Synthetic hail experiments to assess the performance of drone-based hail photogrammetry
Contributors
Data collectors:
-
1.
Federal Office of Meteorology and Climatology MeteoSwiss
Description
Synthetic hail experiments
The data used for assessing the performance of drone-based hail photogrammetry.
Three types of hail objects were used:
- EPS (extended polystyrene)
- Glass pebbles
- Ice from a consumer-grade ice-maker
The experiments were performed on different types of grass, such as soccer fields, lawns and meadows. The models are trained on a leave-one-out cross-validation (LOOCV) scheme, where the test set is based on one surface, while training and validation sets are based on the rest (randomly split). This is defined as an experiment configuration (a-e), where the name refers to the surface of the test set.
Code
The code used to create and analyze the data can be found on github: https://github.com/MeteoSwiss/ehw24-hail-photogrammetry
Table of contents
data.zip
Contains the processed data to create plots
- eps_experiment.nc
- ice_experiment.nc
- glass_experiment.nc
- detection_scores.nc
- detection_fp.nc
- detection_fn.nc
experiments.zip
Contains the full data that need to be processed for each expert and hail type
- annotation
- eps_jportmann_a
- annotations
- instances_Test.json
- instances_Train.json
- train.json
- val.json
- images
- Test
- Train
- annotations
- eps_jportmann_b
- ...
- ...
- eps_jportmann_a
- detections
- eps_jportmann_a
- pkl
- eps_jportmann_b
- ...
- eps_jportmann_a
- models
- eps_jportmann_a
- events.out.tfevents
- last_checkpoint
- metrics.json
- model_final.pth
- eps_jportmann_b
- ...
- ...
- eps_jportmann_a
additional_plots.zip
Loss curves during model training for each expert and hail type
Files
additional_plots.zip
Additional details
Related works
- Is supplement to
- Publication: 10.3389/fenvs.2025.1602917 (DOI)
- References
- Dataset: 10.5281/zenodo.13837507 (DOI)
Dates
- Collected
-
2024Time of field experiments
Software
- Repository URL
- https://github.com/MeteoSwiss/ehw24-hail-photogrammetry
- Programming language
- Python