Align wildfire models and docs to 31-model roster

docs/source/api/pyhazards.models.rst

@@ -17,7 +17,7 @@ Wildfire
 Implemented Models
 ++++++++++++++++++
 
-:doc:`ASUFM </modules/models_asufm>`, :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`FireCastNet </modules/models_firecastnet>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`Wildfire Forecasting </modules/models_wildfire_forecasting>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`, :doc:`CNN-ASPP </modules/models_wildfire_aspp>`.
+:doc:`ASUFM </modules/models_asufm>`, :doc:`Attention U-Net </modules/models_attention_unet>`, :doc:`ConvGRU-TrajGRU </modules/models_convgru_trajgru>`, :doc:`ConvLSTM </modules/models_convlstm>`, :doc:`Deep Ensemble </modules/models_deep_ensemble>`, :doc:`DeepLabV3+ </modules/models_deeplabv3p>`, :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`EarthFarseer </modules/models_earthfarseer>`, :doc:`EarthFormer </modules/models_earthformer>`, :doc:`FireCastNet </modules/models_firecastnet>`, :doc:`FirePred </modules/models_firepred>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`LightGBM </modules/models_lightgbm>`, :doc:`Logistic Regression </modules/models_logistic_regression>`, :doc:`MAU </modules/models_mau>`, :doc:`PredRNN-v2 </modules/models_predrnn_v2>`, :doc:`Rainformer </modules/models_rainformer>`, :doc:`Random Forest </modules/models_random_forest>`, :doc:`ResNet18 U-Net </modules/models_resnet18_unet>`, :doc:`SegFormer </modules/models_segformer>`, :doc:`Swin-Unet </modules/models_swin_unet>`, :doc:`SwinLSTM </modules/models_swinlstm>`, :doc:`TCN </modules/models_tcn>`, :doc:`TS-SatFire </modules/models_ts_satfire>`, :doc:`U-Net </modules/models_unet>`, :doc:`U-TAE </modules/models_utae>`, :doc:`ViT Segmenter </modules/models_vit_segmenter>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`, :doc:`XGBoost </modules/models_xgboost>`, :doc:`CNN-ASPP </modules/models_wildfire_aspp>`.
 
 Earthquake
 ~~~~~~~~~~

docs/source/appendix_a_coverage.rst

@@ -34,7 +34,7 @@ Hazard Summary
      - 0
      - 0
    * - Wildfire
-     - 6
+     - 5
      - 0
      - 0
    * - Flood
@@ -108,12 +108,6 @@ Method and Resource Matrix
      - ``Implemented``
      - None
      - A synthetic-backed AEFA-style forecasting dataset adapter is registered.
-   * - Wildfire
-     - `wildfire_forecasting <https://github.com/Orion-AI-Lab/wildfire_forecasting>`_
-     - Baseline
-     - ``Implemented``
-     - :doc:`Wildfire Forecasting <modules/models_wildfire_forecasting>`
-     -  
    * - Wildfire
      - `WildfireSpreadTS <https://github.com/SebastianGer/WildfireSpreadTS>`_
      - Baseline / Benchmark

docs/source/benchmarks/wildfire_benchmark.rst

@@ -6,7 +6,7 @@ Wildfire Benchmark
 Overview
 --------
 
-The wildfire benchmark family is the single scoring layer for tabular danger tasks, weekly forecasting tasks, and raster spread tasks.
+The wildfire benchmark family is the single scoring layer for tabular occurrence tasks, risk forecasting baselines, and raster spread tasks.
 
 Current coverage is synthetic-backed, but it already exposes a single hazard-level evaluator contract across wildfire danger and wildfire spread smoke configs.
 
@@ -55,11 +55,11 @@ At a Glance
 
       .. container:: catalog-stat-value
 
-         8
+         31
 
       .. container:: catalog-stat-note
 
-         8 models
+         31 models
 
 
 Benchmark Mapping
@@ -97,7 +97,6 @@ Mapped benchmark ecosystems
    :class-container: catalog-dropdown
 
    - ``wildfire_danger_smoke.yaml``
-   - ``wildfire_forecasting_smoke.yaml``
    - ``asufm_smoke.yaml``
    - ``wildfire_spread_smoke.yaml``
    - ``wildfirespreadts_smoke.yaml``
@@ -108,7 +107,7 @@ Mapped benchmark ecosystems
 .. dropdown:: Linked Models
    :class-container: catalog-dropdown
 
-   :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`Wildfire Forecasting </modules/models_wildfire_forecasting>`, :doc:`ASUFM </modules/models_asufm>`, :doc:`CNN-ASPP </modules/models_wildfire_aspp>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`, :doc:`FireCastNet </modules/models_firecastnet>`.
+   :doc:`Logistic Regression </modules/models_logistic_regression>`, :doc:`Random Forest </modules/models_random_forest>`, :doc:`XGBoost </modules/models_xgboost>`, :doc:`LightGBM </modules/models_lightgbm>`, :doc:`U-Net </modules/models_unet>`, :doc:`ResNet18 U-Net </modules/models_resnet18_unet>`, :doc:`Attention U-Net </modules/models_attention_unet>`, :doc:`DeepLabV3+ </modules/models_deeplabv3p>`, :doc:`ConvLSTM </modules/models_convlstm>`, :doc:`MAU </modules/models_mau>`, :doc:`PredRNN-v2 </modules/models_predrnn_v2>`, :doc:`Rainformer </modules/models_rainformer>`, :doc:`EarthFormer </modules/models_earthformer>`, :doc:`SwinLSTM </modules/models_swinlstm>`, :doc:`EarthFarseer </modules/models_earthfarseer>`, :doc:`ConvGRU-TrajGRU </modules/models_convgru_trajgru>`, :doc:`TCN </modules/models_tcn>`, :doc:`U-TAE </modules/models_utae>`, :doc:`SegFormer </modules/models_segformer>`, :doc:`Swin-Unet </modules/models_swin_unet>`, :doc:`ViT Segmenter </modules/models_vit_segmenter>`, :doc:`Deep Ensemble </modules/models_deep_ensemble>`, :doc:`ASUFM </modules/models_asufm>`, :doc:`CNN-ASPP </modules/models_wildfire_aspp>`, :doc:`FireCastNet </modules/models_firecastnet>`, :doc:`FirePred </modules/models_firepred>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`TS-SatFire </modules/models_ts_satfire>`, :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`.
 
 .. dropdown:: Notes
    :class-container: catalog-dropdown

docs/source/benchmarks/wildfirespreadts_ecosystem.rst

@@ -55,11 +55,11 @@ At a Glance
 
       .. container:: catalog-stat-value
 
-         5
+         25
 
       .. container:: catalog-stat-note
 
-         5 models
+         25 models
 
 
 Benchmark Mapping
@@ -103,4 +103,4 @@ Primary Source
 .. dropdown:: Linked Models
    :class-container: catalog-dropdown
 
-   :doc:`CNN-ASPP </modules/models_wildfire_aspp>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`, :doc:`FireCastNet </modules/models_firecastnet>`.
+   :doc:`CNN-ASPP </modules/models_wildfire_aspp>`, :doc:`U-Net </modules/models_unet>`, :doc:`ResNet18 U-Net </modules/models_resnet18_unet>`, :doc:`Attention U-Net </modules/models_attention_unet>`, :doc:`DeepLabV3+ </modules/models_deeplabv3p>`, :doc:`ConvLSTM </modules/models_convlstm>`, :doc:`MAU </modules/models_mau>`, :doc:`PredRNN-v2 </modules/models_predrnn_v2>`, :doc:`Rainformer </modules/models_rainformer>`, :doc:`EarthFormer </modules/models_earthformer>`, :doc:`SwinLSTM </modules/models_swinlstm>`, :doc:`EarthFarseer </modules/models_earthfarseer>`, :doc:`ConvGRU-TrajGRU </modules/models_convgru_trajgru>`, :doc:`TCN </modules/models_tcn>`, :doc:`U-TAE </modules/models_utae>`, :doc:`SegFormer </modules/models_segformer>`, :doc:`Swin-Unet </modules/models_swin_unet>`, :doc:`ViT Segmenter </modules/models_vit_segmenter>`, :doc:`Deep Ensemble </modules/models_deep_ensemble>`, :doc:`FireCastNet </modules/models_firecastnet>`, :doc:`FirePred </modules/models_firepred>`, :doc:`WildfireSpreadTS </modules/models_wildfirespreadts>`, :doc:`TS-SatFire </modules/models_ts_satfire>`, :doc:`ForeFire Adapter </modules/models_forefire>`, :doc:`WRF-SFIRE Adapter </modules/models_wrf_sfire>`.

docs/source/datasets/fpa_fod_weekly.rst

@@ -98,7 +98,7 @@ Related Coverage
 
 **Benchmarks:** :doc:`Wildfire Benchmark </benchmarks/wildfire_benchmark>`
 
-**Representative Models:** :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`Wildfire Forecasting </modules/models_wildfire_forecasting>`, :doc:`ASUFM </modules/models_asufm>`
+**Representative Models:** :doc:`DNN-LSTM-AutoEncoder </modules/models_wildfire_fpa>`, :doc:`ASUFM </modules/models_asufm>`
 
 Inspection Workflow
 -------------------

docs/source/modules/models_attention_unet.rst

@@ -0,0 +1,107 @@
+.. This file is generated by scripts/render_model_docs.py. Do not edit by hand.
+
+Attention U-Net
+===============
+
+Overview
+--------
+
+``attention_unet`` extends the encoder-decoder wildfire baseline with lightweight gating on skip connections.
+
+At a Glance
+-----------
+
+.. grid:: 1 2 4 4
+   :gutter: 2
+   :class-container: catalog-grid
+
+   .. grid-item-card:: Hazard Family
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         Wildfire
+
+      .. container:: catalog-stat-note
+
+         Public catalog grouping used for this model.
+
+   .. grid-item-card:: Maturity
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         Implemented
+
+      .. container:: catalog-stat-note
+
+         Catalog maturity label used on the index page.
+
+   .. grid-item-card:: Tasks
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         1
+
+      .. container:: catalog-stat-note
+
+         Spread
+
+   .. grid-item-card:: Benchmark Family
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         :doc:`Wildfire Benchmark </benchmarks/wildfire_benchmark>`
+
+      .. container:: catalog-stat-note
+
+         Primary benchmark-family link used for compatible evaluation coverage.
+
+
+Description
+-----------
+
+``attention_unet`` extends the encoder-decoder wildfire baseline with lightweight gating on skip connections.
+
+PyHazards keeps it public because attention-augmented U-Net variants appear frequently in wildfire progression comparisons.
+
+Benchmark Compatibility
+-----------------------
+
+**Primary benchmark family:** :doc:`Wildfire Benchmark </benchmarks/wildfire_benchmark>`
+
+**Mapped benchmark ecosystems:** :doc:`WildfireSpreadTS </benchmarks/wildfirespreadts_ecosystem>`
+
+External References
+-------------------
+
+**Paper:** `TS-SatFire: A wildfire progression benchmark from temporally dense satellite sequences <https://doi.org/10.1038/s41597-025-06271-3>`_
+
+Registry Name
+-------------
+
+Primary entrypoint: ``attention_unet``
+
+Supported Tasks
+---------------
+
+- Spread
+
+Programmatic Use
+----------------
+
+.. code-block:: python
+
+   import torch
+   from pyhazards.models import build_model
+
+   model = build_model(name="attention_unet", task="segmentation", in_channels=12)
+   logits = model(torch.randn(2, 12, 16, 16))
+   print(logits.shape)
+
+Notes
+-----
+
+- The smoke path uses a single wildfire raster snapshot and returns a one-channel prediction map.

docs/source/modules/models_convgru_trajgru.rst

@@ -0,0 +1,107 @@
+.. This file is generated by scripts/render_model_docs.py. Do not edit by hand.
+
+ConvGRU-TrajGRU
+===============
+
+Overview
+--------
+
+``convgru_trajgru`` provides a gated recurrent raster-history baseline for wildfire sequence prediction.
+
+At a Glance
+-----------
+
+.. grid:: 1 2 4 4
+   :gutter: 2
+   :class-container: catalog-grid
+
+   .. grid-item-card:: Hazard Family
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         Wildfire
+
+      .. container:: catalog-stat-note
+
+         Public catalog grouping used for this model.
+
+   .. grid-item-card:: Maturity
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         Implemented
+
+      .. container:: catalog-stat-note
+
+         Catalog maturity label used on the index page.
+
+   .. grid-item-card:: Tasks
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         1
+
+      .. container:: catalog-stat-note
+
+         Spread
+
+   .. grid-item-card:: Benchmark Family
+      :class-card: catalog-stat-card
+
+      .. container:: catalog-stat-value
+
+         :doc:`Wildfire Benchmark </benchmarks/wildfire_benchmark>`
+
+      .. container:: catalog-stat-note
+
+         Primary benchmark-family link used for compatible evaluation coverage.
+
+
+Description
+-----------
+
+``convgru_trajgru`` provides a gated recurrent raster-history baseline for wildfire sequence prediction.
+
+PyHazards keeps it available as a lightweight proxy for ConvGRU and TrajGRU style wildfire forecasters.
+
+Benchmark Compatibility
+-----------------------
+
+**Primary benchmark family:** :doc:`Wildfire Benchmark </benchmarks/wildfire_benchmark>`
+
+**Mapped benchmark ecosystems:** :doc:`WildfireSpreadTS </benchmarks/wildfirespreadts_ecosystem>`
+
+External References
+-------------------
+
+**Paper:** `FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction <https://doi.org/10.1038/s41598-025-30645-7>`_
+
+Registry Name
+-------------
+
+Primary entrypoint: ``convgru_trajgru``
+
+Supported Tasks
+---------------
+
+- Spread
+
+Programmatic Use
+----------------
+
+.. code-block:: python
+
+   import torch
+   from pyhazards.models import build_model
+
+   model = build_model(name="convgru_trajgru", task="segmentation", history=4, in_channels=8)
+   logits = model(torch.randn(2, 4, 8, 16, 16))
+   print(logits.shape)
+
+Notes
+-----
+
+- The smoke path uses a short wildfire raster history and returns a one-channel prediction map.