README.md

---
license: other
task_categories:
  - time-series-forecasting
  - other
tags:
  - wildfire
  - canada
  - remote-sensing
  - spatiotemporal
  - era5-land
  - modis
  - cffdrs
pretty_name: CanFireCast Dataset (Paper Reproduction Sample)
size_categories:
  - 10K<n<100K
---

# CanFireCast Dataset (Paper Reproduction Sample)

This repository hosts a **sampled** release used to reproduce the experiments in *CanFireCast for Canada Nationwide Wildfire Activity Forecasting with Multisource Spatiotemporal Modeling*.

> **Important:** This is **not** the full nationwide corpus.  
> The complete dataset (raw products, intermediate layers, annual HDF5 archives, and derived caches) exceeds **10 TB** and cannot be redistributed through online platforms.  
> Access to the full dataset may be requested from the authors **after the anonymity period ends** (see [Full Dataset Access](#full-dataset-access)).

Companion code: [CanFireCast](https://anonymous.4open.science/r/CanFireCast4AAAI-AISI)

---

## What This Release Contains

This Hugging Face package provides the **paper-reproduction sample / training cache** used with `--json F` (`cache_F`) in the CanFireCast codebase. Approximate contents (~65 GB):

| File | Description |
|---|---|
| `windows_*.h5` | Sampled spatiotemporal training windows for train / validation / test |
| `samples_variant_F.json` | Sampling metadata for variant `F` |
| `norm_stats.npz` | Train-only normalization statistics (reuse for validation and test) |

These files are sufficient to **fully reproduce the paper training and evaluation pipeline**. They are a carefully constructed subsample of the nationwide data cube, not a dump of every grid cell and day.

---

## Task Definition

**Next-day wildfire activity forecasting** on a **5 km** grid over the Canadian land area.

For each target cell, the model receives **10 days** of environmental history in a local **13 × 13** patch ending on the issue date, and predicts the probability of a high-confidence active-fire observation at the **center cell** on the following day.

Each sample is:

\[
\mathbf{X}_i \in \mathbb{R}^{54 \times 10 \times 13 \times 13}, \quad y_i \in \{0,1\}
\]

Temporal splits (strict year-based, no leakage across years):

| Split | Years |
|---|---|
| Train | 2000–2019 |
| Validation | 2020–2022 |
| Test | 2023–2025 |

The test set uses a **positive-to-negative ratio of 1:2** to avoid extreme class imbalance.

---

## Multisource Inputs

Inputs combine weather and land state, fire-danger indices, vegetation and fuel proxies, terrain, land cover, and human-activity context. Products are spatially interpolated and temporally aligned onto a daily 5 km grid. Cloud-affected, low-quality, or missing remote-sensing observations are filled with the latest valid observation before the target date.

### Variable groups

| Group | Contents | Main sources |
|---|---|---|
| **W** | Weather, land meteorology, CFFDRS indices, VPD | ERA5-Land; derived FWI System indices |
| **F** | Soil moisture, vegetation, satellite land-surface variables, land cover | ERA5-Land; MODIS Terra/Aqua (e.g., MOD/MYD09GA, MCD15A3H, MOD/MYD11A1, MCD12Q1) |
| **B** | Water, terrain, and terrain-derived variables | ASTER DEM; OpenStreetMap-derived water density |
| **I** | Human-activity variables | WorldPop; OpenStreetMap-derived road / powerline / building density |
| **Label** | High-confidence active-fire detection at the center cell | MOD/MYD14A1 |

### Variable summary

<details>
<summary>Click to expand the variable list</summary>

**W — weather / meteorology / fire danger**

- Temperature 2m (mean, max), Dewpoint Temperature 2m, Skin Temperature Max
- Wind 10m (U, V), Precipitation, Snow Cover, Surface Pressure
- Surface Latent Heat Flux, Net Solar Radiation
- Total / Potential Evaporation, Skin Reservoir Content
- VPD (derived)
- FFMC, DMC, DC, ISI, BUI, FWI (Canadian FWI System, derived)

**F — fuel / vegetation / satellite land surface**

- Soil Water Layers 1–4 (ERA5-Land)
- Reflectance bands 1, 2, 3, 7 (MOD/MYD09GA)
- NDVI, EVI; LAI, FPAR (MCD15A3H)
- LST Day / Night; Emis 31 / 32 (MOD/MYD11A1)
- Brightness temperature bands 20, 21, 31, 32 (MOD/MYD09CMG)
- Land Cover Types (MCD12Q1)

**B — terrain / water**

- DEM; Slope; Aspect (sin, cos)
- Hillshade, TPI, TWI
- Water Density (OSM-derived)

**I — human activity**

- Population (WorldPop)
- Road, Powerline, Building Density (OSM-derived)

**Label**

- Fire Detection (MOD/MYD14A1 high-confidence active fire)

</details>

---

## Sampling Notice

Please read this carefully before citing or redistributing this repository:

1. **This release is a sampled subset** designed for paper reproduction (training windows + metadata + normalization stats).
2. It does **not** include the full daily nationwide 5 km data cube, all intermediate geospatial products, or every candidate location outside the paper sampling protocol.
3. Results reported in the paper were obtained with this sampling protocol and the associated `cache_F` configuration.
4. If you need the **complete >10 TB corpus** for other research uses, request it from the authors after anonymity ends (below).

---

## Quick Start

### Download

```bash
pip install -U "huggingface_hub[cli]"
huggingface-cli download Anonymous4AISI/CanFireCast_Dataset \
  --repo-type dataset \
  --local-dir ./CanFireCast_Dataset
```

### Use with the CanFireCast code

1. Clone the code: [https://anonymous.4open.science/r/CanFireCast4AAAI-AISI](https://anonymous.4open.science/r/CanFireCast4AAAI-AISIt)
2. Set `h5_dir` in `prepare_data_loaders()` in `train_all_h5.py` to the extracted dataset directory.
3. Train / evaluate with `--json F` so the loader uses this sample cache.
4. Keep `norm_stats.npz` unchanged for validation and test (train-only statistics).

Example:

```bash
export MODEL_SAVE_DIR=./checkpoints/canfirecast
python train_single_model_h5.py \
  --model CanFireCast \
  --json F \
  --gpu 0 \
  --log-dir ./outputs/canfirecast
```

---

## Full Dataset Access

The full nationwide corpus exceeds **10 TB** and is **not** hosted here.

After the **anonymity / review period ends**, researchers may contact the corresponding author to request access to the complete dataset. Please include:

- name and institution
- intended research use
- which components are needed (raw products / annual HDF5 / caches / etc.)

Access and transfer arrangements may depend on storage capacity and the licenses of the original source products (ERA5-Land, MODIS, ASTER DEM, WorldPop, OpenStreetMap, and derived CFFDRS variables).

> Author contact details will be added here after the anonymity period.

---

## License and Source Acknowledgments

This release redistributes **derived research samples** assembled from third-party environmental products. Users remain responsible for complying with the licenses and citation requirements of the original sources, including but not limited to:

- ERA5-Land (ECMWF / Copernicus)
- MODIS Terra and Aqua products (NASA)
- ASTER GDEM
- WorldPop
- OpenStreetMap contributors
- Canadian Forest Fire Danger Rating System (CFFDRS) / FWI System indices derived from weather inputs

The dataset license field is set to `other` because redistribution terms of the derived sample follow both this research release and the upstream product policies.