Process EM-DAT disaster data (drought and flood events) for the 11 ICPAC East Africa countries, assign admin2 boundary codes, and generate frequency maps.
# Step 1: Run geocoding (assigns admin2 codes to events)
python 01-common_adm2_code_drought.py
python 02-common_adm2_code_flood.py
# Step 2: Generate all visualizations
python main.py| Order | Script | Purpose | Output |
|---|---|---|---|
| 1 | 01-common_adm2_code_drought.py |
Geocode drought events | em_dat_ea_drought_adm2_v4.xlsx |
| 2 | 02-common_adm2_code_flood.py |
Geocode flood events | em_dat_ea_flood_adm2_v2.xlsx |
| 3 | main.py |
Generate all visualizations | Output/ folder |
Alternative (simplified):
python ea_impact_events.py # Uses admin1 level (less detailed)| File | Description |
|---|---|
public_emdat_custom_request_2026-01-21.xlsx |
EM-DAT disaster data |
ea_adm2_geoboundaries.shp |
GEOBoundaries admin2 shapefile (972 regions) |
icpac_adm1v3.geojson |
ICPAC admin1 boundaries (fallback) |
After running the pipeline:
Output/
├── dr/ # 36 yearly drought maps (1990-2025)
├── fl/ # 36 yearly flood maps (1990-2025)
├── choropleth_drought_frequency.png # Drought frequency map
├── choropleth_flood_frequency.png # Flood frequency map
├── drought_calendar_plot_enhanced.png
├── flood_calendar_plot_enhanced.png
├── drought_combined_PIL_enhanced.png
└── flood_combined_PIL_enhanced.png
| Code | Country |
|---|---|
| BDI | Burundi |
| DJI | Djibouti |
| ERI | Eritrea |
| ETH | Ethiopia |
| KEN | Kenya |
| RWA | Rwanda |
| SDN | Sudan |
| SOM | Somalia |
| SSD | South Sudan |
| TZA | Tanzania |
| UGA | Uganda |
| Disaster | Events | Geocoded | Regions Affected |
|---|---|---|---|
| Drought | 80 | 80 (100%) | 170 admin2 |
| Flood | 368 | 368 (100%) | 424 admin2 |
See GEOCODING_DOCUMENTATION.md for detailed information on:
- Geocoding methodology
- Data flow and processing steps
- Frequency map generation
- Routine operations for new data
ea-impact-events/
├── Input Data
│ ├── public_emdat_custom_request_2026-01-21.xlsx
│ ├── ea_adm2_geoboundaries.shp
│ └── icpac_adm1v3.geojson
│
├── Geocoding Scripts
│ ├── 01-common_adm2_code_drought.py
│ └── 02-common_adm2_code_flood.py
│
├── Geocoded Output
│ ├── em_dat_ea_drought_adm2_v4.xlsx
│ └── em_dat_ea_flood_adm2_v2.xlsx
│
├── Visualization
│ ├── main.py
│ ├── utils.py
│ ├── ea_impact_events.py (simplified alternative)
│ └── Output/
│
└── Documentation
├── README.md
└── GEOCODING_DOCUMENTATION.md
East Africa Impact events will be enhanced through monty-STAC specifications, adding admin boundaries for integration with STAC-based Analysis Ready Cloud Optimized IBF.
The exploration on monty-STAC is documented at arco-ibf/monty-stac.