EPA/600/3-89/065
July 1989
FOREST SURVEY METHODS USED IN THE
USDA FOREST SERVICE
Prepared by:
JOHN W. HAZARD, Statistician, Statistical Consulting Service,
Bend, Oregon 97701
BEVERLY E. LAW, Program Analyst, National Council of the
Paper Industry for Air & Stream Improvement, U.S. Environmental
Protection Agency, Environmental Research Laboratory, Corvallis,
Oregon 97333
Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Corvallis, OR 97333
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NOTICE
The information in this document has been funded wholly or in
part by the U.S. Environmental Protection Agency under IAG #
DW12931230 to the USDA Forest Service and Contract #68-03-3439 to
Kilkelly Environmental Associates. It has been subject to the
agency's peer and administrative review, and it has been approved
for publication as an EPA document.
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Forest Survey Methods Used in the USDA Forest Service
by
John W. Hazard and Beverly E. Law
1. INTRODUCTION
The purpose of this report is to describe the sampling
methodology of the Forest Inventory and Analysis (FIA) survey
system and the National Forest System (NFS) inventories.
in the past twenty years, there has been an increasing need for
forest resource inventory data to contribute to various
objectives of different agencies and organizations. Monitoring
forest health is one area of interest for which existing forest
survey data may be useful. A knowledge of sampling methodology
used to collect the data and kinds of data collected is important
to assess the usefulness of existing data to meet specific
objectives. There are also many opportunities for initiating
cooperative research and inventory efforts to build on existing
data pertaining to mutual areas of interest such as monitoring
forest health.
Many ongoing forest resource survey programs exist. In addition,
other agencies conduct independent surveys of range, soil, water,
wildlife, and other natural resources. However, we have confined
the scope of this report to surveys which focus primarily on
timber There are also many kinds of timber surveys, so we have
further limited our attention to those which provide the most
coverage of the timber resource. This excludes such surveys as
timber cruises, regeneration surveys, and insect infestation
surveys. Our intent is to identify the most current data bases
which extend over the entire U.S. timber resource and identify
and describe the sampling methodology used for each individual
survey system.
The USDA Forest Service has 16 survey units (7 for the FIA and 9
for the NFS). Some continuity exists among FIA and NFS surveys,
but they essentially have their own identities. Our descriptions
of these 16 survey units will show the commonalities and
differences among them.
The Forest Inventory and Analysis fFIAl System
The FIA system is under the USDA Forest Service Forest, Inventory
Economics, and Recreation Research Staff. The Experiment
Stations, through the 7 FIA geographic regions, are responsible
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for the surveys (see Fig. 1) . The surveys are usually performed
on a State-wide basis.
The FIA inventories have been in existence since 1930 and the
process has evolved through the establishment of accuracy
standards and standardization of terminology. Up until about
1955, the inventory concentrated on forest area and volume as
related to timber supply and production. After 1955, the
inventory considered additional forest attributes. The 1974
Resources Planning Act (RPA) required that the inventory provide
data on water, wildlife habitat, timber, and recreation on
forests and rangelands.
The objectives of FIA inventories are as follows: To provide a
comprehensive inventory and analysis of the renewable forest
resources for the RPA assessments; to provide information on
renewable forest resources for use by a diverse group of resource
managers (eg. State and regional agencies, industrial firms and
associations, colleges and universities, State legislative and
Congressional staffs, and others); and to develop and apply
scientific knowledge and technology in support of the inventory
and analysis.
FIA functions with national direction through the Forest Service
Directives. These directives specify minimum accuracy
requirements for the estimation of both forest area and volume
statistics , provide standard definitions of terminology,
identify standard operating procedures where appropriate,
identify minimal reporting requirements, and identify national
information needs that must be met (e.g. RPA data) by the FIA
units. Recently, national direction has resulted in multi-unit
data bases as well as a national FIA-RPA data base. An example
of a multi-unit data base is the Eastwide Data Base (Hansen, et
al). Procedures to maintain and update these are identified.
Thus FIA is a national activity with regional differences.
FIA projects conduct inventories on Federal, State, county, and
private timber lands, with certain exceptions of National Forest
(NF) lands and administratively reserved lands, such as National
Parks, National Wildlife Refuges, State Parks, etc. Exceptions
are listed below. Table 4, in Appendix 3, presents the inventory
responsibility of various owner classes by FIA region.
FIA Region Exceptions
Alaska A cooperative survey of FIA, BLM,
SCS and State of Alaska is conducted.
The maximum allowable error for area is 3% error per 1
million acres of timberland. A 5% error per 1 billion cu. ft.
growing stock on timberland for volume removals and net annual
growth is to be achieved as closely as possible.
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NFS does its own timber inventory with
compilation assistance from FIA. FIA
establishes vegetation inventory plots
on National Forest lands.
South and Southeast FIA inventories all ownerships including
National Forest lands, but excludes
Great Smoky Mts. National Park (NFS).
Northeast and FIA inventories all ownerships including
North Central National Forest lands in Region 9.
Pacific Northwest FIA inventories ownerships except
National Forest lands and in western
Oregon, where BLM inventories BLM lands.
FIA projects have partitioned their respective regions into
survey units. A survey unit is a geographical area which is
inventoried as a separate statistical population. These units
are usually defined by enumerating all counties, states, or
geographical regions within a well defined boundary. Exclusions
such as reserved timberland (for example, wilderness areas) are
delineated so that the exact acreage is known for each survey
unit prior to sampling. However, field measurements are not
taken on most areas of exclusion.
Sampling design. Data collection is normally based upon double
sampling for stratification. This includes the interpretation of
sample points on aerial photographs and subsampling a portion of
the points for verification and to obtain additional data on the
ground. Aerial photo points are normally laid out on a
systematic grid over the survey unit. Classification of points
on this grid provides estimates of forest area. These estimates
may be augmented with information from official records in the
case of public lands. The ground sample plots commonly consist
of a cluster of points spaced over 1 to 5 acres. The Alaska
ground sample plot has covered up to 20 acres. Measurements on
the ground plots provide estimates of stand and individual tree
attributes (see Appendix 1). These plots are generally permanent
and are remeasured on a 10 year cycle, except in areas of
relatively slow change, such as Alaska, where cycles may extend
to 20 years.
Sampling intensities vary among FIA regions and among survey
units. The aerial photo points range from 1 point per 190 acres
in the North Central region to 1 point per 1400 acres in parts of
Underlined words and phrases appearing in the text are
defined in Appendix 2. Terminology.
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the Pacific Northwest region. Sampling intensities of ground
plots range from 1 plot per 3000 acres to 1 plot per 10,000 acres
(1 point per 20,000 acres in Alaska). The frequency of ground
plots generally occur in proportion to the acres in different
strata.
The aerial photo interpretation phase of the inventory yields
information about land use, and frequently land cover, timber
volume classes, and forest type categories. The ground plots
yield specific information about the stand, the plot, individual
trees, and other vegetation.
On ground plots, vegetation data are collected at each point in
the cluster. Two general sampling rules are employed: 1) lesser
vegetation and small trees are measured or counted on a fixed
area around the point and 2) larger trees are sampled with
probability proportional to size (pps) i.e., on variable radius
plots (VRP). There are exceptions to the sampling rules. For
example, some FIA regions are using fixed radius plots for
remeasurement.
National Forest System Inventories
National Forest System inventories produce resource information
for developing, implementing, and monitoring National Forest
Management Plans, for RPA Assessments, and for Survey Reports.
The inventories are usually coordinated by an inventory section
or specialist in Regional Offices of the National Forest System.
National Forest System Regions do not necessarily coincide with
FIA regional boundaries (see Fig. 2). For example, the
Intermountain FIA region contains 4 NFS Regional Offices, 1, 2,
3, and 4. The basic survey unit on National Forest land is the
National Forest. Many resource inventories may be conducted on
each National Forest, e.g. timber, range, soils and geology,
plant life (including threatened and endangered species), fish
and wildlife (including threatened and endangered species),
natural water occurrences (including quality and quantity), and
quantitative data for determining species and community
diversity.
Some National Forests may exclude wilderness areas and research
natural areas from their timber inventories.
Sampling design. In some cases NFS inventories are conducted by
FIA using FIA procedures. In all areas where FIA does
inventories on NFS lands, the National Forests also do timber
inventories which are usually in the form of stand examinations.
In most cases, the NFS inventories its own lands, but many of the
procedures are very similar to FIA procedures. There is one
important difference between NFS and FIA procedures. The NFS does
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not currently use double sampling for stratification. Instead,
they use stratified random sampling or stratified systematic
sampling. The stratified sample gives an exact measurement of
land area by strata. Once a plot location has been selected, the
ground procedures and the kinds of data collected on the ground
are very similar to FIA (see proposed standardization of NFS
timber inventory data in Appendix 1). Sampling intensities are
often much higher than in the FIA system. The NFS is generally
moving away from the use of permanent inventory plots. This
could have some major implications for the ability to detect and
monitor subtle changes in forests over time.
Other Considerations
Survey designs for FIA regions and NFS Regions have traditionally
differed because of their different objectives. Methods have
also differed among FIA projects and among National Forest
Regions, due to differences in forest type, accessibility, and
contrasting philosophies among the units. In general, FIA
inventories are strategic in nature (monitoring for long range
trends and planning on large areas) while NFS inventories are
operational (short to mid range planning for specific areas).
All approaches present statistically sound designs.
These differences do, however, make it difficult to understand
and be knowledgeable of the inventory methods covering all
forests in the United States, Puerto Rico, and the American
Pacific Trust Islands. Another complicating factor is that
inventory methods have evolved over time as the need for new
information increases and more knowledge becomes available about
the resources.
In this report we have attempted to provide the most current
methodology. Previous methods, where applicable, will also be
presented.
2. SPECIFIC SAMPLING DESIGNS
Up to this point, general FIA and NFS methods have been
discussed. The following sections describe the specific sampling
designs of the 7 FIA regions and the 9 independent NFS Regions.
The information is organized geographically, by the 7 FIA
regions. Each section includes the NFS Regions that fall within
the FIA regional boundaries.
Alaska FIA Region
The Alaska FIA region includes the states of Alaska, Hawaii, and
the American Pacific Trust Islands (AMPAC). The Alaska FIA
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survey design is perhaps the newest and most flexible of the FIA
designs. It originated as a cooperative multi-resource inventory
among FIA, BLM, SCS, USGS and the State of Alaska. The different
objectives of these agencies require resource information on
everything from soils and ground shrubs to trees. The efficiency
of this design remains to be tested. NF land in Region 10 is
inventoried separately by NFS personnel. The FIA inventory cycle
is 10 years on areas of rapid change and up to 20 years for areas
of slow change.
The Alaska design recently has been a four phase sampling design,
in which 20 acre plots were interpreted or installed on LANDSAT
imagery (LS), high altitude photography (HAP), low altitude
photography (LAP) and on the ground (G) . Each phase was located
on a systematic grid which was a multiple of the next lower phase
of sampling. Grid intervals were:
Stage Grid size (meters)
LS 5K
HAP 10K
LAP 20K or 10K x 20K
G 40K
Photo scales on HAP are in the neighborhood of 1/60,000 and LAP
is 1/4,000 on the Tanana, 1/7000 on the Southeast and the Copper
River survey units.
Information measured on each photo stage of sampling has been the
proportion of the 20 acre plot falling in various land and
vegetation classes. The degree of resolution increased as the
scale increased. For example:
Stage Information Collected
LS Conifer and hardwood forest, nonforest, ice and snow
HAP Broader species and vegetation classes
LAP Crown widths, tree heights, etc. for use with aerial
volume tables
G Soil, ground vegetation, shrubs, and trees, etc.
The 20 acre ground plot had a 19 point grid subsample
superimposed on it. Varying degrees of information were measured
on 1 or more of these points.
The Tanana and Southeast Alaska survey units have been completed
using this new design. The field work for the Copper River unit
will be completed in 1989. Plans are now in place to fall back
to an earlier design to comply with FIA Washington Office
direction to complete the interior Alaska inventory quickly.
Prior to this new design, FIA conducted a double sampling for
stratification design evaluating one acre homogeneous areas (five
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acre areas in the Susitna River survey). The first phase sample
was systematically located and interpreted on aerial photographs.
The ground plots were 10 point cluster plots (VRP). Soils and
understory vegetation data were collected on each ground plot.
Hawaii and American Pacific Trust Islands (AMPAC)
The Hawaii and AMPAC FIA inventories have been the responsibility
of the PNW FIA project. Recently, they were transferred to the
Alaska FIA project. The survey unit is an island or group of
islands. The most recent inventory was the island of Kauai,
completed in 1986.
The design used was double sampling for stratification. Eight
hundred and fifty five photo points were arrayed on aerial
photos. Each point was photo interpreted (P.I.) by ownership,
land class, vegetation type, and zoning. There were 11 total
strata.
Sixty seven field plots were installed. Field plots were
variable radius plots (VRP), and varied in the number of points
per cluster. Timberland field plots contained 7 points and other
forest plots had 5.
The inventory design for the American Pacific Trust Islands has
been a highly specialized system to accommodate special
considerations of tropical forest inventory.
National Forest System
Region 10: Region 10 includes the Chatham, Stikine, and
Ketchikan areas. The inventory design on Stikine and Ketchikan
areas is a stratified systematic sample. Type maps exist which
stratify all stands into species types, stand size-class, volume
class, and stocking class strata. A 1.5 mile grid of field plots
is taken on productive forest land, and a 6.8 mile grid is
constructed over unproductive forest land. Field plots are 5
point VRP arrayed over 5 acres. Chatham area uses a pps design
with a sampling intensity of 1 point per 5 acres.
The 1988 Chugach National Forest inventory was a joint project of
FIA and NFS Region 10. Region 10 did the field work and FIA
performed the compilation and some analyses. The same methods
and design used on the Copper River Unit were used on the Chugach
National Forest.
Intermountain FIA Region
This region is the largest of the FIA regions (see Fig. 1). It
includes the states of Arizona, Colorado, Idaho, Montana, Nevada,
New Mexico, Utah, and Wyoming, and it includes 4 National Forest
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Regions, each with its own inventory system. The inventory cycle
for FIA and NFS inventories is 10 years.
FIA survey units are states or groups of counties. National
Forest lands and productive reserved lands are excluded. Yuma
county, Arizona and Eastern Colorado are excluded because they
are treeless.
The sampling design is double sampling for stratification. The
first phase sample is located on a 1000 meter grid. This grid is
tied into the Universal Transverse Mercator (UTM) grid, as are
many of the other FIA inventory grids. Each grid point is
located on an aerial photograph and photo interpreted into
ownership and land class strata. A subsample of the photo sample
is installed on the ground as field plots. This second phase
sample of field plots is on a 5000 meter grid, thus there is one
field plot for every 25 photo plots. A 1000 meter grid
translates into 1 photo point per 247.1 acres, and a 5000 meter
grid equals 1 field plot per 6177.6 acres.
Older inventories used temporary field plots, thus trend
information from remeasurement will not be recoverable. They now
use permanent field plots. The new field plot is a 5-10 point
variable radius plot (VRP) systematically arrayed over 1 acre
Fixed radius plots (FRP) are taken on a subset of points to
record trees less than 5 inches in diameter.3
National Forest Systems
Region 1: Each Ranger District on a National Forest in Region 1
is partitioned into administrative compartments. Compartments
are then mapped into forest stands based on slope, aspect, and
yegetational characteristics. All stands are mapped to obtain
100 percent coverage of the compartment. After mapping, stands
are stratified by vegetational characteristics. In many cases
stand characteristics are obtained by photo interpretation and
stored in the database for each stand. These characteristics
include: Slope, aspect, elevation, stand height, mean crown
diameter, crown closure percentage, species, and precipitation.
Some stands are subsequently examined in the field to obtain
information about the stands for silvicultural prescription or
for some other purpose. Field-derived information is then placed
into the stand's database record and the data type code is
updated to reflect the field examination source.
Variable radius plots are very efficient for estimating
basal area per acre and volume per acre (constant X basal area)
However, they are relatively inefficient for estimating number of
trees per acre. Fixed radius plots are efficient for estimatina
numbers of trees. ^^mciting
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A pps sample of stands is chosen within strata by compartment or
group of compartments. Sampling is with replacement. In some
cases stratum means of various stand characteristics such as
volume per acre, basal area per acre, and d.b.h. are estimated
for the sample and ascribed to all stands in that stratum within
the compartment. The preferred procedure involves fitting a
series of regressions to the sample stands. Discriminant
functions are used for classification variables. The resulting
regression and discriminant functions are then used to predict
stand characteristics for all of the stands which were not
sampled. Stand data base records are coded to reflect either a
stratum mean or regression prediction source. Eventually, field
examinations will be taken in stands that previously had records
based on statistical predictions.
Region 2: The inventory design is a stratified random sample. A
100% vegetation map is constructed from aerial photographs and
partially verified by stand examination or "walk-through"
surveys. As the maps are updated due to activity or stand
examinations, more acres become field verified. Approximately
50% of the forested acres have been field verified. Basic strata
for all inventories are forest cover type and stand size. Post
stratification is used in some cases. In the past, 1/5 acre, 10
point cluster, and stand exam plots have been used. Currently 5
points of the previous 10 point cluster plots are being
remeasured and permanently documented. The 10 point plots were
originally established on a photo grid with one plot representing
approximately 2300 acres. Additional samples are randomly
selected if the original plots are lost or to increase the
samples for a particular stratum. All samples except the old 1/5
acre plots use VRP with a fixed radius plot for seedlings and
saplings. The field plots provide the standard inventory
information, such as growing stock, mortality, and growth
volumes.
Region 3: This region has an inventory system similar to that of
Region 2. The inventory design is a stratified random sample.
Aerial photos, satellite imagery, or "walk-through's" are used to
delineate strata based upon species, size class, stocking, and
slope. Where more detailed information is available from stand
examinations, that information can also be used for
stratification. Stands are selected for ground measurements in
two ways. First, stands may be sampled as part of a stand
examination. Additional stands may be selected to more
accurately characterize certain strata for which stand
examination data have not been collected. A grid is not used for
field plots - they are selected randomly within the selected
stands. Each stand is sampled by a variable number of points.
This approach was chosen to compose a complete stand data base
from stand examinations. Stand examinations are conducted on a
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periodic basis. As new information becomes available, the stand
data base is updated. In order for this method to provide timber
resource information at specific points in time, the data base is
queried by relevant timber strata and tables of timber attributes
are produced.
Region 4: Each National Forest is type mapped on aerial
photographs. Stands are stratified by species, stand size-class
and stocking class. Stands are initially selected on a
systematic grid. If additional stands are needed in some strata
to reduce sampling error, they are selected with probability
proportional to their acreage i.e. pps sampling. Area statistics
come from measurement of acres from the type map. Within each
chosen stand a grid of points is constructed. The target grid is
1 point per 10 acres with no more than 20 points. The fewest
number acceptable is 3 points. These points are temporary and
probably cannot be exactly relocated. At each point a VRP is
taken to obtain volume and basal area statistics.
North Central FIA Region
The North Central region is made up of 11 states: Illinois,
Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska,
North Dakota, South Dakota, and Wisconsin. FIA publishes reports
by states, and each state is broken down into two or more survey
units composed of groups of counties. This area includes
portions of NFS Regions 1, 2, and 9. The inventory cycle for FIA
and NFS lands is 12-15 years.
The FIA unit at North Central uses a double sampling design. The
first phase is a systematic grid by township with a random start.
One acre photo plots are classified by land use and on forested
points additional information about general forest type, size and
density is recorded. Phase 1 data are recorded for all lands
without regard to ownership or land use. The photo point
intensity of this phase averages 1 point per 184.7 acres for the
region. The second phase or ground sample is a proportional
sample of the photo strata. The average ground plot intensity of
the field phase is 1 plot per 3,541 acres. The intensity of the
ground phase by states is somewhat uneven since many states in
the region contribute funds to double or triple the number of
field plots to reduce sampling errors. At each ground location a
10 point VRP is superimposed on 1 acre. Trees less than 5.0
inches d.b.h. are sampled on fixed radius plots.
National Forest System
Region 1: Since the area of Region 1 timberland is very small
within the North Central FIA area of coverage, FIA plots are
installed by FIA to FIA standards.
Region 2: See description under Intermountain FIA region.
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Region 9: Region 9 relies on two inventory procedures to meet
their vegetative information management needs. These are
permanent sample plots, which are measured by the FIA survey
units, and stand examination. The stand examination procedure is
initiated with the delineation of compartment and stand
boundaries on aerial photographs. These "pre-delineations" are
verified during the stand examination process and additional
information is taken. For each delineated stand a minimum sample
of 5, Basal Area Factor -10 plots are measured. This process
results in each stand being classified by its forest type, size-
density, basal area, stand condition, average DBH, land
classification, and cultural needs. The North Central FIA's grid
of field plots is extended over NFS lands and 10 point permanent
VRP are remeasured to obtain growing stock volume, growth, and
mortality.
Northeastern FIA Region
This FIA region contains 14 states: Connecticut, Delaware,
Kentucky, Maine, Maryland, Massachusetts, New Hampshire, New
Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, and
West Virginia. It contains part of NFS Regions 8 (Kentucky) and
9. NFS inventories NF lands in Region 9 but NE FIA does take
additional measurements on NF lands. In addition, NE FIA
inventories some NF lands in Region 8. The FIA inventory cycle
is approximately 12 years.
The FIA survey unit is a group of counties within States.
Reports of resources generally appear by state. Productive
reserved lands are also excluded from the survey units.
The sampling design employed in the NE FIA region is double
sampling with partial replacement. The first phase sample is
obtained from a photo grid. Photo points are interpreted into
land use and volume classes. The plot intensity is 1 plot per
340 acres. The field sample is usually a proportional allocation
of plots to photo strata. Apparently some inventories were
performed using optimal allocation. The field sample plots may
be either remeasured 1/5 acre fixed radius plots or 10 point VRP,
and new 5 point VRP. If old plots are selected the existing plot
is maintained for growth measurements and a new 5 point plot is
superimposed on the original plot. Approximately 4 different
fixed radius plots are installed over VRP points to measure
different size trees less than 5.0 inches d.b.h. and shrubs. The
ground sampling intensity is approximately 1 plot per 5000 acres.
In 1989 the NE FIA project will drop the partial replacement
concept in their second phase sample and go to complete
remeasurement with proportional allocation.
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National Forest System
Region 9: See description under North Central FIA Region.
Pacific Northwest FIA Region
The PNW region includes Oregon, Washington and California. It
excludes NF lands in NFS Regions 5 and 6. It also excludes BLM
lands in western Oregon and productive reserved forests The
survey units are groups of counties. The FIA inventory "cycle for
FIA and NFS inventories is 10 years.
The sampling design is double sampling for stratification. Photo
points are arrayed on a rectangular grid located on a base map
and tied into the UTM grid. Photo points are interpreted into
ownership maDor land class, and forest condition class strata.
The expected value of the photo intensity is approximately 1
point per 462.4 acres.
A second phase sample is selected on a systematic 3.4 mile arid
This produces 1 field plot for every 16 photo points. The
sampling intensity of the field sample is 1 plot per 7398 acres
"Other forest" land may be sampled with either a !?f mile ?iSd'
plot grid or a 6.8 mile field plot grid. The grid interval
?o££ ?y Snlt ^ b? f°reSt type' New field Plots °n Productive
forest land are 5 point TOP arrayed over 8 acres. Prior to 1977
field plots were 10 point TOP arrayed over 1 acre. One-point
££J!~P? '«"? five-P?int field Pl°ts have been used to sample
no^« 5orest land ' Fixed "dius plots are taken around the TOP
?SJ? « me£!^re !rees less than 5'° inches, in California in
1981-83, growth and mortality were measured on a subsample of
££E?£iy e^abiished Pi**-- W^h this exception, growth and
field plots3 are baS6d °n remeasurenent of all established
National Forest System
S2rt«i-5- ThS inventory ^sign is a stratified random sample.
Landsat imagery is analyzed to produce timber type maps showing
elf fur* £omblnati°ns°f species, size-class, and canopy *
tolor^l?? hPJ °tlVe f°reSt land and "ilderness are mapped.
tvn^ ? ^P ? ?S are USed to depict location of vegetation
M^'-T. t P ? 3re randolnly chosen «ithin timber strata?
Plots are 5 point TOP taken every 2 chains (132 ft.) arranged in
an L-shape Trees less than 5 inches are measured on fixed
points. P GrOWth 1S measured °n °ne tree on each of ?he 5
Region 6: This inventory system is new and quite different from
previous NFS inventory designs or other Regional designs? It is
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a 5 layered inventory system. Parts of it might be termed
stratified random sampling and other layers are simply
information systems.
Level 1 is a 100 percent detailed vegetation map of existing
vegetation on the ground. Stands are photo interpreted and up to
3 canopy layers described. It identifies species, crown closure,
and crown diameters. This map is continuous over all forested
acres including wilderness. Region 6 personnel are currently
looking into performing this information gathering from LANDSAT
imagery.
Level 2 is termed the "predicted vegetation" layer. Models are
derived which predict the desired vegetation for each location
based on management objectives and environmental factors. This
will also be a 100 percent coverage layered on level 1
information. Levels 1 and 2 form the stratification for ground
sampling.
Level 3 is the "Managed Stand Survey". Based on information in
levels 1 and 2 managed stands are identified. Permanent plots
are installed over a range of stand conditions (species, stand-
size class, and stocking class). Plots are 5 point fixed radius
plots arrayed over 2 1/2 acres. Each point consists of a
concentric 1/100 acre and 1/20 acre plot.
Level 4 is the "Vegetation Resource Survey". This survey covers
all vegetation conditions. It contains measurements of all
vegetation from grasses to mature trees. It excludes soils. No
classification is made; only basic vegetation resource
measurements. This allows any definition of area classification
to be imposed. The intensity of the sample is controlled by
existing 10 point plots, plus new 6-10 point VRP to estimate
volume + or - 15% at 1 SD. The old 10 point plots exist on a
grid. New plots are added to fill gaps in strata.
Level 5 is the "Old-Growth Survey". From levels 1 and 2 mature
stands are identified. Each stand is classified by canopy level.
Canopies are identified by species, crown closure, and crown
size. A field sample is selected within the mature stand strata.
A 10 point VRP is installed over 4 1/2 acres. These plots use a
BAF-40, thus obtaining a high tree tally across the entire
diameter range. The primary objective of this survey is to
measure or obtain distributional information or characteristics,
e.g. tree species and diameter by canopy position, height, age,
etc.
Southern FIA Region
The Southern FIA Region includes the states of Alabama, Arkansas,
Louisiana, Mississippi, Oklahoma, Tennessee and Texas. This FIA
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project inventories all ownerships including NFS. Survey units
are homogeneous groups of counties within states. Productive
reserve lands are excluded from published estimates. Productive
reserved land has been inventoried and archived since 1986
(except for Great Smoky Mountains National Park and Puerto Rico).
The inventory cycle is 10 years, but will be decreased to 7
years. The sampling design is double sampling for
stratification. The first phase sample is a systematic grid
located on a base map. Photo points are photo interpreted into
major land classes (eg. forest and nonforest).
Field plots are located on a 3 mile grid (1 to 5760 acres). A
greater intensity of field plots is taken on NF lands. Field
plots are 10 point VRP arrayed over 1 acre. Trees 1.0 to less
than 5.0 inches in diameter are measured on a 1/275 acre FRP on
points 1 through 3. Additional trees less than 5.0 inches are
measured on points if less than 2 variable radius plot trees are
recorded.
National Forest System
Region 8: The FIA projects inventorying NFS Region 8 use the
identical design and methods used for their standard inventories.
On small National Forests where NFS precision requirements are
not met, additional ground plots are taken. Region 8, like most
other Regions in NFS, maps the forest vegetation, stratifies the
mapping, and randomly selects stands for further sampling. The
results of the mapping are used to supplement the NFS area
estimates, and the results of the sampling are used to develop
Forest and project plans.
Southeastern FIA Region
The Southeastern region includes the states of Florida, Georgia,
North Carolina, South Carolina, and Virginia. This FIA region
inventories all ownerships including NFS. Woodland and
productive-reserved timberland are sampled. A few large National
Parks are currently excluded. Survey units are homogeneous
groups of counties within states. There are 21 such units in
this FIA region. The inventory cycle is 6.5 years.
The sampling design is double sampling for stratification. The
first phase sample consists of a large number of temporary 16
point clusters systematically selected on aerial photographs.
Each 16 point cluster is classified by photo interpretation into
the major land use classes, forest and nonforest. Phase 2
consists of a smaller number of permanent sample points, randomly
selected at some past date from a systematic grid. Another 16
point cluster is located at each permanent sample plot and photo
interpreted as in phase 1. A ground check of each permanent 16
point cluster provides a means of adjusting the photo
16
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interpretation of phase 1 for misclassifications and/or actual
changes since the photos were taken. For estimating forest area,
phase 2 is considered a subsample of phase 1, and the two phases
are related with a ratio estimator. Forest area estimates are
made for each county and summed to the survey unit or state
level.
Field plots for inventory purposes are located at each of the
permanent 16 point sample locations classed as timberland.
Sampling intensities vary among the mountain, piedmont and
coastal plain geographic regions (ie. 1/4800, 1/3700, and 1/2700,
respectively). Field plots are 5 point VRP arrayed over
approximately 1/2 acre. Trees less than 5.0 inches d.b.h. are
measured on a 1/300 acre FRP at each of the 5 points.
National Forest System
Region 8: See description under Southern FIA Region.
3. SUMMARY
There are many different sampling designs ot forest resource
inventories in existence. The key to retrieving and using this
information is not whether the design is complex or simple, but
whether ground plots are permanent and can be accurately
remeasured over time. Those agencies installing permanent fixed
or variable radius plots can provide useful information for
monitoring forest changes. Those installing temporary plots or
temporary point grids will not be as useful. A number of summary
tables are provided in Appendix 3. The Appendices include:
Appendix 1.
Appendix 2.
Appendix 3.
Table 1.
Table 2.
Table 3
Listings of the key stand and tree
information measured in the FIA and
NFS survey systems.
Terminology
Summary Tables
Tables of sampling
frequency, survey cycles
within each FIA region.
Tables of acreage and
number of sampling units
by survey unit within
each FIA region.
Tables of sampling frequency,
acreage within each NFS region
17
-------
Table 4. A table identifying who
is responsible for
inventorying the
different ownerships
within each FIA region.
18
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APPENDIX 1 — A COMPENDIUM OF RESOURCE DATA COLLECTED ON
SAMPLE PLOTS
Forest Inventory and Analysis
Area Data
1. Land use (all lands)
2. Use trend (remeasured plots only)
3. Slope
4. Aspect
5. Terrain position
6. Ownership
7. Forest type
8. Stand age
9. Stand-size class
10. Stand-volume class
11. Stand-stocking (based on basal area)
12. Area-condition class
13. Stand origin
14. Seed source
15. Physiographic classification
16. Past management activity
17. Actual productivity (remeasured plots only)
18. Potential productivity
19. Management opportunity
20. Size of forest stand
21. Wildlife habitat values
a. water
b. edge
c. openings
d. foliage browse level
e. forest type diversity
f. cover items
22. Precipitation
Plot Data
1. Distance to road
2. Recreation opportunity classes
3. Plot age - generally 20-year classes for even-aged stands
4. Timber management classes
5. Harvest history
6. Time since cut
7. Equipment limitations
8. Surface boulders
9. Elevation
10. Soils data
a. organic depth
b. rooting depth
c. mottling depth
d. texture of surface, B horizon
19
-------
e. bedrock depth
f. parent material
g. moisture class
h. soil series
i. soil erosion
j. flooding class
11. Site index - 4 trees: species, height, dbh, and age
Tree Data
1. Species
2. D.B.H.
3. Height (merchantable and sawlog)
4. Cull (Cubic and board foot)
5. Tree quality values:
a. butt log grade
b. external defects
c. internal defects
d. crown classification
e. Crown ratio
f. merchantability
g. damage/cause of death
1. insect presence and identification
2. disease - identification and degree of infection
h. quality class
6. Tree history (remeasured plots only):
a. past d.b.h.
b. past merchantability
c. past quality
7. Wildlife values related to merchantability, species, and
size
a. wolf tree (condition)
b. snag (condition)
c. feeding site
d. tree cavities
8. Regeneration
Other Vegetation Data
1. Foliage structure
2 Foliage condition
3. Percent foliage volume by life form
4. Regeneration/shrubs/vines (count)
a. species
b. height
c. browse avail./utilization
From: Forest Service Resource Inventory: An Overview,
April 1985.
20
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National Forest System
Timber Inventory Data
Area Data
1. Land use class
2. Land cover category
3. Ecosystem/cover type
4. Crown closure (cover)
5. Density
6. Most hazardous pest
7. Seedling/shrub count
8. Site productivity class
9. Stand condition
10. Stand origin
11. Stand size class
12. Stand structure
13. Stand volume
14. Stand year of origin
15. Stocking class
16. Stocking percent
17. Timber treatment opportunity class
Control Data
1. Administrative forest
2. Land availability
3. Ownership class
4. Region/Station
5. State/Territory
6. Subregion
Vegetation Data
1. Basal area
2. Bole length
3. Bole length top diameter outside bark
4. Cause of injury/death
5. Crown class
6. Crown foliage density
7. Crown length (depth), compact
8. Crown ratio, compacted
9. Crown width (diameter)
10. Height growth
11. Height to crown, compacted
12. Mistletoe infection rating
13. Plant species
14. Principal defect
15. Radial growth (increment)
16. Sawlog length
21
-------
17. Sawlog top diameter outside bark
18. Site tree quality
19. Total tree length (height)
20. Tree age
21. Tree class
22. Tree DBH
23. Tree history
24. Tree volume
From: Draft Chapter 20 of Forest Service Handbook 1909.14. This is
still undergoing revision. Standardization of data to be collected
for other NFS inventories is also provided in this draft chapter.
22
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APPENDIX 2. TERMINOLOGY
Basal area. The area in square feet of the cross section at breast
height of a single tree. When the basal area of all trees in a stand
are summed, the result is usually expressed as square feet of basal
area per acre.
Basal area factor. (BAF) The number of units of basal area per acre
represented by each tree tallied on a Variable Radius Plot. For
example, FIA often uses a BAF 37.5 to determine which trees on a plot
should be measured from a sampling point (See Variable Radius Plot
sampling method). In the past, the use of BAF 10 was common. The
larger a BAF, the fewer the number of trees which will be measured.
Biomass. Above-ground mass or weight. FIA definition: The above-
ground volume of all live trees (including bark and foliage) reported
in green tons.
BLM. Bureau of Land Management.
Commercial species. Tree species presently or prospectively
classified as suitable for industrial wood products.
Diameter classes. A classification of trees based on diameter outside
bark, measured at breast height (4 1/2 feet above the ground).
(D.b.h. is the common abbreviation for diameter at breast height.
Two-inch diameter classes are commonly used in Forest Inventory and
Analysis, with the even inch the approximate midpoint for a class.
For example, the 6-inch class includes trees 5.0 through 6.9 inches
d.b.h.)
Double sampling ("two-phase sampling design") for stratification. The
population is sampled in a first phase sample to estimate the size of
strata, and usually a subsample of the first phase sample is selected
for more detailed groun^ measurements. For example, the FIA sample
commonly uses a grid of points on aerial photographs as a first phase
sample. The points are stratified according to land use (forest vs
nonforest), ownership classes, and timber volume classes. A subsample
of the photo points is visited on the ground to obtain more detailed
information about each stratum.
Forest land. Land at least 16.7 percent stocked by forest trees of
any size, or formerly having had such tree cover, and not currently
developed for nonforest use. The minimum area for classification of
forest land is 1 acre. Roadside, streamside, and shelterbelt strips
of timber must have a crown width of at least 120 feet to qualify as
forest land. Unimproved roads and trails, streams, or other bodies of
water or clearings in forest areas are classified as forest if less
than 120 feet wide.
23
-------
Forest type. A classification of forest land based on the species
forming a plurality of live tree stocking.
Growing stock volume. Net volume in cubic feet of growing-stock trees
5 inches d.b.h. and over, from a 1-foot stump to a minimum 4 inch top
diameter outside bark of the central stem or to the point where the
central stem breaks into limbs.
Land. Bureau of the Census definition: Dry land and land temporarily
or partly covered by water such as marshes, swamps, and river flood
plains (omitting tidal flats below mean high tide); streams, sloughs,
estuaries, and canals less than one-eighth of a statute mile wide; and
lakes, reservoirs, and ponds less than 40 acres in area. For FIA
purposes, it is the same definition, except minimum width of streams,
etc., is 120 feet and minimum size of lakes, etc., is 1 acre.
Mortality. The volume of sound wood in growing-stock and sawtimber
trees that dies, usually measured annually or periodically.
National forest land. Federal land that has been legally designated
as National Forest or purchase units, and other land administered by
the USDA Forest Service.
Nonforest land. Land that has never supported forests or where
stockability is limited to less than 16.7% (10% absolute), and land
formerly forested where use for timber management is precluded by
development for other uses.
Nonstocked land. Timberland less than 16.7 percent stocked with
growing-stock trees.
"Other forest land." See definition for woodland.
Physiographic class. A measure of soil and water conditions that
affect tree growth on a site. The physiographic classes are:
Xeric sites - Very dry soils where excessive drainage
seriously limits both growth and species occurrence.
Ex: sandy pine plains.
Xeromesic sites - Moderately dry soils where excessive
drainage limits growth and species occurrence to some
extent. Ex: dry oak ridge.
Mesic sites - Deep, well-drained soils. Growth and
species occurrence are limited only by climate.
Hydromesic sites - Moderately wet soils where
insufficient drainage or infrequent flooding limits
growth and species occurrence to some extent. Ex:
better drained bottomland sites.
24
-------
Hydric sites - Very wet sites where excess water
seriously limits both growth and species occurrence.
Ex: frequently flooded river bottoms, bogs and swamps.
Probability proportional to size (pps) sampling. In the broad sense,
it is a sampling method synonymous with sampling with varying
probabilities. Specifically, it is a type of forest sampling where
sampling units (stands, plots, or trees) are selected proportional to
some measure of size (pps sampling used to select trees proportional
to d.b.h. is called Variable Radius Plot sampling).
Reserved timberland. Forest land sufficiently productive to qualify
as timberland but withdrawn from timber utilization through statute,
administrative regulation, designation, or exclusive use for Christmas
tree production, as indicated by annual shearing. Formerly called
productive-reserved forest land.
SCS. Soil Conservation Service.
Site class. A classification of forest land in terms of inherent
capacity to grow crops of industrial wood based on fully stocked
natural stands.
Site index. An expression of forest site quality based on the height
of a free-growing dominant or codominant tree of a representative
species in the forest type at a specified age.
Stand. A group of trees on a minimum of 1 acre of forest land that is
stocked by forest trees of any size.
Stand-age class. Age of the main stand. Main stand refers to trees
of the dominant forest type and stand-size class.
Stand-size class. A classification of stocked forest land based on
the size class of live trees on the area; that is, sawtimber,
poletimber, or seedlings and saplings.
Stocking. The degree of occupancy of land by trees, measured by basal
area and/or the number of trees in a stand by size or age and spacing,
compared to the basal area and/or number of trees required to fully
utilize the growth potential of the land; i.e., the stocking standard.
Stratified random sampling. The units of the population are grouped
together on the basis of similarity of some characteristic. NFS
commonly stratifies on the basis of timber type, size, and density
(TSD). Within each stratum, sample units are selected according to
some random sampling rule, for example, simple random sampling.
Stratified systematic sampling. The units of the population are
grouped together on the basis of similarity of some characteristic.
Within each stratum a sample is drawn according to some systematic
rule. Usually, this is accomplished by constructing a square grid
25
-------
over all strata. Such grids result in proportional allocations of
sample units to strata.
Timberland. Forest land producing or capable of producing crops of
industrial wood and not withdrawn from timber utilization (i.e.,
reserved timberland). Areas qualifying as timberland are capable of
producing more than 20 cubic feet per acre per year of annual growth
when managed. Currently inaccessible and inoperable areas are
included except when the areas involved are small and unlikely to
become suitable for producing industrial wood in the foreseeable
future. Formerly this was referred to as commercial forest land.
Universal Transverse Mercator (UTH). A type of plane coordinate
system, which is a rectangular grid based on the Mercator map
projection system. It has been widely adopted for topographical maps,
referencing of satellite imagery, and other applications that require
precise positioning.
Variable radius plot (VRP). Method of sampling trees for forest
inventory purposes. The probability of tree selection is proportional
to tree basal area. This is an application of the probability
proportional to size (pps) sampling method (See basal area factor,
probability proportional to size).
Water. Bureau of Census definition: Permanent inland water surfaces,
such as lakes, reservoirs, and ponds at least 40 acres in area; and
streams, sloughs, estuaries, and canals at least one-eighth of a
statute mile wide.
Woodland. Forest land incapable of producing 20 cubic feet per acre
of annual growth or of yielding crops of industrial wood under natural
conditions because of adverse site conditions. Adverse conditions
include shallow soil, dry climate, poor drainage, high elevation,
steepness, and rockiness. Formerly this was called unproductive forest
land.
NOTE: An Interim Resource Inventory Glossary may be issued by the
USDA Forest Service in the near future. It contains some 176 terms
and standards dealing with the inventory of all resources. When
approved, these will become the standards for the Forest Service.
Several of the definitions listed in this appendix will change.
26
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42
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Staff, Forest Inventory and Analysis Research Work Unit. Forest
Statistics for North Alabama Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-95. Southern Forest Exp.
Sta., New Orleans, LA. 15p. 1983.
Staff, Forest Inventory and Analysis Research Work Unit. Forest
Statistics for Southeast Alabama Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-94. Southern Forest Exp.
Sta., New Orleans, LA. 18p. 1983.
Staff, Forest Inventory and Analysis Research Work Unit. Forest
Statistics for West Central Alabama Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-93. Southern Forest Exp.
Sta., New Orleans, LA. 15p. 1983.
Staff, Forest Inventory and Analysis Research Work Unit. Forest
Statistics for Southwest-North Alabama Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-92. Southern Forest Exp.
Sta., New Orleans, LA. 15p. 1983.
Staff, Forest Inventory and Analysis Research Work Unit. Forest
Statistics for Southwest-South Alabama Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-91. Southern Forest Exp.
Sta., New Orleans, LA. 15p. 1983.
Alaska
LaBau, V.J., and W.S. Van Hees. An Assessment of the Ownership of
Timberland in Alaska. U.S. Department of Agriculture, For. Serv.,
Draft Report. Juneau, AK. 33p. 1987.
Arkansas
Hines, F.D. Forest Statistics for Arkansas' Ozark Counties-1988. U.S.
Department of Agriculture, For. Serv. Resource Bull. SO-131. Southern
Forest Exp. Sta., New Orleans, LA. 39p. 1988.
Hines, F.D. Forest Statistics for Arkansas1 Delta Counties-1988. U.S.
Department of Agriculture, For. Serv. Resource Bull. SO-133. Southern
Forest Exp. Sta., New Orleans, LA. 39p. 1988.
Hines, F.D. Forest Statistics for Arkansas' Ouachita Counties. U. S.
Department of Agriculture, For. Serv. Resource Bull. SO-137. Southern
Forest Exp. Sta., New Orleans, LA. 28p. 1988.
Hines, F.D. Forest Statistics for Southwest Arkansas Counties-1988.
U.S. Department of Agriculture, For. Serv. Resource Bull. SO-140.
Southern Forest Exp. Sta., New Orleans, LA. 32p. 1988.
Hines, F.D., and J.S. Vissage. Forest Statistics for Arkansas
Counties-1988. U.S. Department of Agriculture, For. Serv. Resource
43
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Bull. SO-141. Southern Forest Exp. Sta., New Orleans, LA. 68p.
1988.
California
Bolsinger, C.L. The Hardwoods of California's Timberlands, Woodlands,
and Savannas. U.S. Department of Agriculture, For. Serv. Resource
Bull. PNW-RB-148. Pacific Northwest Res. Sta., Portland, OR. 148p.
1988.
Colclasure, P., J. Moen, and C.L. Bolsinger. Timber Resource
Statistics for the Central Coast Resource Area of California. U.S.
Department of Agriculture, For. Serv. Resource Bull. PNW-133. Pacific
Northwest Research Sta., Portland, OR. 32p. 1986.
Colclasure, P., J. Moen, and C.L. Bolsinger. Timber Resource
Statistics for the Northern Interior Resource Area of California.
U.S. Department of Agriculture, For. Serv. Resource Bull. PNW-135.
Pacific Northwest Research Sta., Portland, OR. 32p. 1986.
Hiserote, B.A., J. Moen, and C.L. Bolsinger. Timber Resource
Statistics for the San Joaquin and Southern California Resource Areas.
U.S. Department of Agriculture, For. Serv. Resource Bull. PNW-132.
Lloyd, J.D., J. Moen, and C.L. Bolsinger. Timber Resource Statistics
for the North Coast Resource Area of California. U.S. Department of
Agriculture, For. Serv. Resource Bull. PNW-131. Pacific Northwest
Research Sta., Portland, OR. 32p. 1986.
Lloyd, J.D., J. Moen, and C.L. Bolsinger. Timber Resource Statistics
for the Sacramento Resource Area of California. U.S. Department of
Agriculture, For. Serv. Resource Bull. PNW-134. Pacific Northwest
Research Sta., Portland, OR. 32p. 1986.Pacific Northwest Research
Sta., Portland, OR. 35p. 1986.
Colorado
Benson, R.E., and A.W. Green. Colorado's Timber Resources.
U.S. Department of Agriculture, For. Serv. Resource Bull. INT-48.
Intermountain Research Sta., Ogden, UT. 53p. 1987.
Connecticut
Dickson, D.R., and C.L. McAfee. Forest Statistics for Connecticut.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-105.
Northeastern Forest Exp. Sta., Broomall, PA. 102p. 1988.
Florida
Brown, M.J. Forest Statistics for Northwest Florida, 1987. U.S.
Department of Agriculture, For. Serv. Resource Bull. SE-96.
Southeastern Forest Exp. Sta., Asheville, NC. 50p. 1987.
44
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Brown, M.J. Forest Statistics for Northeast Florida, 1987.
Department of Agriculture, For. Serv. Resource Bull. SE-97.
Southeastern Forest Exp. Sta., Asheville, NC. 53p. 1987.
U.S
Brown, M.J. Forest Statistics for Central Florida, 1988. U.S.
Department of Agriculture, For. Serv. Resource Bull. SE-99.
Southeastern Forest Exp. Sta., Asheville, NC. 53p. 1988.
Brown, M.J., and M.T. Thompson. Forest Statistics for South Florida,
1988. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
100. Southeastern Forest Exp. Sta., Asheville, NC. 48p. 1988.
Brown, M.J., and M.T. Thompson. Forest Statistics for Florida, 1987.
U.S. Department of Agriculture, For. Serv. Resource Bull. SE-101.
Southeastern Forest Exp. Sta., Asheville, NC. 61p. 1987.
Georgia
Sheffield, R.M., and H.A. Knight.
Resource Bull. SO-135. 1988.
Hawaii
Georgia's Forests. U.S. For. Serv,
Buck, M.G., and P.G. Costales, K. McDuffie. Multiresource Forest
Statistics for Molokai, Hawaii. U.S. Department of Agriculture, For.
Serv. Resource Bull. PNW-136. Pacific Southwest For. Exp. Sta.,
Berkeley, CA. 18p. 1986.
Metcalf, M.E., R.E. Nelson, E.Q.P. Petteys, and J.M. Berger. Hawaii's
Timber Resources, 1970. U.S. Department of Agriculture, For. Serv.
Resource Bull. PSW-15. Pacific Southwest For. Exp. Sta., Berkeley,
CA. 20p. 1978.
Idaho
Benson, R.E., and A.W. Green, and D.D. Van Hooser. Idaho's Forest
Resources. U.S. Department of Agriculture, For. Serv. Resource Bull.
INT-39. Intermountain Res. Sta., Ogden, UT. 114p. 1987.
Benson, R.E., and A.W. Green and D.D. Van Hooser. Idaho's Forest
Resources. U.S. Department of Agriculture, For. Serv. Resource Bull.
INT-48. Intermountain Research Sta., Ogden, UT. 114p. 1987.
Illinois
Raile, G.K. and E.G. Leatherberry. Illinois' Forest Resource. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-105. North
Central For. Exp. Sta., St. Paul, MN. 113p. 1988.
45
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Indiana
Hansen, M.H., and M.F. Golitz. Timber Resource of the Indiana Knobs
Unit, 1986. U.S. Department of Agriculture, For. Serv. Resource Bull
NC-104. North Central Forest Exp. Sta., St. Paul, MN. 92p. 1988.
Smith, W.B., and M.F. Golitz. Indiana Forest Statistics, 1986. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-108. North
Central For. Exp. Sta., St. Paul, MN. 138p. 1986.
Iowa
Spencer, J.S., and P.J. Jakes. Iowa Forest Resources-1974. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-52. North
Central For. Exp. Sta., St. Paul, MN. 90p. 1980.
Kansas
Spencer, J.S., J.K. Strickler, and W.J. Moyer. Kansas Forest
Inventory, 1981. U.S. Department of Agriculture, For. Serv. Resource
Bull. NC-83. North Central For. Exp. Sta., St. Paul, MN. 134p.
1984.
Louisiana
May, D.M., and D.F. Bertelson. Forest Statistics for Louisiana
Parishes. U.S. Department of Agriculture, For. Serv. Resource Bull.
SO-115. Southern Forest Exp. Sta., New Orleans, LA. 59p. 1986.
Rosson, J.F., and D.F. Bertelson. Forest Statistics for Northwest
Louisiana Parishes. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-102. Southern Forest Exp. Sta., New Orleans, LA.
31p. 1985.
Rosson, J.F., and D.F. Bertelson. Forest Statistics for Southwest
Louisiana Parishes. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-103. Southern Forest Exp. Sta., New Orleans, LA,
31p. 1985.
Rosson, J.F., and D.F. Bertelson. Forest Statistics for Southeast
Louisiana Parishes. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-104. Southern Forest Exp. Sta., New Orleans, LA.
31p. 1986.
Rosson, J.F., and D.F. Bertelson. Forest Statistics for North Delta
Louisiana Parishes. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-105. Southern Forest Exp. Sta., New Orleans, LA.
31p. 1986.
Rcsson, J.F., and D.F. Bertelson. Forest Statistics for South Delta
Louisiana Parishes. U.S. Department of Agriculture, For. Serv.
46
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Resource Bull. SO-106. Southern Forest Exp. Sta., New Orleans, LA.
31p. 1986.
Rosson, J.F., W.H. McWilliams, and P.O. Frey. Forest Resources of
Louisiana. U.S. For. Serv. Resource Bull. SO-130. 81p. 1988.
Maine
Douglas, S.P., and D.R. Dickson. Forest Statistics for Maine. U. S.
Department of Agriculture, For. Serv. Resource Bull. NE-81.
Northeastern Sta., Broomall, PA. 194p. 1984.
Maryland
Frieswyk, T.S., and D.M. DiGiovanni. Forest Statistics for Maryland.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-107.
Northeastern Forest Exp. Sta., Broomall, PA. 157p. 1988.
Massachusetts
Dickson, D.R., and C.L. McAfee. Forest Statistics for Massachusetts.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-106.
Northeastern Forest Exp. Sta., Broomall, PA. 112p. 1988.
Michigan
Raile, G.K. and W.B. Smith. Michigan Forest Statistics, 1980. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-67. North
Central For. Exp. Sta., St. Paul, MN. lOlp. 1983.
Minnesota
Jakes, P.J. Minnesota Forest Statistics, 1977. U.S. Department of
Agriculture, For. Serv. Resource Bull. NC-53. North Central For. Exp.
Sta., St. Paul, MN. 85p. 1980.
Mississippi
Donner, B.L., and F.D. Hines. Forest Statistics for Mississippi
Counties-1987. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-129. Southern Forest Exp. Sta., New Orleans, LA. 79p.
1987.
Kelly, J.F., and F.D. Hines. Forest Statistics for North Mississippi
Counties-1987. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-122. Southern Forest Exp. Sta., New Orleans, LA. 39p.
1987.
Kelly, J.F., and F.D. Hines. Forest Statistics for South Mississippi
Counties-1987. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-124. Southern Forest Exp. Sta., New Orleans, LA. 34p.
1987.
47
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Kelly, J.F., and F.D. Hines. Forest Statistics for Mississippi Delta
Counties-1987. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-126. Southern Forest Exp. Sta., New Orleans, LA. 34p.
1987.
Kelly, J.F., and F.D. Hines. Forest Statistics for Mississippi
Counties-1987. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-127. Southern Forest Exp. Sta., New Orleans, LA. 34p.
1987.
Kelly, J.F., and F.D. Hines. Forest Statistics for Southwest
Mississippi Counties-1987. U.S. Department of Agriculture, For. Serv,
Resource Bull. SO-127. Southern Forest Exp. Sta., New Orleans, LA.
33p. 1987.
Missouri
Spencer, J.S., and B.L. Essex. Timber in Missouri, 1972. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-30. North
Central For. Exp. Sta., St. Paul, MN. 108p. 1976.
Montana
Green, A.W., R.A. O'Brien, and J.C. Schaefer. Montana's Forests. U.S.
Department of Agriculture For. Serv. Resource Bull. INT-38.
Intermountain Research Sta., Ogden, UT. 69p. 1985.
Nebraska
Raile, G.K. Nebraska's Second Forest Inventory. U.S. Department of
Agriculture, For. Serv. Resource Bull. NC-96. North Central For. Exp
Sta., St. Paul, MN. 87p. 1986.
New Hampshire
Frieswyk, T.S., and A.M. Malley. Forest Statistics for New Hampshire
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-88.
Northeastern Sta., Broomall, PA. lOOp. 1985.
New York
Considine, T.J. and T.S. Frieswyk. Forest Statistics for New York.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-71.
Northeastern Sta., Broomall, PA. 118p. 1982.
North Carolina
Bechtold, W.A. Forest Statistics for North Carolina, 1984. U.S.
Department of Agriculture, For. Serv. Resource Bull. SE-78.
Southeastern Forest Exp. Sta., Asheville, NC. 62p. 1984.
48
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Graver, G.C. Forest Statistics for the Mountains of North Carolina,
1984. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
77. Southeastern Forest Exp. Sta., Asheville, NC. 50p. 1984.
Davenport, E.L. Forest Statistics for the Northern Coastal Plain of
North Carolina, 1984. U.S. Department of Agriculture, For. Serv.
Resource Bull. SE-74. Southeastern Forest Exp. Sta., Asheville, NC.
50p. 1984.
Hutchins, C.C. Forest Statistics for the Piedmont of North Carolina,
1984. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
76. Southeastern Forest Exp. Sta., Asheville, NC. 46p. 1984.
Tansey, J.B. Forest Statistics for the Southern Coastal Plain of
North Carolina, 1983. U.S. Department of Agriculture, For. Serv.
Resource Bull. SE-72. Southeastern Forest Exp. Sta., Asheville, NC.
51p. 1983.
North Dakota
Jakes, P.J., and W.B. Smith. A Second Look at North Dakota's Timber
Land. U.S. Department of Agriculture, For. Serv. Resource Bull. NC-
58. North Central For. Exp. Sta., St. Paul, MN. 87p. 1982.
Ohio
Donald, D.D., and T.W. Birch. Forest Statistics for Ohio. U.S.
Department of Agriculture, For. Serv. Resource Bull. NE-68.
Northeastern Sta., Broomall, PA. 79p. 1981.
Oklahoma
Birdsey, R.A., and D.F. Bertelson. Forest Statistics for Southeast
Oklahoma Counties-1986. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-119. Southern Forest Exp. Sta., New Orleans, LA.
30p. 1987.
Birdsey, R.A., and D.F. Bertelson. Forest Statistics for Northeast
Oklahoma Counties-19CS. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-120. Southern Forest Exp. Sta., New Orleans, LA.
30p. 1987.
Birdsey, R.A., and D.M. May. Timber Resources of Eastern Oklahoma.
U.S. For. Serv. Resource Bull. SO-135. 1988.
Hines, F.D., and D.F. Bertelson. Forest Statistics for East Oklahoma
Counties-1986. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-121. Southern Forest Exp. Sta., New Orleans, LA. 57p.
1987.
49
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Oregon
Farrenkopf, T.O. Forest Statistics for Eastern Oregon, 1977. U.S.
Department of Agriculture, For. Serv. Resource Bull. PNW-94. Pacific
Northwest For. Exp. Sta., Portland, OR. 28p. 1981.
Gedney, D.R., P.M. Bassett, and M.A. Mei. Timber Resource Statistics
for Non-Federal Forest Land in West-Central Oregon. U.S. Department
of Agriculture, For. Serv. Resource Bull. PNW-RB-143. Pacific
Northwest Research Sta., Portland, OR. 26p. 1987.
Gedney, D.R., P.M. Bassett, and M.A. Mei. Timber Resource Statistics
for Non-Federal Forest Land in Northwest Oregon. U.S. Department of
Agriculture, For. Serv. Resource Bull. PNW-RB-140. Pacific Northwest
Research Sta., Portland, OR. 26p. 1986.
Gedney, D.R., P.M. Bassett,and M.A. Mei. Timber Resource Statistics
for Non-Federal Forest Land in Southwest Oregon. U.S. Department of
Agriculture, For. Serv. Resource Bull. PNW-138. Pacific Northwest
Research Sta., Portland, OR. 26p. 1986.
Pennsylvania
Considine, T.J. and.D.S. Powell. Forest Statistics for Pennsylvania.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-65.
Northeastern Forest Exp. Sta., Broomall, PA. 88p. 1980.
Rhode Island
Dickson, D.R., and C.L. McAfee. Forest Statistics for Rhode Island.
U.S. Department of Agriculture, For. Serv. Resource Bull. NE-104.
Northeastern Forest Exp. Sta., Broomall, PA. 96p. 1988.
South Carolina
Tansey, J.B. Forest Statistics for the Piedmont of South Carolina,
1986. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
89. Southeastern Forest Exp. Sta., Asheville, NC. 53p. 1986.
Tansey, J.B. Forest Statistics for the Northern Coastal Plain of
South Carolina, 1986. U.S. Department of Agriculture, For. Serv.
Resource Bull. SE-91. Southeastern Forest Exp. Sta., Asheville, NC.
54p. 1986.
Tansey, J.B. Forest Statistics for the Southern Coastal Plain of
South Carolina, 1987. U.S. Department of Agriculture, For. Serv.
Resource Bull. SE-92. Southeastern Forest Exp. Sta., Asheville, NC.
49p. 1987.
Tansey, J.B. Forest Statistics for South Carolina, 1986. U.S.
Department of Agriculture, For. Serv. Resource Bull. SE-93.
Southeastern Forest Exp. Sta., Asheville, NC. 55p. 1986.
50
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South Dakota
Collins, D.C., and A.W. Green. South Dakota's Timber Resources. U.S.
Department of Agriculture, For. Serv. Resource Bull. INT-56. North
Central For. Exp. Sta., St. Paul, MN. 28p. 1988.
Raile, G.K. Eastern South Dakota Forest Statistics, 1980. U.S.
Department of Agriculture, For. Serv. Resource Bull. NC-74. North
Central For. Exp. Sta., St. Paul, MN. 60p. 1984.
Tennessee
May, D.M., and J.S. Vissage. Forest Statistics for West Tennessee
Counties-1989. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-142. Southern Forest Exp. Sta., New Orleans, LA. 34p.
1988.
Staff, Renewable Resources Evaluation Research Work Unit. Forest
Statistics for West Central Tennessee Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-82. Southern Forest Exp.
Sta., New Orleans, LA. 18p. 1982.
Staff, Renewable Resources Evaluation Research Work Unit. Forest
Statistics for Central Tennessee Counties. U.° Department of
Agriculture, For. Serv. Resource Bull. SO-79. Southern Forest Exp.
Sta., New Orleans, LA. 21p. 1980.
Staff, Renewable Resources Evaluation Research Work Unit. Forest
Statistics for Plateau Tennessee Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-80. Southern Forest Exp.
Sta., New Orleans, LA. 21p. 1982.
Staff, Renewable Resources Evaluation Research Work Unit. Forest
Statistics for East Tennessee Counties. U.S. Department of
Agriculture, For. Serv. Resource Bull. SO-87. Southern Forest Exp.
Sta., New Orleans, LA. 22p. 1982.
Texas
Lang, L.L., and D.F. Bertelson. Forest Statistics for East Texas
Counties-1986. U.S. Department of Agriculture, For. Serv. Resource
Bull. SO-118. Southern Forest Exp. Sta., New Orleans, LA. 66p.
1987.
McWilliams, W.H., and D.F. Bertelson. Forest Statistics for Northeast
Texas Counties-1986. U.S. Department of Agriculture, For. Serv.
Resource Bull. SO-113. Southern Forest Exp. Sta., New Orleans, LA.
29p. 1986.
McWilliams, W.H., and D.F. Bertelson. Forest Statistics for Southeast
Texas Counties-1986. U.S. Department of Agriculture, For. Serv.
51
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Resource Bull. SO-114.
29p. 1986.
Utah
Southern Forest Exp. Sta., New Orleans, LA.
Van Hooser, D.D., and A.W. Green. Utah's Forest Resources. U.S.
Department of Agriculture, For. Serv. Resource Bull. INT-30.
Intennountain For. Exp. Sta., Ogden, UT. 58p. 1983.
Vermont
Frieswyk, T.S., and A.M. Malley. Forest Statistics for Vermont. U.S.
Department of Agriculture, For. Serv. Resource Bull. NE-87.
Northeastern Sta., Broomall, PA. 102p. 1985.
Virginia
Bechtold, W.A., M.J. Brown, and J.B. Tansey. Virginia's Forests. U.S.
For. Serv. Resource Bull. SE-95. 89p. 1987.
Brown, M.J. Forest Statistics for the Northern Mountains of Virginia,
1986. U.S. Department of Agriculture For. Serv. Resource Bull. SE-85.
Southeastern Forest Exp. Sta., Asheville, NC. 56p. 1986.
Brown, M.J. Forest Statistics for the Southern Mountains of Virginia,
1986. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
86. Southeastern Forest Exp. Sta., Asheville, NC. 55p. 1986.
Brown, M.J. Forest Statistics for the Southern Piedmont of Virginia,
1985. U.S. Department of Agriculture, For. Serv. Resource Bull. SE-
81. Southeastern Forest Exp. Sta., Asheville, NC. 55p. 1985.
Brown, M.J., and G.C. Graver. Forest Statistics for the Coastal Plain
of Virginia, 1985. U.S. Department of Agriculture, For. Serv.
Resource Bull. SE-80. Southeastern Forest Exp. Sta., Asheville, NC.
53p. 1985.
Washington
Bassett, P.M., and D.D. Oswald. Timber Resource Statistics for the
Puget Sound Area, Washington. U.S. Department of Agriculture, For.
Serv. Resource Bull. PNW-96. Pacific Northwest For. Exp. Sta.,
Portland, OR. 31p. 1982.
Bassett, P.M., and D.D. Oswald. Timber Resource Statistics for
Eastern Washington. U.S. Department of Agriculture, For. Serv.
Resource Bull. PNW-96. Pacific Northwest For. Exp. Sta., Portland,
OR. 32p. 1983.
Bassett, P.M., and D.D. Oswald. Timber Resource Statistics for
Eastern Washington. U.S. Department of Agriculture, For. Serv.
52
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Resource Bull. PNW-104. Pacific Northwest For. and Range Exp. Sta.,
Portland, OR. 32p. 1983.
Bassett, P.M., and D.D. Oswald. Timber Resource Statistics for
Southwest Washington. U.S. Department of Agriculture, For. Serv.
Resource Bull. PNW-91. Pacific Northwest For. Exp. Sta., Portland,
OR. 24p. 1981.
Bassett, P.M., and D.D. Oswald. Timber Resource Statistics for the
Olympic Peninsula, Washington. U.S. Department of Agriculture, For.
Serv. Resource Bull. PNW-93. Pacific Northwest For. Exp. Sta.,
Portland, OR. 31p. 1981.
Wisconsin
Spencer, J.S., W.B. Smith, J.T. Hahn, and G.K. Raile. Wisconsin's
Fourth Forest Inventory, 1983. U.S. Department of Agriculture, For.
Serv. Resource Bull. NC-107. North Central For. Exp. Sta., St. Paul,
MN. 158p. 1988.
In addition, the following people provided information for this
document through personal contact and review of the document:
FIA Contacts:
Roy Beltz
Forestry Sciences Laboratory
Box 906
Starkville, MS 39759
James T. Bones, Richard A. Birdsey
Washington Office FIA
For. Inventory, Econ., and Rec. Research Staff
U.S. Department of Agriculture South Bldg.
12th & Independence., S.W.
Washington, DC. 20250
Noel Cost, Raymond Sheffield
Southeastern Forest Experiment Station
200 Weaver Blvd.
P.O. Box 2680
Asheville, NC 28802
Dave Dickson, John Peters, Charles Scott
Northeast Forest Experiment Station
370 Reed Rd. Broomall, PA. 19008
Neal Kingsley, Mark Hansen, Brad Smith
North Central Forest Experiment Station
1992 Folwell Ave St. Paul, MN. 55108
53
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Vernon J. Labau, Theodore S. Setzer
Forestry Sciences Laboratory
201 E. 9th Ave., Suite 303
Anchorage, AK 99501
Dan Oswald, Janet Ohman, Charles Bolsinger
Pacific Northwest Forest and Range Experiment Station
Forestry Sciences Laboratory
P.O. Box 3890, Portland, OR. 97208
Dwane Van Hooser, Alan W. Green
Forestry Sciences Laboratory
507 25th St.
Ogden, UT 84401
National Forest contacts for survey information:
Frank Birch
Pacific Southwest Region
630 Sansome St.
San Francisco, CA. 94111
Jim Brickell
Northern Region
Federal Bldg., Timber, Coop. For. and Pest Mngmt.
P.O. Box 7669, Missoula, MT. 59807
Hank Cheatham
Intermountain Region
Fed. Bldg., Timber Management
324 25th St., Ogden, UT. 84401
James Dick
Southwestern Region
Fed. Bldg., Timber Management
517 Gold Ave., S.W.
Albuquerque, NW. 87102
Ray M. Ellis
Eastern Region
310 W. Wisconsin Ave.
Milwaukee, WI 53203
Gyde Lund
Washington Office NFS
Timber Management Staff
U.S. Department of Agriculture South Bldg.
12th & Independence., S.W.
Washington, DC. 20250
54
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Bill Martin, Roy Belcher
Southern Region
1720 Peachtree Rd., N.W.
Atlanta, GA. 30367
Mel Mehl
Rocky Mountain Region
11177 West 8th Ave.
Box 25127
Lakewood, CO 80255
George Rogers
Alaskan Region
Fed. Office Bldg., Timber Management
P.O. Box 21628, Juneau, AK. 99802-1628
John Teply
Pacific Northwest Region
319 S.W. Pine St.
P.O. Box 3623, Portland, OR. 97208
Other reviewers who provided helpful comments
Joe Barnard
National Vegetation Survey
USDA Forest Survey
PO Box 12254
RTP, NC 27709
Kurt Riitters
NSI Technology Services
Environmental Protection Agency - AREAL
PO Box 12313
2 Triangle Dr.
RTP, NC 27709
55
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