Biometricsand Inventory RemoteSensingJ
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however, some errors may remain.
Multistage
RemoteSensing
IbwardanAnnualNationalInventory
Forest
Council1992).TheAgricultural
heForest
Inventory
and
Analysis
Remote
sensing
canimprove
efficiency
ofsta(FIA)program
of theUSDA Research, Extension, and Education
tistical
information.
Landsat
data
can
identify
ForestService
produces
a base- Reform Act of 1998 (PL. 105-185,
andmap
afewbroad
categories
offorest
lineandlong-term
setof scientifically Section253) directsthe ForestService
cover
andlanduse.However,
more-detailed sound resourcestatisticsfor the 748 milto produce
more-timely
F1Adataand
lion acres of forest and woodland
to betterutilizeremotely
sensed
data.
information
requires
asample
ofhigherin theUnitedStates.
These
resolution
imagery,
which
costs
less
than
field ecosystems
dataareusedto assess
the extent,health, Rates of Change
databutconsiderably
more
thanLandsat
productivity,
andsustainability
of pubRapidchanges
in forestconditions,
data.
Anational
remote
sensing
program
licandprivate
forestlands.
FIAinforma- realor perceived,
fuelthedemandfor
would
beamajor
undertaking,
requiring
tion is criticallyimportantat many annual
FIA data.Rapidchanges
aredriunprecedented
partnerships
between
federal scales
to effectively
dealwith conserva- venbyurbanization,
implementation
of
programs
andstakeholders.
tion challenges;
influence
patterns
of publicpolicies,
and fluctuating
ecocapitalinvestment;
andmeettheneeds nomics
in theforest
products
andagriof theforestry
profession,
resource
man- cultural
sectors
overlargegeographic
reBy RaymondL.Czaplewski
agers,
forest
landowners,
andthepublic. gions(from 10 millionto 50 million
FIA methods
varysomewhat
by re- acres).Examples
includeclearingof
gion,but thefollowing
description
isa forestland
foragricultural
orurbanuses,
validgeneralization.
Thefirstphase
uses conversion
of agricultural
landsinto
a sampleof 9.4 millionplots,with one forestland,
harvesting
of wood,andreplotper240 acres.
Eachplotisinexpen- generation
of harvested
forests.
Other
sivelydassified
intoa fewcategories
of rapidchanges
areepisodic,
caused
by
land coverusinghigh-altitude
aerial hurricanes,wind, ice storms, floods,
photography.
The second
phaseusesa droughts,
andinsectepidemics.
These
subsample
of 364,000 one-acrefield processes
cause
changes
in forestcover
plots.120,500of whichareforested, thatcanbedetected
withavarietyof rewith oneplotper6,200acres.
A two- motesensing
technologies,
thesuccess
personfield crew can measureone ofwhichdepend
onsensor
resolution.
I assume that other indicators of
forested
fieldplotin oneday.The ForestHealthMonitoring
(FHM) program forestconditions
change
moreslowly
measures
more-expensive
indicators
on amongdetailedcategories
of forest
a subsample
of 13,500plots,4,500 of (table1). An exampleis the average
whichareforested,
with oneplotper volumeandnumberof treesperacre
167,000acres.Remotesensing
at the by treespecies
andtwo-inchdiameter
firstphaseimproves
FIA estimates
of class.I makethesameassumption
for
forestareaandpopulation
totals,but trendsin downwoodydebris,nontree
detailed
information
onforest
composi- vegetation,
andsimilarcharacteristics.
tionandcondition(table1) primarily Manyotheraspects
of foresthealthare
relies
onexpensive
fielddata.Forest
Ser- affected
by gradualchanges
in forest
vicefunding
in 1999was$37.2million. demographics
andanthropogenic
stresAlthoughFIA is amongthe best sors,such as air pollution, climate
programs
ofitskindin theworld,more change,exoticspecies,
and diseases.
than half of all FIA information is outTheseslowandubiquitous
processes
of-date.CurrentFIA procedures
and are measured
with field plotsin the
fundingallowa 10- to 15-yearremea- FIA andFHM programs.
surement
cycle,butdatamorethanfive
If theseassumptions
are approxiyearsold are not reliable(American matelytrue,thenremote
sensing
could
44
December 1999
be moreefficientthan field plotsfor
frequent
monitoring
of rapidchanges.
However,
less-frequent
remeasurement
of fieldplotsremains
essential
to monitorgradual
changes
in forest
composiuonandcalibrate
forerrors
in remotely
sensed measurements.
RemoteSensingTechnologies
Remotesensing
canimproveefficiency
if remotely
sensed
dataareavailablewhenneeded
andif theyarewell
correlated
with importantfieldmeasurements
(table1). Forexample,
augmentation
of fielddatawithaerialphotography
canbesixto 15timesmoreefficientin estimating
totalareaof forest,
andtwiceasefficient
in estimating
total
wood volume (Aldrich 1979). A wide
range
ofremote
sensing
technologies
are
usedin forestry.
Satellite
dataarecorrelatedwith someattributesin table1, but
•nformation content increaseswith sen-
sor resolution.Regardless,
remotely
sensed
datacontainvarious
degrees
of
measurement
errors
thatrequire
statistical calibration with current FIA field
data.My discussion
of satellite
datais
based
onreviews
byWynneandCarter
(1997)andHolmgrenandThuresson
(1998);myassessment
ofaerial
photographyisbased
onAldrich(1979).
six-mileswathwidth,andsmallpixel
measured
by a satelliteorbiting500 size of three to 10 feet wide, are best
milesfromEarth.Thesedatacansepa- suitedfor imagingsmallsites.These
datahavecapabilities,
limitapensive
andcovervastareas,
havinga rate forestfrom nonforest,and reason- satellite
similar
to high-altitude,
600- to 1,800-mileswathwidth.Spa- ablyidentifya fewbroadtypesof forest tions,andcosts
1:40,000small-scale
ual resolution
ispoor,witheachpixel and severallevelsof forestdensity. nine-inch-square,
fromtheUS Geodatacandistinguish
more-de- aerialphotographs
ranging
between
160and320 acres
in Landsat
Survey
(USGS)National
Aerial
of forestcoverwith logical
s•ze.Thesedatahaveprovedsuccessfultailedcategories
Photography
Program
(NAPP).
Each
customized
approaches
(Wynne
and
for continental
scalemapsof forested
NAPP
photograph
covers
an
area
five
Carter
1997).
These
data
can
identify
landscapes,
globalchange
models,
and
andphotobut theyarelesssuc- mileswide.Thesesatellite
detecting
hotspots
of severe
deforesta- recentclearcuts,
datacanreliably
distinguish
a
withpartialcuts.Landsat
data graphic
non within denselyforestedland- cessful
types
offorest
in eachregion,
regeneration
of fewbroad
scapes.
Theseremotely
sensed
datado canidentifyadvanced
not have sufficient resolution to relistages
of standdevelopment,
forests
afterlandclearing.
Thesedata several
andmanypartiallycutareas,
buttheyare clearcuts
ablymeasure
andmonitormostindica- canidentifyurbancenters,
tors of forest conditions in table 1.
afterlandclearing,
and
less
successful
withsparse
urbanization. regeneration
Medium-resolution satellite data inof treemortali•.Photo
Theycanmeasure
size,shape,
andcon- concentrations
clude Landsat-S&7, Radarsat,SPOTcanidentifyforeststands,
nectivityof forestpatches.
High-qual- interpreters
to adjacent
roads
and
dataare available
for landuse,distance
2&4, IRS-C&D and P2&5, Spin-2, ity, cloud-free
EOS AM-1, and CBERS-I&2. These mosttemperate
andmany
regionseachyearor water,forestfragmentation,
Depending
on
sensors
havea reasonably
smallpixel two, which is sufficientfor annual in- typesof urbanization.
scale,it wouldtake200,000 to 1 million
s•zeof30 to 100feetwide,andtheyare ventoryandmonitoring.
to cover
theUnitedStates.
The
relativelyinexpensive
for largeareas,
High-resolution
satellite
datainclude images
Statistics
havinga 30- to 100-mileswathwidth. Ikonos-2, OrbView-3&4, EROS- USDANationalAgricultural
1&2, although Service and USGS National Wetlands
Forexample,
theconterminous
United B1&2, andQuickbirduseNAPPphotographs
for
yet.The two-to Inventory
States
iscovered
by540Landsat
scenes. noneareoperational
Low-resolution satellite data include
However,thereis a limit to what canbe
AVHRR, MODIS, OrbView-2, ERS2, and SPOT 4. These data are inex-
Journalof Forestry 45
nationalmappingon a 20-yeartime the country,but onlya fewprograms scaleNAPPphotography
for 9.4 milframe,butthisisnotpractical
foran- consistently
coverthewholecountry. lion photo-interpreted
plots. The
nualmonitoring.
The NAPPschedule Several
of theseprograms
useLandsat USDA Natural Resources Conservaforimage
acquisition
ispoorly
suited
to datato maptheconterminous
United tion Service's National Resources Inannual
monitoring,
butsatellite
dataare States.
Otherprograms
usea sample
of ventory(NRI) usesNAPP andsmallexpected
to beavailable
whenneeded. higher-resolution
aerialphotography formataerialphotography
for300,000
statistical
estimates.
Large-scale
aerialphotography
ranges to produce
primarysamplingunits.Most samThe USGS Multi-Resolution Land
in scale from 1:2,500 to 1:12,000.
plingunitsare160acres,
witha samCommercial
aerialsurveycompanies Characteristics
(MRLC) programuses plingintensity
of 1 to 4 percent
of the
routinelyacquirethistypeof custom Landsat
datato mapthreeforestcate- totallandarea.Accuracy
of NRI datais
imageryfor smallsites.Eachphoto- gories,threeurbancategories,
three limitedby qualityandscheduling
of
graphcovers
an areaone-tenthto two woodland
categories,
threeagricultural aerialphotography.
NRI hasbeenconmileswidedepending
onscale
andfor- categories,
and21 othercategories
of ductedonceeveryfive years,but is
mat. Photointerpreters
couldreliably landuseandcover(Volgelmann
et al. changingto an annualsystem,much
identifymanyof theforestcovercondi- 1998).The USGSGapAnalysis
Pro- likeFlA.Theannualbudget
forNRI is
tionsin table1. Measurements
might gram(GAP) mapscriticalhabitatsto $8.5 million.Finally,USGSNational
include
fiveto l 0 broadtypes
of forest; help conservebiologicaldiversity. Wetlands
Inventory
uses
a sparse
samfivestages
of standdevelopment;
three GAP uses18 categories
of forest,al- pleof small-scale
NAPPphotography
stand-density
dasses;
clearcut
andpar- thoughnot all occurin everyregion. for its estimatesof statusand trends,
tialcutareas;
regeneration
success;
stand Both programsusesophisticated
re- but thisis a minorpartof its overall
origin(natural,artificial);threeto five motesensing
techniques
that require mappingprogram.
severity
levelsfor treemortality;most considerable
analytical
input.MRLC
indicators of urbanization and fine scale began
in 1995withanannualbudget The MinnesotaExperience
forestfragmentation;
and standsize, of $10 million,and GAP beganin
The AnnualForestInventorySysshape,
andedgemetrics.
Thistypeof 1994with an annualbudgetof $3.6 tem(AFIS)began
in 1991asajointefphotography
wouldrequire
manymil- million.Neitherprogram
hasyetcov- fort betweenthe MinnesotaDepartlionsof images
to completely
coverthe eredthe entirecountry.Thesepro- ment of Natural Resources and the
nation,but sampling
makesthisim- gramsplan to updatetheir mapsto USDA Forest Service. Lessons learned
agery
feasible
onthenational
scale.
compensate
for changes
in landcover, in AFIS are relevant to the mandate in
perhaps
on a 1O-year
cycle.
PublicLaw105-185.AFISsuccessfully
UsingRemotelySensedData
Threeprograms
usea sample
of aer- used numerous Landsat scenesto clasNumerous
landmanagement
agen- ial photography
to coverthe United sifylandcoverinto a fewbroadcateciesuseremotesensing
for portions
of States.The FIA programusessmall- goriesanddetectabruptchanges
over
December 1999
time.AFISprocessed
Landsat
datathat Much of the expensivefield data
wasre-imaged
overfour-year
intervals, merelyverifiedwhetheror not these
but vigorous
regeneration
of dearcuts plotswereclearedof trees.In the bereduced
theaccuracy
of change
detec- ginning,AFISdid not useaerialphotion.HadLandsat
databeenpurchased tography
because
Landsat
islessexpenalongorbitalpathsratherthanphysio- sivefor largeregions.During later
graphic regions,changedetection stages
ofAFIS, a sample
of aerialphocouldhavebeenconducted
everytwo tographywas reconsidered
because
yearsat littleextracost.A singletech- high-resolution
imagerycouldreduce
niciancouldprocess
a Landsat
scene
in thecostof fielddatato verifychange
fiveto 10daysbecause
changes
in land detection from Landsat data.
cover
weredetected
withsimple
digital
Multistage Sampling
AFIS
demonstrated
that Landsat
datacanimproveFIA products.
However,Landsat
dataalonedonotgreatly
reducethe requiredamountof field
data.Landsat
provides
onlybroadinformation about forestconditions,and
the detailed information in table 1 re-
quiresfield measurement.
However,
high-resolutionimagery provides
much more detailed data that are bet-
methods. AFIS classifications of land
coverwith LandsatreplacedNAPP
photography
for the firstphasein the
FIA statistical
design,
andimageacquisition dates for Landsat were more
compatible
thanNAPP for an annual
system.
In addition,Landsat
provided
mapsof landcoverandchange
thatare
notfeasible
forlargeregions
withaerial
photography
orfieldsampling.
If Landsatdatasuggested
that an
FIA plotmighthavebeenaffected
by
timberharvest
or change
in landuse,
thentheplotwasremeasured
bya field
crew.Remeasuring
consumedabout
halfthebudget
forfielddata.Misregistration and other errors with Landsat
data caused incorrect dassification of
someFIA plotsas havingchanged.
Realor perceivedrapid changesin
forest cover and conditions
fuel the
demand for annual FIA data. The causes
of suchchangescanbe detectedwith a
varietyof remotesensingtechnologies
and data types.Levelsof sensorresolution are key to successful
detection;
some of those levels are illustrated
in
this sequenceof photographsof the
Beaverhead-Deerlodge
NationalForest
in Dillon, Montana.
Left to ril•ht: A LandsatThematic
Mapper(TM) satelliteimage;a higherresolutiondigital ortho quad image;
a high-altitudeaerialphotograph;a
digitalinfraredcameraimage(above).
Thelatter wastakenfiveyearsafter the
TM image,closerto the time whenthe
changein forestcoverwasinvestigated.
Toassessconditionsat the forest,plot,
and tree levels costs less than field data
but more than Landsat data.
All imagescourtesyof USDA ForestServiceRemote
SensingApplications
Center,Salt LakeCity,Utah
Journalof Forestry 47
ter correlated with attributes in table 1.
changes
overthefive-year
intervalbe- resolution
images
eachyear.Expectanumerous
A multistage
statistical
design
cancom- tweenacquisition
of newimageryfor tionsmustbekeptrealistic,
bine wall-to-wall Landsat data at the
andformidable
eachpermanent
sampling
unit.High- detailsawaitanalysis,
firststage,
a sample
of high-resolutionresolution
imagery
couldimprove
sta- problems
remainunsolved.
Multistage
imagery
at thesecond
stage,
andtradi- tistical
efficiency,
allowing
a reduction sampling
withremotesensing
wasentionalFIA andFHM fieldplotsat the in the requirednumberof FIA sam- visionedby theNationalAcademyof
thirdstage.
The NationalAcademy
of plingunits.Calibrated
measurementsSciencesin 1974, but the vision has
Sciences
recommended
a similarap- fromthehigh-resolution
images
might neverbeenimplemented.
However,
•f
proach
25 yearsago(Aldrich,1979).I evenreplace
fielddatafor inaccessiblethesechallenges
canbe overcome,
a
describetwo enterprises
that would areas.
The largesampling
unitsbetter partnershipamongexistingfederal
implement
a multistage
design.
matchthe scaleof Landsatimages programs
couldproducethe world's
The firstenterprise
wouldacquire thanone-acre
FIA plots,thusimprov- premiersystemto estimatenational
all Landsat scenes that cover the coningthelinkagebetween
Landsat
data trendsin land coverand land use,determinous United States. Multi-date
and more accurate measurements of
tectchanges
in healthofwildlands
and
Landsatdatawouldrapidlyidentify sampling
units.Thisenterprise
could agricultural
landscapes,
evaluate
effecabruptchanges
in spectral
reflectance cost $15 million to $25 million each tiveness
of publicpolicies,
andguide
that are often associated with clear-
year.
sustainable use of the nation's natural
is similarto resources.
cuts,landclearing,
andreforestation. The latterenterprise
Changedetection
allowsrelatively
in- the National ResourcesInventory
expensive
updates
to existing
MRLC (NRI). The costof newimageryand Literature Cited
R.C.1979.Remote
sensing
ofwildland
resources
and GAP maps.FIA woulduseup- interpretation
might be sharedbe- ALDRICH,
A state-of-the-art
review.
General
Technical
Report
datedmapsto replace
itsphotointer- tween FIA and NRI, which would
RM-71. Fort Collins, CO: USDA ForestService,
pretationof 9.4 million first-phase maketheenterprise
morefeasible
and
Rocky
Mountain
Forest
andRange
Experiment
Station.
plots.Directannualcostis estimated efficient.This partnership
poses
conFOREST
COUNCIL.
1992.Report
oftheblue
at $1.5 million to $2 million.
siderable
technical
challenges,
suchas: AMERICAN
ribbon
panel
onjCrest
inventory
andanalysis.
WashingThe secondenterprise
wouldac- incremental
alignment
of separate
FIA
ton, DC.
quirea nationalsampleof large-scale and NRI samplingframes;complex CZAPLEWSKI,
R.L.1999.Integration
ofstrategic
invenaerialphotography
or high-resolutionstatistical
techniques
for calibration toryandmonitoring
programs
fortheforest
lands,
range
lands
andagricultural
lands
ofthe
of multipletime-series woodlands,
satelliteimagery.
The resulting
data andcomposites
United
States.
In
Proceedings
of
the
North
American
sample
data;a sophistiwoulddetectchanges
in landuse,par- of multivariate
Science
Symposium,
7•ward
a Unified
Framework
er
tial cuts,forestmanagement,
andse- catedinformationmanagement
sysInventorying
andMonitoring
Forest
Ecosystem
Resources,
in the aerial
vereepisodic
events.
Sample
imagery tem; capacity-building
Guadalajara,
Jalisco,
Mexico,
November
1-6, 1998
Fort Collins,CO: USDA ForestService,
Rocky
wouldinclude364,000primarysam- survey
industry
to deliver
largequantiMountain ResearchStation.
plingunits,eachcovering
anexisting tiesof photography;
andadjustments HOLMGREN,P.,andT. THURESSON.
1998. SatellitereFIA field plot. Eachsamplingunit for cloud coverand missingdata
motesensing
forforestry
planning--a
review.
Scan&1999).Bureaucratic
chalcouldrangefrom40 to 640 acresin (Czaplewski
navian
Journal
ofForest
Research
13:90-110.
size,and the collectionof sampling lengeswouldbe equallyformidable USDA FORESTSERVICEINVENTORYAND MONITORING
INSTITUTE.
1998.Integrating
surveys
ofterrestrial
natunitswouldencompass
1 to 10 per- (USDA ForestServiceInventoryand
uralresources:
TheOregon
Demonstration
Project.
Incentof thetotallandarea.The large MonitoringInstitute1998). Robust
ventory
andMonitoring
Institute
Report
No.2. Fort
sampling
unitswouldbettercapture solutionsto these challengesare
Collins,
CO:USDAForest
Service,
Rocky
Motrattan
rare features than one-acre FIA field
untested, cost-effectivenessmust be
plots,whichencompass
only 0.016 evaluated, and risks must be reduced
percent
of thelandscape.
Eachyear,20 through
simulations
andrealistic
pilot
percentof the largesamplingunits tests.
wouldbe remeasured
withnewhighresolution
imagery.
Photointerpreters Conclusion
woulddelineate
andclassify
landuses,
Congress
hasemphasized
theneed
for more-current statistical informaland cover, and forest standswithin
eachsampling
unit. Photogrammetrytion about the nation's forests. Tradi-
ResearchStation.
VOLG•LM^NS',
J.E.,T. SOHL,
P.V.C^MPBELL,
andD.M
SH^W.
1998.Regional
landcover
characterization
using
Landsat
Thematic
Mapper
dataandancillary
sources.
Environmental
Monitoring
andAssessment
51:415-28.
WYNNE,R.H., and D.B. C^RTER.1997. Will remote
sensing
liveuptoitspromise
forforest
management>
Journal
ofForestry
95(10):23-26.
would producemore-detailed
mea-
tionalFIA fieldprocedures
wouldsatisfythisneedat an estimated
annual
secondary
sampling
pointswithineach costof $82million.Multistage
remote
40- to 640-acresamplingunit, and sensing
mightsave$20 millioneach
oneof thesepointswouldbe a one- yearandproduce
valuable
newprodacreFIA field plot. Thesemeasure- ucts.Implementation
requires
an unments would be well correlated with
precedented
infrastructure
thatcanacmany field observations
in table 1. quireandprocess
hundreds
of Landsat
Photo interpreterswould measure scenes
andtensof thousands
of highsurements of forest characteristics at
48
December 1999
Raymond
L. Czaplewski
(e-mail:czap@
lamar.
colostate.
edu)isproject
leader
and
mathematicalstatistician,ForestInven-
tory and MonitoringEnvironmetrics,
USDAForest
Service,
Rocky
Mountain
Research
Station,240 l•st Prospect
Road, Fort Collins, CO 80526.