FLORIDA GEOGRAPHIC DATA LIBRARY DOCUMENTATION
VERSION 2003, RELEASED NOVEMBER, 2002.
FLORIDA FOREST INVENTORY AND ANALYSIS
Geodataset Name: FLFIA Geodataset Type: SHAPE Geodataset Feature: POINT
GENERAL DESCRIPTION:
This dataset contains data collected from the forest inventory and analysis sampling points in the State of Florida.
DATA SOURCE(S): USDA Forest Service (source data), converted to
spatial dataset by FGDL staff (see contact
information below)
SCALE OF ORIGINAL SOURCE MAPS: Unknown
DATE OF AUTOMATION OR SOURCE: 1999
GEODATASET EXTENT: State of Florida
FEATURE ATTRIBUTE TABLES:
Datafile Name: FLFIA.DBF NAME WIDTH TYPE PRECISION CNTY_PLT 10 DECIMAL - COUNTY 4 DECIMAL - PLTNUM 4 DECIMAL - OWNER 3 DECIMAL - TYPECUR 3 DECIMAL - TYPOLD 3 DECIMAL - STDAGE 4 DECIMAL - STDSIZE 3 DECIMAL - STORCUR 3 DECIMAL - STOROLD 3 DECIMAL - SITECL 3 DECIMAL - SI 3 DECIMAL - SIAGE 3 DECIMAL - GLUCUR 3 DECIMAL - GLUOLD 3 DECIMAL - BA 5 DECIMAL - SLOPE 4 DECIMAL - ASPECT 4 DECIMAL - PHYSIO 3 DECIMAL - TREATOP 3 DECIMAL - INHIBPC 3 DECIMAL - NONSTPC 3 DECIMAL - GRSTKPC 5 DECIMAL - ALSTKPC 5 DECIMAL - REMPER 5 DECIMAL - EXPACR 7 DECIMAL - EXPVOL 7 DECIMAL - EXPGRO 7 DECIMAL - EXPMOR 7 DECIMAL - EXPREM 7 DECIMAL - LONG 9 DECIMAL - LAT 9 DECIMAL - DESCRIPT 50 CHARACTER - DESCRIPT2 50 CHARACTER -
FEATURE ATTRIBUTE TABLES CODES AND VALUES:
item item description
CNTY_PLT Unique identifier for every FIA plot in the state. First 1 to
3 digits refer to the county FIPS code and the last three digits
refer to the Plot Number (see PLTNUM item below).
COUNTY County code-The three-digit FIPS code number for each
county, parish, or other similar governmental unit in a State.
FIPS codes from the Bureau of the Census, 1980, are used.
PLTNUM Plot number-A four-digit plot number. Plot numbers are
unique within counties, but may be repeated within a
State or survey unit.
OWNER Ownership code-Legal owner of the plot land at the time
of the current inventory. In addition, this code indicates if
private lands have been leased to forest industry.
Code Owner Definition
11 National Forest Lands owned or administered by USDA Forest Service,
National Forest System.
12 Bureau of Land Lands owned or administered by
Management (BLM) USDI Bureau of Land Management
13 Indian Lands Tribal lands held in fee by the Federal Government but
administered for Indian tribal groups, and Indian
trust allotments. (Indian lands not administered
by the BIA are placed in the appropriate private
owner class.)
14 Other Federal Lands owned or administered by Federal agencies other
than the Forest Service or the BLM. These include
military reservations, National Parks, National Fish
and Wildlife Service lands, and Corps of Engineers lands.
15 State Lands owned by State governments, or lands leased by
State governmental units for more than 50 years.
16 County and Lands owned by county or municipal agencies,
Municipal or lands leased by these agencies for more
than 50 years.
20 Forest Industry Lands owned by companies or individuals operating
wood-using plants.
40 Farmer Lands owned by an individual who operates a farm (farm
operator), either participating in the work or directly
supervising the work. A farm is defined as land on
which agricultural operations are being conducted and
sale of agricultural products totals $1,000 or more
during the year.
50 Farmer Owned- Lands owned by a farm operator but leased to
Leased forest industry.
60 Other Private- Lands owned by private corporations other than
Corporate forest industry or farmers.
70 Other Private- Lands owned by individuals other than farmers.
Individual
80 Other Private- Lands owned by corporations but leased to
Corporate-Leased forest industry
90 Other Private- Lands owned by other private individuals but
Individual-Leased leased to forest industry.
If lease status is unknown, the owner codes for unleased (40, 60, 70) are recorded.
If corporate status is unknown, the owner codes for individual are recorded (70, 90).
TYPECUR Current forest type-The predominant forest type of the area
where the plot is located. This type is based on the tree species that
form a plurality of all live stocking within the stand. In this two-digit
coded element, the first digit represents a general type group and the
second digit specifies an Eastwide standard type, as shown below.
These types come from the standard set of local forest types in the
Forest Service Handbook, with several types added. Not every type is
recognized in every State, and type names used in published reports
may differ from State to State. For example,the 1986 Indiana report
shows area in a type called lowland oak. In the data base,
the plots that represent this area are coded 61-swamp chestnut
oak-cherrybark oak. The assignment of a forest type to a stand depends
on the determination of stocking. Each FIA project has somewhat
different methods of assigning stocking. Information on how data are
assigned to these types for a particular State can be obtained directly
from the FIA project responsible for the inventory and from the
following publications or people:
Southeastern:
Contact Joseph F. Glover, Southeastern Forest Experiment Station
Type Forest Type group or
group type forest type name
00 White - Red - Jack Pine
01 Jack pine
02 Red pine
03 White pine
04 White pine - hemlock
05 Hemlock
06 Scotch pine
07 Ponderosa pine
10 Spruce - Fir
11 Balsam fir
12 Black spruce
13 Red spruce - balsam fir
14 Northern white-cedar
15 Tamarack
16 White spruce
17 Norway spruce
18 Larch
19 Red spruce
20 Longleaf - Slash Pine
21 Longleaf pine
22 Slash pine
30 Loblolly - Shortleaf Pine
31 Loblolly pine
32 Shortleaf pine
33 Virginia pine
34 Sand pine
35 Eastern redcedar
36 Pond pine
37 Spruce pine
38 Pitch pine
39 Table-mountain pine
40 Oak - Pine
41 White pine - northern red oak - wash
42 Eastern redcedar - hardwood
43 Longleaf pine - scrub oak
44 Shortleaf pine - oak
45 Virginia pine - southern red oak
46 Loblolly pine - hardwood
47 Slash pine - hardwood
49 Other oak - pine
50 Oak - Hickory
51 Post oak - black oak - bear oak
52 Chestnut oak
53 White oak - red oak - hickory
54 White oak
55 Northern red oak
56 Yellow-poplar - white oak - northern red oak
57 Southern scrub oak
58 Sweetgum - yellow-poplar
59 Mixed central hardwoods
60 Oak - Gum - Cypress
61 Swamp chestnut oak - cherrybark oak
62 Sweetgum - Nuttall oak - willow oak
63 Sugarberry - American elm - green ash
65 Overcup oak - water hickory
66 Atlantic white cedar
67 Baldcypress - water tupelo
68 Sweetbay - swamp tupelo - red maple
69 Palm-mangrove - other tropical
70 Elm - Ash - Cottonwood
71 Black ash - American elm - red maple
72 River birch - sycamore
73 Cottonwood
74 Willow
75 Sycamore - pecan - American elm
76 Red maple - lowland
79 Mixed lowland hardwoods
80 Maple - Beech - Birch
81 Sugar maple - beech - yellow birch
82 Black cherry
83 Black walnut
84 Red maple - northern hardwood
87 Red maple - upland
88 Northern hardwood - reverting field
89 Mixed northern hardwoods
90 Aspen - Birch
91 Aspen
92 Paper birch
93 Gray birch
94 Balsam poplar
99 99 Nonstocked
TYPEOLD Old forest type-Forest type at the previous survey.
Criteria for assigning types and codes are the same as for
TYPCUR. TYPOLD is zero for new or temporary plots.
STDAGE Stand age-The age (in years) of the stand the plot is in. If
actual age is unavailable or the stand has a mix of ages,
999 is entered. Any inventory dated 1983 or later will
contain stand ages recorded to the nearest year. For some older
inventories, stand age was recorded in 10- or 20-year age classes
and the value recorded is the center of the age class.
STDSIZE Stand size class-A classification of forest land based on
the predominant stocking by the size of all live trees
present on the plot. The d.b.h. range for poletimber trees
is from 5.0 to 8.9 inches for softwoods and from 5.0 to 10.9
inches for hardwoods. Sawtimber trees are 9 inches d.b.h. or
larger for softwoods and 11 inches d.b.h. or larger for hardwoods.
Seedling and sapling trees are smaller than 5 inches d.b.h.
Stand size class is determined by the percent stocking represented
by various size trees. More detailed information on how stand
size class is determined from plot data in a particular State
can be obtained directly from the FIA project responsible for
the inventory and from the following publications or people:
Southeastern:
Contact Joseph F. Glover, Southeastern Forest Experiment Station
Code Stand size class Definition
1 Sawtimber Stands with an all live stocking value of
at least 16.7 on which more than 50 percent
of the stocking is in trees 5 inches d.b.h.
or larger, and the stocking of sawtimber
size trees is equal to or greater than the
stocking of poletimber size trees.
2 Poletimber Stands with an all live stocking value of
at least 16.7 on which more than 50 percent
of the stocking is in trees 5 inches d.b.h.
or larger, and the stocking of sawtimber
size trees is less than the stocking of
poletimber size trees.
3 Seedling-sapling Stands with an all live stocking value of
at least 16.7 on which at least 50 percent
of the stocking is in trees less than 5
inches d.b.h.
4 Non-stocked Stands with an all live stocking value of
less than 16.7.
STORCUR Current stand origin-The origin of the stand in which the plot is
located (planted or natural). In a planted stand, most of the trees
that define the stand size class and forest type must have
originated from planting or direct artificial seeding.
Code Current stand origin
1 Natural stands
2 Planted stands
STOROLD Old stand origin-Same as STORCUR at the time of the last
inventory. STOROLD is zero for new or temporary plots.
Code Current stand origin
1 Natural stands
2 Planted stands
SITECL Site productivity class-A classification of timber land in
terms of inherent capacity to grow crops of industrial wood.
The class identifies the average potential growth in cubic
feet/acre/year (trees 5 inches d.b.h. or larger to a 4-inch top)
and is based on the culmination of mean annual increment of
fully stocked natural stands.
Code Site productivity class
1 225+ cubic feet/acre/year
2 165-224 cubic feet/acre/year
3 120-164 cubic feet/acre/year
4 85-119 cubic feet/acre/year
5 50-84 cubic feet/acre/year
6 20-49 cubic feet/acre/year
SI Site index-Site index (in feet) of the stand in which the plot is
located. A site index of 100 or more is recorded as 99.
SIAGE Site index base age-The base age of the site index curves
used to get Site index.
GLUCUR Current land use class-A classification that indicates the
basic biological potential of the land and its current use and
legal status. Initially, land is broken into two broad classes
(forest and nonforest). These broad classes are separated into
the more specific classes that are actually coded.
Code Current land use class
20 Timberland
25 Reserved Timberland
40 Other Forest Land
45 Reserved Other Forest Land
60 Nonforest Land
91 Census Water
Land class Definition
Forest Land Land currently growing forest trees of any size with
a total stocking value of at least 16.7 (see element
27: ALSTKP for the definition of stocking), or lands
formerly forested, currently capable of becoming forest
land, and not currently developed for nonforest uses.
These lands must be a minimum of 1 acre in area.
Roadside, streamside, and shelterbelt strips of timber
must have a crown width of at least 120 feet to qualify
as forest land. Unimproved roads, trails, streams, and
clearings within forest areas are classified as forest
land if they are less than 120 feet wide. Recently
clearcut areas that are currently nonstocked are
classed as forest land unless they are being used for
a nonforest use such as agriculture. Forest land is
divided into two categories (timberland and other forest
land), and both of these categories may be further
classified as reserved if harvesting of trees is
prohibited by statutory or administrative restrictions.
Timberland Forest land that is producing or capable of producing
crops of industrial wood. This land should be capable
of producing 20 cubic feet of industrial wood per acre
per year. Thisincludes all land formerly called
commercial forest land.
Other Forest Forest land not capable of producing crops of
Land industrial wood. This may be the result of adverse
site conditions such as sterile soils, dry climate,
poor drainage, high elevation, and rockiness. Trees
on these sites are usually of poor form, small size,
or inferior quality and consequently are not used
for industrial products. These sites often contain
tree species that are not currently used for
industrial wood production. (These lands were called
unproductive forest in previous reports.)
Reserved Forest Forest lands that have statutory or administrative
Land restrictions prohibiting the harvest of trees.
Examples include land within the National
Wilderness Preservation System, Research Natural
Areas, National Parks and Monuments, and State Parks.
In National Forests, reserved forest lands are referred
to collectively as withdrawn forest land. This
classification of reserved can be given to either
timberland or other forest land.
Nonforest Land Land that has never supported forests or land formerly
forested but now developed for uses such as agriculture,
residence, commerce, industry, city parks, or improved
roads. If located within forest areas, unimproved roads
and nonforested strips must be more than 120 feet wide,
and clearings and other openings in a forest area must
be more than 1 acre to qualify as nonforest land.
Nonforest land also includes streams, sloughs, estuaries,
and canals more than 120 feet wide but less than one-
eighth of a mile (660 feet) wide, or lakes, reservoirs,
and ponds 1 to 40 acres in size.
Census Water Streams, sloughs, estuaries, and canals more than one-
eighth of a statute mile (660 feet) wide, and lakes,
reservoirs, and ponds more than 40 acres in size.
GLUOLD Old land use class-Same as GLUCUR at the time of the
last inventory. GLUOLD is zero for new or temporary plots.
Code Old land use class
20 Timberland
25 Reserved Timberland
40 Other Forest Land
45 Reserved Other Forest Land
60 Nonforest Land
91 Census Water
BA Basal area-The summed-cross sectional area at breast
height of all live trees 1.0 inches d.b.h. or larger on the plot.
This item is usually measured by variable radius plot
(prism) sampling and recorded in square feet per acre.
SLOPE Slope-The average percentage of the deviation from the
horizontal over the sample acre. Valid values are 0 through
99.
ASPECT Aspect-The direction of drainage for most of the plot,
recorded as the azimuth of this direction. Valid values are
0 through 360. 0 is only valid when slope is also 0.
PHYSIO Physiographic class-A measure of soil and water condi-
tions that affect tree growth on the plot.
Code Physiographic class Definition
3 Xeric Very dry soils where excessive drainage
seriously limits both growth and species
occurrence.
4 Xeromesic Moderately dry soils where excessive
drainage limits growth and species
occurrence to some extent.
5 Mesic Deep, well-drained soils. Growth and
species occurrence limited only by
climate.
6 Hydromesic Moderately wet soils where insufficient
drainage or infrequent flooding limits
growth and species occurrence to some
extent.
7 Hydric Very wet sites where excess water
seriously limits both growth and
species occurrence.
TREATOP Treatment opportunity class-Identifies the physical
opportunity to improve stand conditions by applying
management practices. The 11 classes are defined as follows:
Treatment
Code opportunity Definition
class
1 Regeneration The area is characterized by the absence of a
without site manageable stand because of inadequate
preparation stocking of growing stock. Growth will be
much below the potential for the site if the
area is left alone. Prospects are not good for
natural regeneration. Artificial regeneration
will require little or no site preparation.
2 Regeneration The area is characterized by the absence of a
with site manageable stand because of inadequate stocking
preparation of growing stock. Growth will be much below the
potential for the site if the area is left alone.
Either natural or artificial regeneration will
equire site preparation.
3 Stand The area is characterized by stands of undesirable,
conversion chronically diseased, or off-site species. Growth
and quality will be much below the potential for
the site if the area is left alone. The best
prospect is for conversion to a different forest
type or species.
4 Thinning The stand is characterized by a dense stocking of
seedlings and growing stock. Stagnation appears likely if left
saplings alone. Stocking must be reduced to help crop trees
attain dominance.
5 Thinning The stand is characterized by a dense stocking of
poletimber growing stock. Stocking must be reduced to
prevent stagnation or to confine growth to
selected, high quality crop trees.
6 Other The stand is characterized by an adequate stocking
stocking of seedlings, saplings, and/or poletimber
control growing stock, mixed with competing vegetation
either overtopping or otherwise inhibiting the
development of crop trees. The undesirable material
must be removed to release overtopped trees; to
prevent stagnation; or to improve composition, form,
or growth of the residual stand.
7 Other The stand would benefit from other special treat-
intermediate ments such as fertilization to improve the
treatments growth potential of the site, and pruning to
improve the quality of individual crop trees.
8 Clearcut The area is characterized by a mature or over-
harvest mature sawtimber stand of sufficient volume to
justify a commercial harvest. The best prospect
is to harvest the stand and regenerate.
9 Partial cut The stand is characterized by poletimber or saw-
harvest timber size trees with sufficient merchantable
volume for a commercial harvest, which will
meet intermediate stand treatment needs or prepare
the stand for natural regeneration. The stand is
of a favored species composition and may be even or
uneven aged. Included are such treatments as
commercial thinning, seed tree or shelterwood
regeneration, and use of the selection system to
maintain an uneven age stand.
10 Salvage The stand is characterized by excessive damage to
harvest merchantable timber because of fire, insects,
disease, wind, ice, or other destructive agents.
The best prospect is to remove damaged or
threatened material.
11 No treatment Stand is characterized by an adequate stock of
growing-stock trees in reasonably good condition.
INHIBPC Percent inhibiting vegetation-Percent of the area covered by inhibiting
vegetation. A value of 99 is recorded for areas that are entirely (100 percent)
covered with inhibiting vegetation. This item is not available for States
inventoried by the Northeastern Forest Experiment Station.
NONSTPC Percent nonstocked-Percent of the area in which the plot is located that
is nonstocked with all live trees (0-100 percent basis). A value of 99 is re-
corded for plots that have no live stocking (100 percent nonstocked). This
item is not available for States inventoried by the Northeastern Forest
Experiment Station.
GRSTKPC Growing stock stocking-Stocking of the plot by growing-stock trees.
Data are in the form of an absolute stocking value (0-167). More detailed
information on how stocking values are determined from plot data in a
particular State can be obtained directly from the FIA project responsible
for the inventory and from the following publications or people:
Southeastern:
Contact Joseph F. Glover, Southeastern Forest Experiment Station
ALSTKPC All live stocking-Stocking of the plot by live trees of any species. Data
are in the form of absolute stocking value (0-167). See element 26,
GRSTKPC, for a list of publications that describe how stocking values are
determined from plot data. The following classification of plots based on
the stocking value (all live and/or growing stock) is common in FIA reports.
Overstocked Stands in which stocking of all live trees is 130.0 or more.
Fully stocked Stands in which stocking of all live trees is from 100.0
to 129.9.
Medium stocked Stands in which stocking of all live trees is from 60.0 to
99.9.
Poorly stocked Stands in which stocking of all live trees is from 16.7 to
59.9.
Nonstocked Stands in which stocking of all live trees is less than 16.7.
REMPER Remeasurement period-The number of years between measurements
of remeasured plots. This item is zero for new or temporary plots. Re-
measurement period is based on the number of growing seasons between
measurements. Allocation of parts of the growing season by month is
different for each FIA project. Contact the individual FIA project for
information on how this is done for a particular State.
EXPACR Area expansion factor-The number of acres the plot represents for
estimating area variables such as ownership and land cover class.
The sum of EXPACR over all record 20's in a file is the total land and
water area of the State.
EXPVOL Volume expansion factor-The number of acres that the plot represents
for estimating current volume and number of trees. Volume will be
"expanded" over the appropriate acreage by multiplying EXPVOL x each
volume/acre element on the tree record (record type 30). Total volume in
a State is calculated by summing the expanded volume estimates from all
trees on all plots in an EWDB file. Number of trees is expanded in a similar
way.
EXPGRO Growth expansion factor-The number of acres that the plot represents
for estimating growth. Growth will be "expanded" over the appropriate
acreage by multiplying EXPGRO x each growth/acre element on the tree
record (record type 30). Total growth in a State is calculated by summing
these expanded estimates from all trees on all plots in an EWDB file. Some
plots will not have a value in this field. In some State inventories, growth
is only estimated on remeasured plots. In such cases, this item would be zero
for new or temporary plots.
EXPMOR Mortality expansion factor-The number of acres that the plot represents
for estimating mortality. Mortality will be "expanded" over the appropriate
acreage by multiplying EXPMOR x each mortality/acre element on the tree
record (record type 30). Total mortality in a State is calculated by summing
these expanded estimates from all trees on all plots in an EWDB file. Some
plots will not have a value in this field. In some State inventories,
mortality is only estimated on remeasured plots. In such cases, this item
would be zero for new or temporary plots.
EXPREM Removals expansion factor-The number of acres that the plot represents
for estimating removals. Removals will be "expanded" over the appropriate
acreage by multiplying EXPREM x each removals/acre element on the tree
record (record type 30). Total removals in a State is calculated by summing
these expanded estimates from all trees on all plots in an EWDB file. Some
plots will not have a non-zero value in this field. In some State inventories,
removals are only estimated on remeasured plots. In such cases, this item would
be zero for new or temporary plots.
LONG Longitude-The longitude of the plot recorded to the nearest
100 seconds.
LAT Latitude-The latitude of the plot recorded to the nearest 100
seconds.
DESCRIPT Based on GLUCUR item.
DESCRIPT2 Based on TYPECUR, if none listed 'UNKNOWN' value entered.
Core Species occurrence
table by FIA project
SPP Common name Genus Species SPPGRP group NC NE SO SE
043 Atlantic white-cedar Chamaecyparis thyoides 9 2 . X X X
060 redcedar Juniperus sp. 9 2 . X . X
107 sand pine Pinus clausa 3 1 . . X X
110 shortleaf pine Pinus echinata 2 1 X X X X
111 slash pine Pinus elliottii 1 1 . . X X
115 spruce pine Pinus glabra 3 1 . . X X
121 longleaf pine Pinus palustris 1 1 . . X X
128 pond pine Pinus serotina 3 1 . X X X
131 loblolly pine Pinus taeda 2 1 X X X X
221 baldcypress Taxodium distichum 8 2 X X X X
222 pondcypress Taxodium distichum 8 2 . X . X
var. nutans
311 Florida maple Acer barbatum 16 4 . . X X
313 boxelder Acer negundo 26 3 X X X X
316 red maple Acer rubrum 17 3 X X X X
341 ailanthus Ailanthus altissima 28 3 X X X X
370 birch sp. Betula sp. 27 4 . . . X
391 American hornbeam, Carpinus caroliniana 28 4 X X X X
musclewood
400 hickory sp. Carya sp. 14 4 . X X X
451 southern catalpa Catalpa bignonioides 28 4 . . . X
460 hackberry sp. Celtis sp. 26 3 . . . X
471 eastern redbud Cercis canadensis 28 3 X X X X
491 flowering dogwood Cornus florida 27 4 X X X X
521 common persimmon Diospyros virginiana 27 4 X X X X
531 American beech Fagus grandifolia 18 4 X X X X
540 ash Fraxinus sp. 21 4 . X . X
552 honeylocust Gleditsia triacanthos 27 4 X X X X
555 loblolly-bay Gordonia lasianthus 26 3 . . . X
591 American holly Ilex opaca 27 4 . X X X
602 black walnut Juglans nigra 25 4 X X X X
611 sweetgum Liquidambar styraciflua 19 3 X X X X
621 yellow-poplar Liriodendron tulipifera 24 3 X X X X
652 southern magnolia Magnolia grandiflora 26 3 . . X X
653 sweetbay Magnolia virginiana 26 3 . X X X
660 apple sp. Malus sp. 28 4 X X X X
680 mulberry sp. Morus sp. 27 4 . . . X
691 water tupelo Nyssa aquatica 20 3 X X X X
692 ogeechee tupelo Nyssa ogeche 28 4 . . . X
693 blackgum Nyssa sylvatica 20 3 X X X X
694 swamp tupelo Nyssa sylvatica var. 20 3 X . X X
biflora
701 eastern hophornbeam, Ostrya virginiana 28 4 X X X X
ironwood
711 sourwood Oxydendrum arboreum 28 4 . X X X
721 redbay Persea borbonia 26 3 . . X X
731 sycamore Platanus occidentalis 26 3 X X X X
740 cottonwood Populus spp. 22 3 . X X X
762 black cherry Prunus serotina 26 3 X X X X
802 white oak Quercus alba 10 4 X X X X
812 southern red oak Quercus falcata var. 13 4 X X X X
falcata
813 cherrybark oak,
swamp red oak Quercus falcata var. 11 4 X X X X
pagodaefolia
819 turkey oak Quercus laevis 28 4 . . X X
820 laurel oak Quercus laurifolia 13 4 . X X X
822 overcup oak Quercus lyrata 12 4 X X X X
824 blackjack oak Quercus marilandica 13* 4 X X X X
825 swamp chestnut oak Quercus michauxii 10 4 X X X X
826 chinkapin oak Quercus muehlenbergii 10 4 X X X X
827 water oak Quercus nigra 13 4 X X X X
831 willow oak Quercus phellos 13 4 X X X X
834 Shumard oak Quercus shumardii 11 4 X X X X
835 post oak Quercus stellata 12 4 X X X X
838 live oak Quercus virginiana 12 4 . . X X
840 bluejack oak Quercus incana 28 4 . X X X
899 scrub oak Quercus sp. 28 4 . . . X
920 willow Salix sp. 26 3 . X X X
931 sassafras Sassafras albidum 26 3 X X X X
950 basswood Tilia sp. 23 3 . X . X
970 elm Ulmus sp. 26 3 . X . .
983 chinaberry Melia azedarach 28 4 . . X X
984 water-elm Planera aquatica 28 4 . . X X
985 smoketree Cotinus obovatus 28 4 . . X .
999 unknown or not listed 28 4 X . X X
*Blackjack oak is given a species group code of 28 in States inventoried by the Southeastern FIA
project.
USER NOTES:
The FIATREE1.DBF and FIATREE2.DBF tables can be joined to the FLFIA.DBF table using the CNTY_PLT item,
which is common to all three tables. These tables are located in the FLFIA_TABLES folder
of your FGDL CD.
ESTIMATION PROCEDURES
Users of the Eastwide Data Base need a basic understanding of FIA sampling and estimation procedures
to understand the type of data available. Here, we present a general discussion of these procedures.
Specific sampling methods differ among regions and even among States within a region. Publications
cited in this manual give more detailed information about methods used by each region. If you need
more information about sampling procedures for a specific State, contact the FIA project responsible
for that State's inventory.
Each State inventory begins with the interpretation of an aerial-photo sample that classifies the land
by various photo classes. The total area of a sample comes from outside sources (usually Bureau of
Census reports). The photo classes used are based on land use (pasture, cropland, urban, etc.). For
forested land, more detailed classes are sometimes defined based on criteria such as forest type,
volume per acre, stand size, stand density, ownership, and stand age. Then, ground plots are measured
to adjust the aerial photo sample for changes since the date of photography and misclassification and
to obtain estimates that cannot be made from the aerial photography. The photo classification of these
ground plots, together with the area estimates from the photo sample, is used to assign area expansion
factors to all ground plots. These area expansion factors are used to expand values observed on the
plot from a per acre basis to a population basis. An area expansion factor is basically the area (in
acres) that the plot represents for estimation purposes. The sampling area, or level at which
expansion factors are assigned, is different from State to State, as is the scheme used to assign
photo-interpretation classes. For the details of how these expansion factors were assigned to the
ground plots for a particular State, contact the appropriate FIA project.
FIA plots are designed to cover a 1-acre sample area; however, not all trees on the acre are measured.
Various arrangements of fixed radius and variable radius (prism) sample points are used to select
sample trees to be measured. Ground plots may be new plots that have never been measured, or
remeasurement plots that were measured in the previous inventory. For all plots, several
observations are recorded for each sample tree, including its diameter breast height (d.b.h.),
species, and other measurements that enable us to predict the tree's volume, growth rate, and quality.
These tree measurements form the basis of the data on the tree records in the EWDB.
Some of the data items in the EWDB come directly from field measurements; others are computed from
tree measurements. Net cubic foot volume is a computed item. Each FIA project uses some type of volume
equation to compute this volume based on d.b.h. and other tree and stand attributes. Although
equations differ from State to State, they were all designed to compute the same volume.
One important computed item is the tree expansion factor VOLFAC. This item expresses the number of
trees per acre that each sampled tree represents in the current inventory. It is the inverse of the
size of the plot the tree was sampled on. For example, if the plot design samples trees under 5 inches
d.b.h. on a single one-one hundredth-acre fixed radius plot, this item would have the value
100 trees per acre for a tree less than 5 inches d.b.h. If trees 5 inches d.b.h. and larger are
sampled with ten 37.5 BAF (English) prism points, as is common with FIA plots, the expansion factor
would depend on the d.b.h. of the tree. Under such a sample, a 14.0-inch tree would have an expansion
factor of 3.51 trees per acre, again the inverse of the plot size*.
* The plot size of a 14.0-inch tree on a single 37.5 BAF (English) prism plot would be: (14.02 x
pi)/(37.5 x 22 x 122) = 0.0285 acres. The plot size of this tree on a 10-point cluster would be 10
times this or 0.285 acres, producing an expansion factor of 3.51.
Two other computed expansion factors are in the data base: MORTFAC and REMVFAC. They are used to
compute mortality and removals. The mortality factor (MORTFAC) expresses an estimate of how many trees
per acre of annual mortality are represented by a given sample tree. This factor is the number of
trees per acre of annual mortality that the sample tree represents. In sample designs that have
remeasurement plots, this value is zero for a tree that did not die over the remeasurement period. For
trees that did die, MORTFAC is a function of the tree expansion factor and the remeasurement period.
Some State inventories also estimate mortality from new ground plots. In these cases, mortality is
estimated from either a mortality prediction equation that predicts the probability that a tree will
die over some time period, or from a field estimate of mortality based on the measurement of dead
trees and an estimate of when they died.
The removals factor (REMVFAC) is computed and used like MORTFAC. REMVFAC is the number of trees per
acre of annual removals that the sample tree represents. It is computed based on observations of trees
cut on either new or remeasured plots, depending on the inventory design. None of the Eastern FIA
projects use removals prediction equations to estimate removals.
The items in the plot record are either observations of a specific condition at the plot center or
estimates of average conditions on the acre sampled by the plot. Ownership is an example of a specific
condition recorded at plot center, rather than averaged over the plot. If a plot area overlaps more
than one owner, the ownership at plot center determines the recorded ownership class. Basal area is an
example of an item averaged over the entire plot. If the plot falls in two stands with different basal
areas, the value recorded in BACUR will represent their average basal area. In some State inventories,
plots falling on more than one stand are shifted into one stand. EWDB users concerned about field
procedures should check with the FIA project for more information.
We have tried to make the data in the EWDB as consistent as possible from one State to another.
Therefore, although differences in field and estimation procedures do exist between States, the data
in the EWDB for different States are compatible. The minor differences that do exist should have
little or no impact on most uses of this data.
Creation of the FIATREE1 and FIATREE2 tables
The SPP_### items in the FIATREE tables were found by dividing the total of live trees of each species
in each plot by the total trees sampled in the plot. Live trees were selected from
the status item found in the original "tree record" text file obtained from the USDA Forest Service.
Status items include: Live, Dead (not salvageable), Cut, Salvageable dead and Snag (special code for
wildlife den trees used only by the Northeastern FIA project). Only trees with status item "Live" were
used. For more information on the FIA data, visit the reference websites.
Accuracy Standards
Forest inventory plans are designed to meet sampling error standards for area, volume, growth, and
removals provided in the Forest Service Handbook. These standards, along with other guidelines, are
aimed at obtaining comprehensive and comparable information on timber resources for all parts of the
country. In the East, FIA inventories are commonly designed to meet the specified sampling errors at
the State level at the 67-percent confidence limit (one standard error). A 3-percent error per 1
million acres of timberland is the maximum allowable sampling error for area. A 5-percent error per 1
billion cubic feet of growing stock on timberland is the sampling error goal for volume, removals, and
net annual growth.
Caution: FIA inventories are extensive inventories that provide reliable estimates for large sampling
areas. As data are subdivided into smaller and smaller areas, such as a geographic unit or a county,
the sampling errors increase and the reliability of the estimates decreases. For example, a State with
5 million acres of timberland would have a maximum allowable sampling error for area of 1.3 percent, a
geographic unit within that State with 1 million acres of timberland would have a 3.0 percent maximum
allowable sampling error, and a county within that State with 100 thousand acres would have a 9.5
percent maximum allowable sampling error at the 67-percent level.
Scale of the original aerial photos used to generate the location of each sampling point is unknown.
The points in this coverage were generated using Lattitude and Longitude points given in the FLFIA.PAT
(using the generate command in Arc/Info). See Data Lineage Summary for further explanation.
Scale is an important factor in data usage. Certain scale datasets are not suitable for some project,
analysis, or modeling purposes. Please be sure you are using the best available data.
Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are
familiar with your data before using it for projects or analyses. Every effort has been made to supply
the user with data documentation. For additional information, see the References section
and the Data Source Contact section of this documentation. For more information regarding scale and
accuracy, see our web pages at:
http://www.geoplan.ufl.edu/education.html
FGDL QUALITY ASSURANCE STATUS:
- set tolerances to geoplan standards - dropped items MDATE, ADFOR, UNIT, and STATE from the original data downloaded from the web. - added item CNTY_PLT based on the FIPS county code and the plot number for each plot. The purpose of this was to get around the fact that plot numbers reapeated in different couties. The CNTY_PLT item is therefore a unique identifier for each plot, and can be used in place of the FLFIA-ID item as such. In fact, to facilitate this, the FLFIA-ID item was calculated to be equal to the CNTY_PLT item. - added item DESCRIPT based on GLUCUR item - added item DESCRIPT2 based on TYPECUR item - dropped 175 records from the coverage. These records had no Lattitude or Longitude data and therefore could not be generated as accurate points. The only item fields that were populated for these records were CNTY_PLT, COUNTY, PLTNUM, GLUCUR, GLUOLD and EXPACR
REFERENCES: http://www.srsfia.usfs.msstate.edu/ewdata/ewrec.htm#
DATA LINEAGE SUMMARY:
FIA procedures (see above- User Notes) were completed in Florida during 1995 and summarized for counties, plots, and trees. The data is available to the public on the web at: http://www.srsfia.usfs.msstate.edu/ewdata/ewrec.htm#. Data for Florida (1995) is in the form of three comma-delineated ascii files containing data for county, plot, or tree records. Geoplan downloaded this data from the web in December 1999 and developed a program written in Arc Macro Language to put the data in the form we desired. The Generate command in Arc/Info was used to create a point coverage. The data from the comma-delineated ascii file for plot records was then placed in the coverage point attribute table. The tree records were used to create the FIATREE1.DBF and FIATREE2.DBF tables (see User Notes above). The comma-delieated file for tree records contains data for individual trees. Rather than have a copious amount of records, GeoPlan decided to summarize some of the tree data for each plot. This was done by using the FREQUENCY command in Arc/Info for the SPP (species) data (see list above) for each tree record. The frequency data was then converted into a percentage of live trees in each species in each plot, and each species code (see list above) for species that occured in the Florida FIA procedure was turned into an item in either the FIATREE1.DBF or FIATREE2.DBF. Two tables were created in order to place a limit on the number of items in each table (35 species items are in both FIATREE tables). Data does not exist for every plot, so when the tables are linked to the FLFIA.DBF, not every record will be populated in every species field. FIATREE1.DBF and FIATREE2.DBF can be linked to the FLFIA.DBF using the CNTY_PLT item, which is common to all three tables.
MAP PROJECTION PARAMETERS
PROJECTION ALBERS DATUM HPGN UNITS METERS SPHEROID GRS1980 PARAMETERS 1st standard parallel 24 0 0.000 2nd standard parallel 31 30 0.000 central meridian -84 00 0.000 latitude of projection`s origin 24 0 0.000 false easting (meters) 400000.00000 false northing (meters) 0.00000
DATA SOURCES CONTACT(S):
NOTE: Original data and information regarding the data
can be found at USDA Forest Service:
http://www.srsfia.usfs.msstate.edu/ewdata/ewrec.htm#
Information regarding the data conversion can be found at:
Name: FLORIDA GEOGRAPHIC DATA LIBRARY
Abbr. Name: FGDL
Address: Florida Geographic Data Library
431 Architecture Building
PO Box 115706
Gainesville, FL 32611-5706
Web site: http://www.fgdl.org
Contact Person: FGDL Data Manager
Email: data@fgdl.org
FGDL CONTACT:
Name: Florida Geographic Data Library
Abbr. Name: FGDL
Address: Florida Geographic Data Library
431 Architecture Building
PO Box 115706
Gainesville, FL 32611-5706
Fax: (352) 846-3124
Web site: http://www.fgdl.org
Contact FGDL:
Technical Support: http://www.fgdl.org/fgdlfeed.html
FGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.html
FGDL Mailing Lists: http://www.fgdl.org/fgdl-l.html
For FGDL Software: http://www.fgdl.org/software.html