> ## Documentation Index
> Fetch the complete documentation index at: https://pyfia.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# pyFIA

> High-performance Python for USDA Forest Inventory and Analysis (FIA) data — statistically valid estimates, 10-100x faster than EVALIDator.

**pyFIA** turns the USDA Forest Service's national forest inventory into a few lines of Python. Download a state, pick an estimator, and get design-based estimates — with proper variance — that match the official [EVALIDator](https://apps.fs.usda.gov/Evalidator/evalidator.jsp) tool.

```python theme={null}
from pyfia import download, FIA, area

db_path = download("RI")          # pull Rhode Island straight from the FIA DataMart

with FIA(db_path) as db:
    db.clip_most_recent()         # use one complete, valid evaluation
    print(area(db, land_type="forest"))   # forest area, with SE and a 95% CI
```

## Start here

<CardGroup cols={2}>
  <Card title="Getting started" icon="rocket" href="/getting-started">
    Install pyFIA and run your first estimate end-to-end in about five minutes.
  </Card>

  <Card title="How-to guides" icon="list-check" href="/guides/downloading">
    Task-focused recipes: downloading data, filtering, grouping, and spatial analysis.
  </Card>

  <Card title="Concepts" icon="book-open" href="/concepts/fia-methodology">
    How FIA sampling, the EVALID system, and design-based variance actually work.
  </Card>

  <Card title="API reference" icon="code" href="/api/pyfia-estimation-estimators-volume">
    Every public function and class, generated from the source docstrings.
  </Card>
</CardGroup>

## Why pyFIA

<CardGroup cols={2}>
  <Card title="Statistically valid" icon="square-root-variable">
    Design-based estimation following Bechtold & Patterson (2005), with standard errors and confidence intervals on every estimate.
  </Card>

  <Card title="Fast" icon="bolt">
    Built on [Polars](https://pola.rs/) and [DuckDB](https://duckdb.org/) for 10-100x faster analysis than legacy tooling.
  </Card>

  <Card title="EVALIDator-validated" icon="circle-check">
    Results checked against the official USFS estimates — typically within 1-3% on standard errors.
  </Card>

  <Card title="Simple API" icon="feather">
    Direct functions — `volume(db)`, `mortality(db)`, `area(db)` — not factories and builders.
  </Card>
</CardGroup>

## Estimation functions

| Function                                                          | Estimates                                        |
| ----------------------------------------------------------------- | ------------------------------------------------ |
| [`area()`](/api/pyfia-estimation-estimators-area)                 | Forest area by land type and category            |
| [`area_change()`](/api/pyfia-estimation-estimators-area_change)   | Annual change in forest area                     |
| [`volume()`](/api/pyfia-estimation-estimators-volume)             | Standing tree volume                             |
| [`tpa()`](/api/pyfia-estimation-estimators-tpa)                   | Trees per acre and basal area                    |
| [`biomass()`](/api/pyfia-estimation-estimators-biomass)           | Tree biomass and carbon                          |
| [`site_index()`](/api/pyfia-estimation-estimators-site_index)     | Area-weighted mean site index                    |
| [`mortality()`](/api/pyfia-estimation-estimators-mortality)       | Annual tree mortality                            |
| [`growth()`](/api/pyfia-estimation-estimators-growth)             | Annual tree growth                               |
| [`removals()`](/api/pyfia-estimation-estimators-removals)         | Timber removals                                  |
| [`tree_metrics()`](/api/pyfia-estimation-estimators-tree_metrics) | TPA-weighted statistics (QMD, mean height)       |
| [`panel()`](/api/pyfia-estimation-estimators-panel)               | Remeasurement panels for change/harvest analysis |

## Coming from rFIA?

pyFIA brings the ergonomics of R's [rFIA](https://doserlab.com/files/rfia/) to Python:

| Task             | rFIA (R)                        | pyFIA (Python)           |
| ---------------- | ------------------------------- | ------------------------ |
| Download a state | `getFIA(states = 'RI')`         | `download("RI")`         |
| Multiple states  | `getFIA(states = c('RI','CT'))` | `download(["RI", "CT"])` |
| Estimate area    | `area(fia)`                     | `area(db)`               |
| Estimate volume  | `volume(fia)`                   | `volume(db)`             |

<Note>
  pyFIA is released under the MIT License and built by [Chris Mihiar](https://github.com/mihiarc). Found a bug or have a question? [Open an issue](https://github.com/mihiarc/pyfia/issues).
</Note>