--- 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 **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
Click to expand the variable list **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)
--- ## 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.