FPA-FOD Tabular

Incident-level FPA-FOD features packaged for wildfire cause and size classification.

Overview

FPA-FOD Tabular converts one wildfire incident record into one feature vector for classification tasks such as incident cause prediction and grouped size prediction.

PyHazards exposes it as a loadable dataset with a deterministic micro mode so the full source database is not required for smoke tests or quick experimentation.

At a Glance

Provider

Fire Program Analysis Fire-Occurrence Database (FPA-FOD) adaptation in PyHazards

Hazard Family

Wildfire

Source Role

Incident Tabular

Coverage

User-provided FPA-FOD coverage

Geometry

Tabular feature vectors

Spatial Resolution

Incident-level records

Temporal Resolution

Event-based

Update Cadence

User-managed local inputs or deterministic micro mode

Period of Record

Depends on the supplied FPA-FOD source files

Formats

SQLite, DB, CSV, and Parquet inputs

Inspection CLI

python -m pyhazards.datasets.fpa_fod_tabular.inspection --task cause --micro

Registry Entry

fpa_fod_tabular

Data Characteristics

  • Supports task=’cause’ and task=’size’ classification targets.

  • Accepts SQLite, DB, CSV, and Parquet sources.

  • Micro mode keeps the path deterministic and lightweight for validation.

  • Returned splits follow the standard DataBundle contract with tabular inputs and integer targets.

Typical Use Cases

  • Wildfire cause classification experiments.

  • Grouped fire size classification from incident records.

  • Lightweight smoke and regression tests for the wildfire tabular path.

Access

Use the links below to access the upstream source or its public documentation.

PyHazards Usage

Use this dataset through the public inspection or registry surface documented below.

Registry Workflow

Primary dataset name: fpa_fod_tabular

from pyhazards.datasets import load_dataset

data = load_dataset(
    "fpa_fod_tabular",
    task="cause",
    micro=True,
    normalize=True,
).load()

train = data.get_split("train")
print(train.inputs.shape, train.targets.shape)

  • region=’US’ uses all available states, while region=’CA’ restricts to California incidents.

  • cause_mode=’paper5’ preserves the five consolidated cause groups used by the public wildfire tabular path.

Inspection Workflow

Use the documented inspection path below to validate local files before training or analysis.

python -m pyhazards.datasets.fpa_fod_tabular.inspection --task cause --micro

Reference