pyfia 1.3.0

High-performance Python library for Forest Inventory and Analysis (FIA) data analysis

pyFIA

The Python API for forest inventory data

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A high-performance Python library for analyzing USDA Forest Inventory and Analysis (FIA) data. Built on DuckDB and Polars for speed, with statistical methods that match EVALIDator exactly.

Why pyFIA?

Feature	pyFIA	EVALIDator
Speed	10-100x faster	Baseline
Interface	Python API	Web UI
Reproducibility	Code-based	Manual
Custom analysis	Unlimited	Limited options
Statistical validity	✓ Exact match	✓ Reference

Quick Start

pip install pyfia

from pyfia import FIA, biomass, tpa, volume, area

with FIA("path/to/FIA_database.duckdb") as db:
    db.clip_by_state(37)  # North Carolina
    db.clip_most_recent(eval_type="EXPVOL")

    # Core estimates
    trees = tpa(db, tree_domain="STATUSCD == 1")
    carbon = biomass(db, by_species=True)
    timber = volume(db, land_type="timber")
    forest = area(db, land_type="forest")

Core Functions

Function	Description	Example
tpa()	Trees per acre	tpa(db, tree_domain="DIA >= 5.0")
biomass()	Above/belowground biomass	biomass(db, by_species=True)
volume()	Merchantable volume (ft³)	volume(db, land_type="timber")
area()	Forest land area	area(db, grp_by="FORTYPCD")
site_index()	Site productivity index	site_index(db, grp_by="COUNTYCD")
mortality()	Annual mortality rates	mortality(db)
growth()	Net growth estimation	growth(db)

Statistical Methods

pyFIA implements design-based estimation following Bechtold & Patterson (2005):

• Post-stratified estimation with proper variance calculation
• Ratio-of-means estimators for per-acre values
• EVALID-based filtering for statistically valid estimates
• Temporal methods: TI, annual, SMA, LMA, EMA

Installation

# Recommended: use uv for fast, reliable installs
uv pip install pyfia

# Or with pip
pip install pyfia

# With spatial support (polygon clipping, spatial joins)
uv pip install pyfia[spatial]

Tip: Always use a virtual environment (uv venv or python -m venv .venv).

For development setup, see the Getting Started guide.

Documentation

Full documentation: mihiarc.github.io/pyfia

Citation

@software{pyfia2025,
  title = {pyFIA: A Python Library for Forest Inventory Applications},
  author = {Mihiar, Christopher},
  year = {2025},
  url = {https://github.com/mihiarc/pyfia}
}

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Affiliation

Developed in collaboration with USDA Forest Service Research & Development. pyFIA provides programmatic access to Forest Inventory and Analysis (FIA) data but is not part of the official FIA Program.

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_{Built by Chris Mihiar}