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GridFIA Documentation

Welcome to GridFIA - a Python API for spatial forest analysis using USDA Forest Service BIGMAP data.

Part of the FIAtools Ecosystem

GridFIA is one of four integrated Python tools for forest inventory analysis. Visit fiatools.org to explore the complete ecosystem and see how the tools work together.

What is GridFIA?

GridFIA is a user-friendly wrapper that makes it easy to work with BIGMAP 2018 forest biomass data. BIGMAP provides 30-meter resolution estimates of tree species biomass across the contiguous United States, and GridFIA gives you a clean Python API to:

  • Download species biomass rasters for any state, county, or custom region
  • Store data efficiently in cloud-optimized Zarr format
  • Calculate diversity metrics (Shannon, Simpson, richness, evenness)
  • Generate publication-ready maps and visualizations

The FIAtools Python Ecosystem

Tool Purpose Key Features
pyFIA Survey & plot data DuckDB backend, 10-100x faster than EVALIDator
gridFIA Spatial raster analysis 327 species at 30m resolution, Zarr storage
pyFVS Growth simulation Chapman-Richards curves, yield projections
askFIA AI interface Natural language queries for forest data

Explore the full ecosystem at fiatools.org

Quick Start

# Install with uv (recommended)
uv pip install gridfia

# Or with pip
pip install gridfia

from gridfia import GridFIA

api = GridFIA()

# Download species data for Montana
files = api.download_species(
    state="Montana",
    species_codes=["0202", "0122"],  # Douglas-fir, Ponderosa pine
    output_dir="downloads/"
)

# Create Zarr store
zarr_path = api.create_zarr("downloads/", "data/montana.zarr")

# Calculate diversity metrics
results = api.calculate_metrics(
    zarr_path,
    calculations=["species_richness", "shannon_diversity"]
)

# Create maps
maps = api.create_maps(zarr_path, map_type="diversity", state="MT")

Key Features

Simple API

One class, eight methods - that's all you need:

api = GridFIA()
api.list_species()        # See available species
api.download_species()    # Download raster data
api.create_zarr()         # Convert to Zarr format
api.calculate_metrics()   # Run forest calculations
api.create_maps()         # Generate visualizations
api.get_location_config() # Configure geographic extents
api.list_calculations()   # See available metrics
api.validate_zarr()       # Validate data stores

15+ Forest Metrics

Category Metrics
Diversity Species richness, Shannon index, Simpson index, Evenness
Biomass Total biomass, Species proportion, Threshold analysis
Species Dominant species, Presence/absence, Rare/common species

Cloud-Optimized Storage

GridFIA uses Zarr for efficient storage and processing of large raster datasets with configurable chunking and compression.

Any Geographic Extent

Download data for any US location:

# Entire state
api.download_species(state="California")

# Specific county
api.download_species(state="Texas", county="Harris")

# Custom bounding box
api.download_species(bbox=(-123.5, 45.0, -122.0, 46.5), crs="EPSG:4326")

Documentation

About BIGMAP Data

BIGMAP (Biomass and Carbon Mapping) provides modeled estimates of live tree biomass at 30-meter resolution. The data is derived from:

  • FIA plot measurements
  • Landsat imagery
  • Topographic variables
  • Climate data

Species-level biomass estimates are available for 300+ tree species. See the FIA BIGMAP documentation for methodology details.

Contributing

We welcome contributions! See our GitHub repository to:

  • Report issues
  • Submit pull requests
  • Request features

Learn More

  • fiatools.org - Explore the complete FIA Python ecosystem
  • GitHub - Source code and issue tracker
  • PyPI - Package installation

License

GridFIA is released under the MIT License.

fiatools.org ยท Python Ecosystem for Forest Inventory Analysis