| --- |
| license: mit |
| task_categories: |
| - visual-question-answering |
| - image-classification |
| language: |
| - en |
| tags: |
| - extreme-weather |
| - satellite-imagery |
| - multimodal |
| - vqa |
| - benchmark |
| - disaster-analysis |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # ObsCrisis-Bench |
|
|
| A multimodal benchmark for evaluating large vision-language models on extreme weather event analysis tasks. |
|
|
| ## Dataset Description |
|
|
| ObsCrisis-Bench contains **4,202 VQA samples** across **127 extreme weather events** in **8 disaster categories**, covering **61 countries**. Each sample combines satellite multispectral imagery (AMSU-A, HIRS, MHS sensors) with optional weather station data, and requires models to perform risk assessment, type classification, timing prediction, and impact analysis. |
|
|
| ## Disaster Categories |
|
|
| | Category | Events | VQA Samples | Subtypes | |
| |----------|--------|-------------|----------| |
| | cold-wave | 5 | 140 | cold-wave | |
| | earthquake | 10 | 417 | ground movement, tsunami | |
| | flood | 17 | 523 | coastal flood, flash flood, general flood, riverine flood | |
| | heat-wave | 5 | 165 | heat-wave | |
| | mass movement (wet) | 6 | 189 | landslide (wet), mudslide | |
| | storm | 55 | 1,852 | blizzard/winter storm, derecho, extra-tropical storm, general storm, hail, lightning/thunderstorm, sand/dust storm, severe weather, storm surge, tornado, tropical cyclone | |
| | volcanic activity | 15 | 450 | ash fall, general activity, lava flow, pyroclastic flow | |
| | wildfire | 14 | 466 | forest fire, general wildfire, land fire | |
| | **Total** | **127** | **4,202** | | |
|
|
| ## Task Structure |
|
|
| Each VQA sample belongs to one of three task categories: |
|
|
| | Task Category | Samples | Percentage | |
| |---------------|---------|------------| |
| | Early Warning | 1,524 | 36.3% | |
| | Impact Assessment | 2,465 | 58.7% | |
| | Recovery Assessment | 213 | 5.1% | |
|
|
| ### Task Types |
|
|
| **Early Warning** (t1, t8, t12): |
| - Risk Detection (381 samples): Assess the risk of an impending disaster |
| - Type Classification (381 samples): Identify the specific type of potential disaster |
| - Arrival Time Prediction (381 samples): Predict when the disaster will arrive |
| - Duration Prediction (381 samples): Predict how long the disaster will last |
|
|
| **Impact Assessment** (t1, t8, t12, t15, tmax): |
| - CPI / Crisis Prevention Index (610 samples): Estimate the crisis prevention index |
| - Total Affected (485 samples): Predict total affected population |
| - Total Deaths (455 samples): Predict total deaths |
| - No. Affected (400 samples): Predict number of affected people |
| - No. Injured (260 samples): Predict number of injured people |
| - Magnitude (185 samples): Predict earthquake magnitude |
| - No. Homeless (70 samples): Predict number of homeless people |
|
|
| **Recovery Assessment** (t15, tmax-1): |
| - Recovery Time Prediction (213 samples): Predict recovery time after the event |
|
|
| ### Timestep Convention |
|
|
| - `t1` = 14 days before event start |
| - `t8` = 7 days before event start |
| - `t12` = 3 days before event start |
| - `t15` = event start day |
| - `tmax` = maximum impact time (event-dependent) |
| - `tmax-1` = one timestep before maximum impact |
| - `t_number = (image_date - event_start_date).days + 15` |
|
|
| ## Dataset Structure |
|
|
| ``` |
| ObsCrisis-Bench/ |
| ├── cold-wave/ # Satellite imagery |
| │ └── cold-wave1/<event_id>/<sensor>/<band>/t1.png ... tN.png |
| ├── cold-wave_json/ |
| │ └── All.json # VQA records |
| ├── heat-wave/ |
| ├── heat-wave_json/All.json |
| ├── earthquake/ |
| ├── earthquake_json/All.json |
| ├── flood/ |
| ├── flood_json/All.json |
| ├── mass movement (wet)/ |
| ├── mass movement (wet)_json/All.json |
| ├── storm/ |
| ├── storm_json/All.json |
| ├── volcanic activity/ |
| ├── volcanic activity_json/All.json |
| ├── wildfire/ |
| └── wildfire_json/All.json |
| ``` |
|
|
| ### Satellite Sensors |
|
|
| The dataset includes multispectral imagery from three satellite sensors: |
|
|
| | Sensor | Bands | Description | |
| |--------|-------|-------------| |
| | AMSU-A | 15 bands (0-14) | Advanced Microwave Sounding Unit-A | |
| | HIRS | 20 bands (0-19) | High-resolution Infrared Radiation Sounder | |
| | MHS | 5 bands (0-4) | Microwave Humidity Sounder | |
|
|
| ### Weather Station Data |
|
|
| Selected samples include supplementary weather station measurements (temperature, pressure, humidity, wind speed) when available for the event location. |
|
|
| ## VQA Sample Fields |
|
|
| | Field | Type | Description | |
| |-------|------|-------------| |
| | `Question_id` | string | Unique identifier (format: `Task/Type/timestep/subtype/event_id`) | |
| | `Task` | string | Task category (Early Warning / Impact Assessment / Recovery Assessment) | |
| | `Subtask` | string | Subtask with timestep, e.g. "Risk Detection (t1)" | |
| | `Text` | string | Question text | |
| | `Image` | string | Comma-separated relative image paths | |
| | `Stations` | object | Weather station sensor data (optional) | |
| | `Ground truth` | string | Standard answer | |
|
|
| ### QID Format |
|
|
| ``` |
| Task/Type/timestep/subtype/event_id |
| ``` |
| Examples: |
| - `Early Warning/Risk Detection/t1/ground movement/2014-0049-GRC` |
| - `Impact Assessment/Magnitude/tmax/tsunami/2011-0282-JPN` |
| - `Recovery Assessment/Recovery Time Prediction/t15/cold-wave1/2011-0105-MEX` |
|
|
| ## Evaluation |
|
|
| The evaluation framework supports multiple scoring rules per subtask type: |
| - **Boolean**: Exact match (Risk Detection) |
| - **Numeric**: Error-based scoring with tolerance (CPI, Magnitude, population counts) |
| - **Classification**: Exact or partial match (Type Classification) |
| - **Text**: Jaccard word overlap (Arrival Time, Duration, Recovery Time) |
|
|
| Evaluation code is available at: [https://github.com/YYQ898/ObsCrisis-Bench](https://github.com/YYQ898/ObsCrisis-Bench) |
|
|
| ## Citation |
|
|
| If you use this dataset, please cite: |
|
|
| ```bibtex |
| @misc{obscrisis-bench, |
| title={ObsCrisis-Bench: A Multimodal Benchmark for Extreme Weather Event Analysis}, |
| author={ObsCrisis Team}, |
| year={2025} |
| } |
| ``` |
|
|
| ## License |
|
|
| MIT License |
|
|
