels are not provided. Model predictions should be compared against actual landslide occurrences after the fact.
• —Spectral indices are proxies — NDMI shows surface moisture, not subsurface conditions.
• —No DEM — slope steepness is inferred from visual cues.
• —Temporal context — days_before_event provides the temporal gap between image acquisition and actual event.

Citation

If you use this dataset, please cite the Italian Emergency Events (EIT) database and the Copernicus Sentinel-2 mission.

Generated on 2026-05-02.