Domain filtering

Define your analysis population with land type, tree type, and custom SQL-like domain filters.

A domain is the population you want to estimate — forest land, growing-stock trees, a single species, trees above a diameter threshold, and so on. pyFIA gives you three layers of control: land_type, tree_type, and free-form domain expressions.

Land type

land_type controls which land conditions are included:

Value	Description	Filter applied
"forest"	All forest land	COND_STATUS_CD = 1
"timber"	Timberland only	COND_STATUS_CD = 1 and productive, unreserved
"all"	All sampled land	none

import pyfia

pyfia.volume(db, land_type="forest")   # forest land
pyfia.volume(db, land_type="timber")   # productive timberland

Tree type

tree_type filters which trees are counted:

Value	Description	Filter
"live"	All live trees	STATUSCD = 1
"dead"	Standing dead trees	STATUSCD = 2
"gs"	Growing stock (live, merchantable)	TREECLCD = 2
"all"	All trees regardless of status	none

pyfia.volume(db, tree_type="gs")      # growing stock
pyfia.tpa(db, tree_type="live")       # all live trees

Defaults vary by estimator to match the most common use case — for example, mortality() defaults to growing stock on timberland. Check each function’s API reference for its defaults.

The growth/removal/mortality estimators (growth(), mortality(), removals()) additionally accept "al" (all live) and "sl" / "sawtimber" (sawtimber-size), which select the matching FIA GRM tree populations.

Custom domain filters

For anything more specific, pass SQL-like expressions. These are evaluated against the underlying FIA columns.

Tree domain

Filters individual trees by their attributes:

# Large trees only
pyfia.volume(db, tree_domain="DIA >= 12.0")

# Specific species
pyfia.volume(db, tree_domain="SPCD IN (110, 111, 121)")

# Combined conditions
pyfia.volume(db, tree_domain="DIA >= 5.0 AND SPCD = 316")

Area domain

Filters conditions/plots by their attributes:

# A specific forest type
pyfia.area(db, area_domain="FORTYPCD = 201")

# Gentle slopes only
pyfia.volume(db, area_domain="SLOPE < 30")

# Private land
pyfia.area(db, area_domain="OWNGRPCD = 40")

Putting it together

Domain filters compose, so you can target a precise population:

# Pine growing stock on private timberland, gentle slopes
pyfia.volume(
    db,
    land_type="timber",
    tree_type="gs",
    tree_domain="SPGRPCD = 10",     # softwood group
    area_domain="OWNGRPCD = 40 AND SLOPE < 30",
)

Common patterns

Species-specific volume

pyfia.volume(
    db,
    land_type="timber",
    tree_type="gs",
    tree_domain="SPGRPCD = 10",   # softwoods
)

Sawtimber volume

pyfia.volume(
    db,
    vol_type="sawlog",
    land_type="timber",
    grp_by="SPCD",
)

Private forest land

pyfia.volume(
    db,
    land_type="forest",
    area_domain="OWNGRPCD = 40",
)

See also

• Grouping results — break estimates down by category
• How FIA estimation works — land and tree classifications in depth