PEER.REVIEWED
TECHNICAL
ARTICTE
BRIEF
Level1,
Noteonthe Useof USGS
for
DEMGoverages
T,SMinute
Analyses
Drainage
Landscape
J. Garbrechtand P. Starks
lntroduction
The intuitively appealing notion to define topographic characteristics of complex landscapes from digital elevation models (nEt,ls) has lead to numerous nsNl evaluation procedures
and applications, In the field of hydrology and water resources, landscape characterization has focused predominantly on the definition of the drainage network, drainage
divides, flow paths, and local slope and aspect (Band, 1986;
Fairfield and Leymarie, 1991; fenson and Domingue, 19BB;
Martz and Garbrecht, 1992; O'Callaghan and Mark, 1g8q;
Skidmore, tg90). Given the success of previous applications
(fenson, 1991; Moore et al., L991.;Quinn ef 01., 1991; Tribe,
1991), the authors intended to investigate the characteristics
of depressional wetlands and their contributing drainage areas in south central Nebraska using available usGS 7.5-minute DEM coverages. However, limitations in the DEM
coverages prevented the proposed investigation of depressional wetlands. The authors experience with their application of Level 1 7.5-minute DEMs is reported here. First, the
limitations and systematic errors in the DEMs representing
the region under consideration are illustrated, and their impact on the drainage analysis is exemplified. Second, the reasons for the unsuccessful application are discussed and a
simple, custom-produced DEM coverage is presented. The intent of the paper is to caution hydrologists and hydraulic engineers in the indiscriminate use of certain DEMs,and to
expose the need for hydrographically consistent nnMs for
drainage analyses.
DEMCoverages
CIay County in south central Nebraska was selected for the
depressional wetland investigation. The region is characterized by low relief (on the average, a 15-m vertical change
over a horizontal distance of about 10 km) and numerous
wetlands ranging in size from a few to several hundred hectares. The USGS7.s-minute topographic quadrangles and the
conesponding DEM coverages for the geographic area under
investigation are listed in Table 1. On the topographic quadrangles, depressions are defined by hachured contours as illustrated for the northeast corner of the Fairfield quadrangle
(Figure 1). The hachured contours that define depressions are
highlighted by thicker lines. Several depressions are deep
enough to require two 1O-ft contours for their full vertical
definition (Figure 1). The Iargest depression, Massie Lagoon,
which is the focus for the remainder of the discussion, is de-
USDA-ARS,National Agricultural Water Quality Laboratory,
P . O . B o x 1 4 3 0 ,D u r a n t , O K 7 4 7 0 2 - 1 . 4 3 0 .
PE&RS
fined by single hachured lines below the 1760-ft contour and
by douLle hichured lines below the 1750-ft contour. The
oltlines of the depressionare generally smooth and well defined, and the contributing areascan be inferred from the
contours surrounding the depressions'Drainagechannels
outside the depressionare easily recognizedby contour crenulation and the denser contours that define valley sides
(lower left corner in Figure 1). Given the unambiguous definition of the drainagefbatureson the topographic quadran-gles and the significlnt depth of the depression,a numerical
inalysis of the topography using available USGS7'5-minute
DEMcoverageswis ittempted in order to automatically define the locition, extent.iize, and shapeof the depression
and its contributing area.
Computerdisplay of the usGS7.5-minuteDEMcoverages
in Table 1 show consistentand systematiceast to west strip-
ticularly visible in the northeastern,western, and southeastern poriion of the coverage(Figure 2). The absenceof the
striping on the topographic maps and the regularity with
which ihey appeal in the DEMdisplay suggeststhat they are
artifacts of the lsu.
The impact of the striping on the proposed automated
wetland analysis,and on drainagestudies in general,is
threefold. First, the outline of drainagefeatures,such as depressionsor drainagepaths, is not well defined. Smooth outiines that have a north-south direction (perpendicularto the
striping) are often representedin the DEMas raggedlines
havine east-westindentations of about 90 m width. For example] the outline and the shape of Massie Lagoon in the
DEMcoverageare difficult to identify. The DEMcoveragesuggeststhat the lagoon is a parallel sequenceof shallow
irenches. Second,drainagepaths are systematicallybiased in
the east-westdirection becauseof the flow draining into and
following the stripes that identify a lower elevation. And
third, th; striping may introduce apparent drainageblockage
for drainagepaths that have a north-south flow component.
These appirent drainageblockagescan produce many artifiPhotogrammetricEngineering& Remote Sensing,
v o l . 6 1 , N o . 5 , M a y 1 9 9 5 ,p P . 5 1 ' S - 5 2 2 .
0 0 9 9 - 1 1 2 l 9 5 / 6 10 5 - 5 1 9 $ 3 . 000 i
O 1995 American Society for Photogrammetry
and RemoteSensing
PEER.REVIEWED
Trerr 1.
USGS7.s-MtNUreTopocnnpHrcQuADRANGLES
Ar.roCoRnesporlotllc
DEMCovERAGEs
roR tHe Recror.rUr.roeR
ltvesttcnttott.
Quadrangle Name
Trumbull, Nebraska
Hasting East,Nebraska
Pauline, Nebraska
Lawrence,Nebraska
Fairfield, NW, Nebraska
Harvard NW, Nebraska
Inland, Nebraska
Harvard NE, Nebraska
Harvard, Nebraska
Fairfield, Nebraska
Fairfield SE, Nebraska
Deweese,Nebraska
Contour interval
in feet
5
5
10
10
10
5
10
tr
10
10
10
cial depressions,some of which reach considerablesize as
exhibited in the Fairfield nnu coverage(Figure 3). According
to the elevationsgiven by the DEM,approximately 20 percent
of this coverageconsistsof depressions.Many of the depressions follow major channels,indicating that the channels are
continually blocked by the artificial striping in the DEM.On
the other hand, the depressionarea on the UScS7.b-minute
topographic quadranglesis only about 5 percent. Taken together, the above three effectsof the striping on drainagefeatures render the available USGS7.S-minuteDEMcoverages
listed in Table 1 unusable for the depressionalwetland investigation.
ARIICIE
the 1970sat a time when today's modern and accuratetechniques were not available.DEMsthat are developed today are
generally derived from Digital Line Graphs (nr,cs)and are
processedfor consistencyand edited to remove identifiable
systematicerrors. These nEMsare classifiedas Level 2 and
do not exhibit the above describedproblems. However, it is
important to note that the majority of the available USGS7.5minute DEMcoveragesare Level 1 DEMseven though not all
were developed with the manual profiling technique. Therefore, the limitations of the DEMsdiscussedhere generally apply to those coveragesdeveloped from manual profiling ofphotogrammetricstereomodelsand for low relief topogiaphic
conditions similar to those encounteredin this investigation.
Other Level 1 DEMprocessingtechniques,such as the Gestalt
Photo Mapper II, have their own systematicerrors within the
stated accuracystandards,and these may also adverselyaffect drainageanalyses.
Once the limitations of the DEMcoverageswere recognized, two alternativeswere considered:editing the existlng
coveragesor development of a custom DEM.The editing consists of either smoothing the coverageby using a box-car raster smoothing, or by applying
a one by five custom raster
^tle
filter perpendiculai to
str'iping.Boih alternativeswould
smgg+ out the striping, but were rejectedbecausesmoothing
and filtering reduce the relief and the definition of the outline of drainagefeatures.Retaining relief is critical for the
definition of depressionalwetlands which have little relief to
begin with. Also, smoothing can introduce new drainage
blockagesat narrow passagewaysin the landscape,restricted
valleys, and/or incised channels.
Soutces
ofSystematic
DEMEnor
The source of the striping is related to the DEMproduction
technique. All 12 DEMcoveragesused in the wetland investigation were developedusing manual profiling from photogrammetric stereomodelsof National High-Altitude
Photography.In this production technique, profiles €ueusually scannedat g0-m separation,with elevationsrecorded at
varying intervals depending on terrain characteristics(U.S.
GeologicalSurvey, 1990). The scan proceedsfrom east to
west and then from west to east,and so forth until the coverage is completed. The striping introduced by the manual
profiling is a combination of human and algorithmic errors
(B. Kunert, U.S. GeologicalSurvey, personal communication,
1993). The human error results from the slightly different
perception the technician has of the ground as he/she scans
either from east to west, or from west to east.The algorithmic error is introduced by the interpolation algorithm for elevations between the scannedprofiles. Together,these errors
result in the observedsystematicand identiftable striping
shown in Figure 2 (B. Kunert, U.S. GeologicalSurvey, personal communication, 1993).
The DEIr,ls
produced by manual profiling from photogrammetric stereomodelsare classifiedas Level 1 DEMs.The
desired accuracystandard for Level L DEMsis a vertical rootmean-squareerror (Ruse) value of 7 m, with a maximum
permitted value of 15 m. An absolute elevation error tolerance of 50 m relative to the true height from mean sea level
is set for blunders for any grid node. Also, an array of 49
contiguous elevation points shall not be in error by more
than 21 m. It is also emphasizedthat svstematiceirors
within the stated accura;y standardsare tolerated (U.S. GeoIogical Survey, 1990).These include the previously discussed striping. Many of the Level 1 DEMswere developedin
520
Figure1. Northeastcornerof the FairfieldQuadrangle;
MassieLagoonis highlighted
by the hachuredarea.
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PEER.REVIEWED
ARIICTE
andConclusions
Summary
The Iimited application potential of certain uscs Level 1 7.5minute luM cbveragesfor drainageanalysesis presented.-The Level 1 DEMscbnsideredin this study were produced by
manual profiling from photogrammetricstereomodelsof National High-Altiiude Photography.The geographicarea for
the invesligation is situated in Clay County, south central
Nebraska.The evaluation of 1'2contiguousDEMsshowed systematic and identifiable scan striping. The striping distorted
the outlines of drainagefeatures,biased the flow paths, and
introduced apparentblockageof flow. The source of the
striping *as ielated to the manual profiling technique' The resrrlting anomalieswere found to be within the USGSstated
ac"l-,rac| standards for Level 1 DEMs.Subsequent-manipulation of ihe DEMcoveragesto remove the striping by smoothing and filtering were ieiected becauseof the additional data
degradationthat they would introduce. A custom DEM,interpolated from digitized contours, proved adequateto conduct
the drainageand wetland analysis.
The unsuccessfulapplication of the usGSLevel 1 7.5-
Figure2. DEMcoverageof the FairfieldQuadrangleas
displayedby a GlS.
The alternative selectedby the authors is a custom DEM
derived from the contours of uscs 7.S-minutetopographic
quadrangles.The contours of the wetlands and their contributing areas,including immediate surrounding areas,are digitized. The digitized contours are then interpolated into a
raster DEMusing a two-part algorithm. First, a searchradius
around the grid point is selectedand those data points falling within that radius are assigneda weighting coefhcient
based on the distance from the grid point. Next, the grid
point is assigneda DEMvalue which is the weighted sum of
ihe data points divided by the sum of the weighting coefficients. In order to ensure accuratedepressionalanalysis,a
small searchradius must be chosen to eliminate the influence of outlying data points. However, a small searchradius
often necessitatesthe addition of supplementarycontours in
areaswhere contours are few and far between. The result of
this DEMproduction is shown in Figure 4 for the Massie Lagoon. The outline of the wetland, as well as the other neighboring wetlands, is well reproduced and conforms closely to
the depressionboundaries defined by the contours on the
USGst.s-minute topographic quadrangles(Figure 1).
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Figure3. Locationand extentof depressionin the Fairfield DEMcoverage;depressionsare definedby the white
areas.
PEER.NEVIEWED
Figure4. CustomDEMof the geographic
areaencompassingthe Massie Lagoon.
minute DEMcoveragesproduced by manual profiling is attributed to the requirement of a high tei.a resolution and
consistency for drainage analyses.The systematic errors encountered in the Level 1 DEMcoveragesare too large for the
proposed drainage analysis even though they are within the
stated accuracy standards set forth by the USGS.Therefore,
caution is advised: the availability of uscs Level 1 7.S-minute
DEMcoveragesdoes not necessarily guaranteea data source
for a landscape analysis of drainage features.More detailed or
higher resolution digital elevation data may be necessiry.
References
Band, L.E., 1986.TopographicPartition of Watershedswith Digital
Elevation Models, Water ResourcesResearch,22(I):75-24.
Fairfield, fohn, and P. Leymarie, 1991.DrainageNetworks from Grid
Digital Elevation Models, Water ResourcesResearch,ZZ(S):7O9fenson, S.K., 1991. Applications of Hydrologic Information Automatically Extracted from Digital Elevation Models, Hydrological
Processes,5i3'L-44.
[enson,S.K., and J.O.Domingue, 1988.ExtractingTopographic
Structure from Digital Elevation Data for Geographic Information
System Analysis, Photogrammetric Engineering & Remote Sensrng,54(11):1593-1600
ANTICTE
Martz, L.W., and f. Garbrecht, 1992. Numerical Definition of
Drainage Network and Subcatchment Areas from Digital Elevation Models, Computers and Geosciences,An Intemational lournal, 18(6):747-761.
Moore, I.D., R.B. Grayson,and A.R. Ladson, 1991. Digital Terrain
Modelling: A Review of Hydrological, Geomorphological,and
Biological Applications, Hydrological Processes,5:3-30.
O'Callaghan,J.F.,and D.M. Mark, 1984. The Extraction of Drainage
Networks from Digital Elevation Data, Computer Vision, Graphics, and Image Processing,28:323-344.
Quinn, P., K. Beven,P. Chevallier,and O. Planchon, 1991.The
Prediction of Hillslope Flow Paths for Distributed Hydrological
Modelling Using Digital Terrain Models, Hydrological proCesses,
5:59-79.
Skidmore,A.K., 1990.Terrain Position as Mapped from a Gridded
Digital Elevation Model, International lournal of Geographical
Information Systems,4 :33-49.
Tribe, A., 1991. Automated Recognition of Valley Heads from Digital
Elevation Models, Earth Surface Processesand Landforms, 16:
33-49.
U.S. Geological Survey, 199O.Digital Elevation Models Data users
Guide, Reston,Virginia, 51 p.
(Received19 July 1993;accepted1o November 1993; revised 13 December1993)
furgen Garbrecht
JurgenGarbrecht,8.S., Swiss Federal Institute of
Technology,Zurich; M.S. and Ph.D. Colorado
State University, has been a ResearchHydraulic
Engineer at the USDA-ARS,National Agricultural Water Quality Laboratory in Durant,
Oklahoma since 1.988.His interestsinclude large scale hydrologic modeling, surfaceand channel runoff processes,and
integration of cIS technology and traditional hydrologic models.
Patrick ). Starks
Patrick J. Starks is employed as a Soil Scientist
at the USDA-ARS, National Agricultural Water
Quality Laboratory in Durant, Oklahoma. He received his B.S. degreein Geographyfrom the
University of Central Arkansas (1979),Conway,
and_the M.A. degree in Geography from the University of Nebraska-Omahain 1.984.In 1990 he was awarded the PhD degree in Agronomy from the University of Nebraska-Lincoln
where he specializedin micrometeorologyand remote sensrng.
MUTTIPURPOSE
GADASTRE:
TERMSANDDEFINTTTONS
This booklet presents a list of "core" terms and definitions that represent a good beginning to a
common vocabulary for use in GIS/LIS. Also included are terms used in the fields of automated
mapping, facilities management, land records modertrization, natural resource mlnagement systems,
and multipurpose land information systems.
1989. Dueker and Kierne. 12 pp. $S $ort.cover). Stock # 4AO8.
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