base maps require a data model that supports the...

8In 1884, John Wesley Powell, director of the USGS, envisioned the first National Map

of the United States. It was to cover densely populated areas at a scale of 1:62,500 (15‑minute quad), important mining districts at 1:125,000, and other terrain at 1:250,000. It was to include several types of information that are still today considered base map layers: transportation, hydrography, place names, boundaries, and eleva‑tion. Expected to take 24 years, the map wasn’t completed until 1990.

Certainly, you would expect that cartographic methods and standards have evolved considerably since 1884. With the growth and use of GIS in the past decade, cartographic technology and methods have changed even more. GIS‑based cartography is now an important GIS application, and it is increasingly possible and appropriate for GIS professionals to adapt cartographic compilation methods for use in their GIS data automation tasks. Most GIS users want to provide high‑quality interactive maps in their GIS.

This chapter has several objectives. The first objective is to describe the essential content of a base map within the context of a GIS and in support of the USGS National Map vision. Although there are many kinds of base maps, this chapter focuses on a topographic map because this is possibly the most complex and inclusive type of base map, the superset of most others that might be constructed.

The second objective is to demonstrate how high‑quality cartographic capabilities can be added to any existing GIS data model. GIS techniques that support high‑quality cartography are presented throughout the chapter.

The third objective is to present a design for managing a complex feature classification and descriptive system, a key issue for national mapping agencies. Project and feature‑level metadata for source tracking will also be discussed.

At the end of this chapter, you can read about the application of this cartographic data model at TNRIS. This case study presents several interesting design choices that simplify some map layers to streamline the data compilation work for cartographic needs.

Base maps require a data model that supports the generation of high-quality digital

cartographic products with varying levels of detail for a desired range of map scales.

Base maps provide a framework for GIS data use and analysis, and commonly used GIS

data from many domains may be combined with cartographic attributes to build the

base map. This chapter presents a case study for a topographic base map at 1:24,000

scale, building on work in progress at TNRIS, based in Austin, Texas.

Excerpt from Designing Geodatabases: Case Studies in GIS Data Modeling, by David Arctur and Michael Zeiler. ©ESRI Press. www.esri.com/esripress. ISBN 978-1-58948-021-6

Cartography and the base map

IntroductIon

Framework —conceptual model and layers

transportatIon admInIstratIve boundarIes

cultural Features

HydrograpHy

HypsograpHy Image base surFace overlays and IntegratIve tHemes

geograpHIc place names

page layout desIgn

color model

revIsIon management

descrIptIve classIFIcatIon model

a classIFIcatIon model Illustrated

tHe model In actIon

cartograpHIc data model summary

reFerences

308310314324330334338344346348350352354356358360370372

308 • Designing geodatabases

Base maps are used for a wide range of activities, including infrastructure planning and management, demographic analysis, and outdoor recreation. The cartographic represen-tations contained in base maps can be derived from the same multipurpose thematic layer designs used for traditional GIS as described throughout this book.

One way to think about base maps is that they are a potential application you can add to your GIS by extending your data model in specific ways to support advanced cartographic representations.

Extending base maps with GIS

Traditionally, base maps have been purely cartographic products. The earliest base maps portrayed roads, railways, canals, structures, other landmarks, and boundaries against a backdrop of vegetation, rivers, lakes, elevation points, and contour lines. GIS first emerged as a tool for thematic geographic analysis, but often fell short in meeting the demanding specifications for creating finished cartographic products. However, GIS has changed.

Using current GIS technology, common spatial representa-tions can be used for both advanced cartographic display and GIS analysis. For example, local roads are represented as lines at 1:24,000; lakes as polygons; and so on. Traditional GIS data models for these layers can be extended with symbol and label attributes to become a cartographic data model as well.

Extending any traditional GIS data model enables the data to be used effectively for thematic and other GIS analysis, as well as high-quality cartographic map products. The GIS provides numerous useful tools for editing and managing the integrity of multipurpose data used in topographic mapping.

The methods described in this chapter are meant to build on many of the data models presented in this book by adding specifications for map layers, symbols, and layer properties, as well as properties for map elements and the page layout for a topographic map series. Each section focuses on the cartographic extensions that could be reasonably applied to

IntroductIon

Base maps serve multiple purposes. As a purely cartographic product, such as reference

maps, they provide a spatial reference framework for the reader to locate and identify

objects in the surrounding terrain. Within a GIS, the base map layers provide a reference

framework for a number of critical feature and raster layers used in GIS applications and

support advanced cartographic symbols and label text.

any geodatabase schema that contains the proper geographic representations for features, such as streams, lakes, contours, and roads. You’ll find more discussion on map layers and cartographic symbols than on features and table structures.

Common themes

Some of the commonly used layers in topographic base maps include:

• Geographicnames

• Transportation(roads,railroads,airports)

• Boundaries(state,county)

• Hydrography(rivers,streams,lakes)

• Landcover(vegetation)

• Culturalfeatures(regionalcenters,urbanareas)

• Elevation(contours,spotelevations,DEMs)

• Orthoimagery

• Landsat7satelliteimagery

This list may vary from state to state and across nations. For example, TNRIS does not include land cover and groups geographic names with cultural points in its base map in adifferentmanner from theUSGSNationalMap speci-fication. In any case, these are the themes to be discussed throughout this chapter.

Cartography and the base map • 309

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Center Johnston High School

StateCapitol

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Blanton School

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Projection:Texas State Plane SouthLambert_Conformal_ConicFalse Easting: 2000000 mFalse Northing: 0 mCentral Meridian: �99.00 degreesStandard Parallel 1: 28.383333 degreesStandard Parallel 2: 30.283333 degreesLatitude of Origin: 27.833333 degrees1927 North American Datum

There might by private inholdings within the boundariesof the National or State reservations shown on the map.

VERSION 4: MAY 31, 2002

TN

MN

5º 21’

TNRIS TOPOGRAPHIC MAP PRODUCTTexas Topographic Base Map

1 0 10.5

Miles

1,000 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Feet

0 1 20.5

Kilometers

Legend for Common Features

Street or Road...................

Primary highway...............

BM

Spot Elevationsor Survey Points................

Interstate.....................

US Route.....................

Buldings andStructures...........................

Scrub.............................

Woods/Brushland..........

Built Up or Cultural.......

Education......................

Healthcare......................

Religious........................

Recreation......................

Park...............................

Municipal Boundary.....

Park Boundary..............

Fence Line....................

Levee or Dike...............

Railroad.............................

Radio Tower.................

Religious Building........

Pit, Unconsolidated Material.........................

Major Street......................

Ramp.................................

Secondary Highway..........

Military..........................

Agricultural....................Water Tank...................

Other Tank....................

S1

SCALE: 1:24,000

CONTOUR INTERVAL 20 FEET

NATIONAL GEODETIC VERTICAL DATUM OF 1983

THIS MAP COMPLIES WITH NATIONAL MAP ACCURACY STANDARDSFOR SALE BY TEXAS NATURAL RESOURCES INFORMATION SYSTEM, PO BOX 13231, AUSTIN, TX 78711�3231

A FOLDER DESCRIBING TOPOGRAPHIC MAPS AND SYMBOLS IS AVAILABLE ON REQUEST

ADJOINING 7.5’ QUADRANGLES

1. Jollyville Texas2. Pflugerville West Texas3. Pflugerville East Texas4. Austin West Texas5. Manor Texas6. Oak Hill Texas7. Montopolis Texas8. Webberville Texas

1 2 3

4

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landcover(vegetation),soiltype,andsurfacegeology.Thesecould come from many sources, including advanced very highresolutionradiometer(AVHHR)usedbyNOAA.TheNaturalResourcesConservationService(NRCS)providescounty-level soil surveys over most or all the United States.

Image base

Useful for either the map background or ground reference, this might include satellite and orthophotos; scanned maps, suchasUSGSdigitalrastergraphs(DRG);andotherthe-maticimages(seeChapter7,‘Usingrasterdata’).

Reference

Primarily intended for cartographic support for location finding, this data includes map grids or graticules and other labeled tics at the map’s edge.

Page layout design

The elements of a cartographic product might include a North arrow, a legend, source attribution, inset or locator maps, and so on.

CRoSS-CUTTING ThEMES

Labelsandotherannotationarepartofalmostalltheabovethemes. Since annotation of, for example, river names might be handled differently for cartographic purposes than anno-tation of administrative areas, it is expected that each feature class may have corresponding annotation classes.

Place names are also important across many themes. This chapter presents a simple approach for a comprehensive names table. A more elaborate approach is discussed inChapter4,‘Addressesandlocations’.

Similarly, revision information is often desired for features in various themes. This can be designed to keep track of when, why, and by whom various data was modified. One design for revision tracking is provided in this chapter.

The conceptual model is organized around the base map thematiclayersdescribedhere.Manyofthesethemesappearin other chapters of this book, which contain more detailed models.Contentfromthisdatamodelmaybeintegratedwith these other models, and vice versa.

Transportation

This includes roads, railroads, transportation infrastruc-ture,andcartographicfeatures.Asophisticatedthememayinclude transportation networks for route finding; however, this data model is focused on identification of transportation features for cartographic purposes. TNRIS obtained most ofthisdatafromtheTexasDepartmentofTransportation(TxDOT)andfromtheUSGSgeographicnamesinforma-tionsystem(GNIS).

Boundaries

Boundaries include administrative areas, such as municipal and other legal jurisdictions. This could include census boundaries,ifthedataisavailable(seeChapter3,‘Censusunitsandboundaries’).

Cultural

This theme includes any cultural features not already in other themes, such as hospitals, schools, museums, and other significant buildings or landmarks.

hydrography

Hydrography includes surface water and features for manag-ing water, such as rivers, lakes, canals, wells, and water treat-mentplants(seeChapter2,‘Streamsandrivernetworks’).

hypsography

Hypsography includes elevation points, contour lines, TINs, DEMs,andshadedreliefbasedontheDEMs.

Surface overlays

This theme could have any number of different features, depending on the purposes for the map. Examples include

Framework—conceptual model and layers

For governments trying to improve the quality and currency of their maps while reducing

duplication of effort across departments and agencies, base maps are strategic products

in their own right. Bringing together all the layers shown here requires an integrative

approach within each state. This is intended as a representative model that is expected

to vary somewhat across local and state agencies.


8

LayerMap use

Data sourceRepresentation

Spatial relationshipsMap scale and accuracy

Symbology and annotation

TransportationRepresents how goods and people move between destinations.TxDOT, USGS, GNIS.Routes, infrastructure, cartographic representations, and annotation.At least one node of road segments must connect to another road. Acceptable for 1:10,000 through 1:30,000-scale products.Organizational standard based on USGS 1:24,000-scale products.

LayerMap use




BoundariesAdministrative and legal boundaries: parks, military reservationsUSGS, Census TIGER files, councils of governmentsLines with areas to support annotationNone for TNRISAcceptable for 1:10,000 through 1:30,000-scale productsOrganizational standard based on USGS 1:24,000-scale products

LayerMap use




CulturalRepresents cultural features and landmarksUSGS, GNISPoints, lines, areas, and annotationNoneAcceptable for 1:10,000 through 1:30,000-scale productsOrganizational standard based on USGS 1:24,000-scale products

LayerMap use




ReferenceLocation findingUSGS, ArcMap graticules, and PLSSMap grids, labeled tics at map edgeContinuous data for the United States where it appliesAcceptable for 1:10,000 through 1:2,000,000-scale productsOrganizational standard for text sizes, tics, and lines

LayerMap use




LayerMap use




Image baseMap background and reference.Aerial photos, satellite imagery, USGS DRGs, other historical images.Raster.Pixels cover the image area.Pixel size is 1 to 2.5 meters; useful for products of 1:4,000 to 1:65,000.Color or grayscale.

LayerMap use




Surface overlaysOther useful themes, such as land cover, land use, and soils.Potentially many, including USGS, NRCS, AVHHR, and local sources.Areas and rasters.Different types do not overlap.Acceptable for 1:10,000 through 1:50,000-scale products.Organizational standard based on USGS 1:24,000-scale products.

LayerMap use




HydrographySurface water and features for moving, storing, and managing waterUSGS, GNISPoints, lines, and areasNone for TNRISAcceptable for 1:10,000 through 1:50,000-scale productsOrganizational standard based on USGS 1:24,000-scale products

LayerMap use




Page layout designMap collar, data use, and color specificationArcMap template and style maintained at organizational levelMap template and style for every product variationNone�1:24,000Organizational standard based on USGS 1:24,000-scale map products

HypsographyRepresents terrainUSGSElevation points, contour lines, TINs, DEMs, and hillshadesContour lines are only connected to other lines of the same elevationAcceptable for 1:10,000 through 1:50,000-scale productsOrganizational standard based on USGS 1:24,000-scale product


Surface overlays

This dataset typically contains vegetation or land cover layers if vector features are used. A topology created with this feature class can be used to help construct a clean dataset without overlapping polygons. If raster data is used, colors can be used to symbolize the pixels.

BoundariesThis dataset contains administrative boundaries for government, military, and legal jurisdictions, together with their cartographic place names as annotation. A topology is created for the boundary feature classes to ensure coincidence and tessellation as appropriate.

HypsographyThe hypsography dataset contains spot elevation points, contour lines, and their annotation (elevation values). A topology is created for contours to ensure nonintersection. When contours are derived from a DEM, such a topology is not necessary.

TablesThe nonspatial tables shown

here are used to hold place names, revision tracking

information, and to support construction of valid feature

descriptions. VVTs are described later in

this chapter.

TransportationThe transportation dataset contains the road and

railway classes appropriate to 1:24,000 scale. Infrastructure contains airports, depots, customs

facilities, and other related features. A topology is shown for road, ramp, and highway classes only but

may be extended to include railroads.

ReferenceThis reference dataset contains an index to the USGS 1:24,000-scale topographic map quad sheets. Other grids may be included according to users’ needs.

CulturalCultural points model landmarks,

lines model specific boundaries, and areas model land use zones. A

topology is used to ensure coincidence of adjacent feature

boundaries. Annotation features are used to display the place

names for each type of feature.

Feature datasetReference

Polygon feature classUSGS24KQuadSheetIndex

ATTVALTable

ATTDESCTable

FCODETable

RevisionInfoTable

PlaceNameTable

ElevationPoint_VVTTable

Contour_VVTTable

TopologyHypsography_Topology

Feature datasetHypsography

Line feature classContour

Point feature classElevationPoint

Annotation feature classHypsoAnno

Feature layerSurface Contours 20' Interval

Feature layerSurface Elevation Points

Feature datasetSurface overlay

Polygon feature classLandcover

Feature layerLandcover

TopologyBoundary_Topology

Polygon feature classLegalBoundary

Line feature classCountyBoundary

Line feature classMilitaryResBoundary

Line feature classMunicipalBoundary

Polygon feature classMunicipalAreasCarto

Line feature classParkBoundary

Line feature classStateBoundary

Feature datasetBoundaries

Annotation feature classBoundaryAnno

Feature layerFeature layerMunicipal Areas for Label

Feature layerFeature layerLegal Boundary Area

Group layer

Boundaries

Feature layerMunicipal Boundaries

Feature layerAdministrative Boundaries

Feature layerLegal Boundaries

Group layer

RoadsCartoDissolve_VVTTable

TransCartoPoint_VVTTable

TopologyTransportation_Topology

Feature datasetTransportation

Line feature classRoad

Polygon feature classInfrastructureArea

Feature layerFeature layer

Roads

Infrastructure Areas

Annotation feature classTransAnno

Line feature classRailroad

Feature layerFeature layerRailroads in Streets

Feature layerFeature layerRailroads

Line feature classRoadsCartoDissolve

Line feature classMajorHwy

Point feature classTransCartoPoint

Feature layerMany road layers

Line feature classRamp

TopologyCultural_Topology

Feature datasetCultural

Polygon feature classCulturalArea

Line feature classCulturalLine

Point feature classCulturalPoint

CulturalArea_VVTTable

CulturalLine_VVTTable

CulturalPoint_VVTTableFeature layer

Cultural Points

Feature layerCultural Areas

Feature layerStructure Polygons

Feature layerCultural Lines

TopologyHydrography_Topology

Feature datasetHydrography

Polygon feature classHydroArea

Line feature classHydroLine

Point feature class

HydroPoint

Line feature classHydroShoreline

Feature layerHydrography Points

Feature layerShorelines

Feature layerHydrography Areas

Feature layerHydrography Lines

HydrographyHydrography points model springs and wells; lines model streams and shorelines; and areas model lakes and other water bodies.

Framework—geodatabase overvIew

The major data elements for creating and maintaining the topographic base map

are shown in this diagram. A key aspect of this data model is organizing the data for

cartography. Multiple map layers can use data from a single feature class, and a given

map layer can use data from more than one feature class or table. While the details of

these feature classes, tables, and map layers may vary among data providers, the broad

groupings are likely to be consistent.

These diagrams summarize the most important feature classes and tables used to implement the conceptual model shown previously. An important element of thecartographic data model is captured in the layer defini-tions (yellowboxes) shownhere. In the restof the casestudies, there was no attempt to capture specifications for cartographic representations as part of each data model. However, the map layers play an important role in most GIS applications.


8

Surface overlays

This dataset typically contains vegetation or land cover layers if vector features are used. A topology created with this feature class can be used to help construct a clean dataset without overlapping polygons. If raster data is used, colors can be used to symbolize the pixels.

BoundariesThis dataset contains administrative boundaries for government, military, and legal jurisdictions, together with their cartographic place names as annotation. A topology is created for the boundary feature classes to ensure coincidence and tessellation as appropriate.

HypsographyThe hypsography dataset contains spot elevation points, contour lines, and their annotation (elevation values). A topology is created for contours to ensure nonintersection. When contours are derived from a DEM, such a topology is not necessary.

TablesThe nonspatial tables shown

here are used to hold place names, revision tracking

information, and to support construction of valid feature

descriptions. VVTs are described later in

this chapter.

TransportationThe transportation dataset contains the road and

railway classes appropriate to 1:24,000 scale. Infrastructure contains airports, depots, customs

facilities, and other related features. A topology is shown for road, ramp, and highway classes only but

may be extended to include railroads.

ReferenceThis reference dataset contains an index to the USGS 1:24,000-scale topographic map quad sheets. Other grids may be included according to users’ needs.

CulturalCultural points model landmarks,

lines model specific boundaries, and areas model land use zones. A

topology is used to ensure coincidence of adjacent feature

boundaries. Annotation features are used to display the place

names for each type of feature.

Feature datasetReference

Polygon feature classUSGS24KQuadSheetIndex

ATTVALTable

ATTDESCTable

FCODETable

RevisionInfoTable

PlaceNameTable


Contour_VVTTable








Feature datasetSurface overlay















Group layer

Boundaries




Group layer








Roads



















Cultural Points








Point feature class

HydroPoint






HydrographyHydrography points model springs and wells; lines model streams and shorelines; and areas model lakes and other water bodies.


Transportation data is important for urban and regional plan-ning, disaster preparedness, service delivery, emergency 911 (E‑911)responseplanning,zoning,andgeneralmapreference.

Atopographicbasemaptypicallyshowsthecompleteroadand rail network based on centerline data. The type of each road or rail feature determines its symbology. This data model serves not only to distinguish the symbology of different road types but also to support a set of topological rules for ensuring the spatial integrity of the road network.

Because this chapter deals extensively with cartography, both feature classes and map layers are shown in relation to

transportatIon

The road network is one of the most important feature layers on a base map. In this data

model, transportation consists mainly of road centerline data and cartographic cues. At

a scale of 1:24,000, essentially every road and significant trail are included. Capturing

the type and vertical level of each road segment permits sophisticated and accurate

cartographic rendering of complex interchanges. Labeling can be simple and effective.

Topology can be used to help manage the integrity of the road network.

each other. It is the layers that determine the cartographic appearance of a map.

The logical data model for the transportation portion of the topographic base map data model includes:

• Schemadefinitions

• Classificationofroadandrailroadtypes

• Map layersused to representdifferent elevation levels,such as for complex overpasses

• Symbologyandlabelingofroadsandrailroadsforhigh‑quality cartographic rendering

• Useoftopologytoensuredataquality

In addition, you will find a number of practical tips for improving the cartographic quality of transportation features on a base map.

SChEMA of RoAd fEATURE ClASSES

The three feature classes on the next page are used to hold dozens of road types. The main distinction between MajorHwysandRoadsisthatMajorHwysareforrestrictedaccessroads,whichconnecttootherMajorHwysandRoadsvia Ramps.

NoticetheTypeandOverpassLevelfieldsineachoftheseclasses; they will be used to support multiple map layers for cartographic rendering.

The fourth feature class, TransJunctions, may be created as an artifact of the topological network for roads and railroads. These point features are useful for locating breaks in road features during routine editing and ensuring proper con-nectivitybetweenMajorHwys,Ramps,andRoads.

Group layer








Roads












8

Restricted access highways

Type of highway

Permanent unique identifier

Basis for a join to the RevisionInfo table

Road level for drawing order

Ramps

Type of ramp




Produced by the geometric networkand used to ensure only ramp featuresconnect to restricted access highways

Road and street features

Type of road or street (for symbology)

Class of road feature (for labeling)




Simple feature classMajorHwy Contains Z values

Contains M valuesGeometry Polyline

NoNo

Data typePrec-ision Scale Length

Allownulls

Object IDGeometry Yes

Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Short integer Yes 0

Double Yes 0 0

Defaultvalue

01

Field name

OBJECTIDShapeTYPE

TRANSIDSOURCE

OverpassLevelEnabled

Shape_Length

Domain

EnabledDomain

Simple feature classRamp Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Short integer Yes 0

Double Yes 0 0

Defaultvalue

900

01

Field name

OBJECTIDShapeTYPE

TRANSIDSOURCE


Shape_Length

Domain

EnabledDomain

Simple feature classRoad Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Short integer Yes 0

Double Yes 0 0

Defaultvalue

904

01

Field name

OBJECTIDShapeTYPE

CLASSTRANSIDSOURCE


Shape_Length

Domain

EnabledDomain

Simple feature classTransJunction Contains Z values

Contains M valuesGeometry Point

NoNo


Allownulls


Long integer Yes 0Short integer Yes 0

DefaultvalueField name

OBJECTID_1Shape

OBJECTIDEnabled

Domain


Roads can take on many classifications. This data model usesadomaintablethatidentifies74typesofU.S.roads,spread across five major categories. These categories have different names in most countries, but generally follow a similar pattern.

At the scale of 1:24,000 for which this data model isintended,cul‑de‑sacs(usuallyaroundedterminationonalocalstreet)arerepresentedbyapointfeatureclass,Trans-CartoPoints,withacorrespondinglayercalledCulDeSacshaving the symbol shown below.

AllotherstreetclassificationsareorganizedforcartographicpurposesinalinefeatureclasscalledRoadsCartoDissolve.This class contains all the features merged from the Roads, MajorHwys,andRampsfeatureclasses.Whiletheseparatefeature classes are important for data maintenance, such as totakeadvantageoftopologytools,theRoadsCartoDissolvefeature class is most useful and efficient for rendering and labeling the road network for a cartographic product.

The field VVT_ID is the attribute identifier that holdstheclassification foreachof the74 typesof roads in theRoadsCartoDissolvefeatureclass.Thisistheprimarykeyofarelatedtable,RoadsCartoDissolve_VVT,whichholdsa detailed definition of each road type. A more detaileddescriptionoftheVVTapproachisdiscussedneartheendof this chapter.

In addition to road classification, the vertical level of each road segment helps determine its symbology. In this data model, the attribute OverpassLevel is placed on eachtransportation class. Each road segment then takes on a positive or negative integer value corresponding to its rela-tive drawing order above or below other road levels. In this way, any number of overpass roads and underpass tunnels canbeaccuratelyrendered.WhencopyingthedatatotheRoadsCartoDissolve class, the OverpassLevel values areplacedintheLevel_field.

transportatIon—classIFyIng roads

The schema and layer definitions to support cartographic rendering of roads are pre-

sented here. This involves the creation of several additional feature classes whose data

is derived from the other transportation feature classes. Although these additional

feature classes may seem like overhead, this approach helps support high-quality road

symbols and enforce independence of road data from its cartographic representation,

which leads to more robust and adaptive databases and applications.

Group Layer Roads

Feature layer Cul De Sacs (symbols and values only)Source Transportation : TransCartoPoint

NoneSymbology method Simple

Definition query

Joins and relates NoneSymbol

Feature layer Roads (symbols and values only)Source Transportation : RoadsCartoDissolve

(Multiple definition queries)Symbology method

Definition querySimple

Joins and relates NoneSymbols Label

Major or primary highwayRampSecondary highwayMajor streetStreet


8

Point features that support high-quality cartography, such as cul-de-sacs

Type of feature, defined in a valid value table

Display angle

Lines that are dissolved from the roads, ramps, and major highways based on VVT_ID and Name attributes to support rapid map rendering and labeling

Name of point feature

Drawing level of point feature

Label string

Feature type key

Simple feature classRoadsCartoDissolve Contains Z values


NoNo

Length

255

128

Field name

OBJECTIDShape

Min_NAMESTRLevel_

LabelStrVVT_ID

Shape_Length

Defaultvalue Domain

RoadLevel

Roads

Simple feature classTransCartoPoint Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0

Field name

OBJECTIDSHAPEVVTIDAngle

DomainDefaultvalue

TableTransCartoPoint_VVT


Allownulls

Object IDLong integer Yes 0 0Long integer Yes 0

String Yes 254String Yes 254

Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Data type

Object IDGeometry

StringLong integer

StringLong integer

Double

Allownulls

YesYesYesYesYesYes

Prec-ision

0

00

00

Scale

Coded value domainRoadLevel

DescriptionField type

Split policyMerge policy

Overpass levelLong integerDefault valueDefault value

Code

0

-2

-1

1

2

3

4

5

6

Description

Ground Level

Tunnel 2 Levels Down

Tunnel 1 Level Down

Overpass 1 Level Up

Overpass 2 Levels Up





Coded value domainCoded value domainRoads

Field typeSplit policy

Merge policy

DoubleDefault valueDefault value

Code0123456789

10111213141516171819202122

232425262728293031323334353637

Code

3839404142434445464748

4950515253545556575859606162636465666768697071727374

Description

Street, Off Interstate Business RouteStreet, Off Interstate Business RouteTrail, JeepTrail, MotocrossTrail, BicycleTrail, HikingTrail, FootpathSecondary Highway, US RouteSecondary Highway, Off State Business RouteSecondary Highway, US Route AlternateSecondary Highway, US Route Spur

Secondary Highway, State RouteSecondary Highway, State Route AlternateSecondary Highway, State Route LoopSecondary Highway, State Route SpurSecondary Highway, Off Interstate Business Route

Secondary Highway, Off US Business RouteMajor Street, US RouteMajor Street, Off State Business RouteMajor Street, Off Farm or Ranch Business RouteMajor Street, Farm to MarketMajor Street, Ranch to MarketMajor Street, Ranch RoadMajor Street, Farm to Market SpurMajor Street, Ranch to Market SpurMajor Street, Ranch Road SpurMajor Street, US Route AlternateMajor Street, Principal ArterialMajor Street, County Road (CR Networks)Major Street, City Street (City Networks)Major Street, US Route SpurMajor Street, State RouteMajor Street, State Route AlternateMajor Street, State Route LoopMajor Street, State Route SpurMajor Street, Off Interstate Business RouteMajor Street, Off US Business Route

CodeStreet, Ranch to Market SpurStreet, Ranch Road SpurStreet, US Route AlternateStreet, Recreational Road SpurStreet, Principal ArterialStreet, County Road (CR Networks)Street, City Street (City Networks)Street, FrontageStreet, ServiceStreet, AccessStreet, US Route SpurStreet, State RouteStreet, State Route AlternateStreet, State Route LoopStreet, State Route Spur

Description

DescriptionRestricted Access Highway, InterstateRestricted Access Highway, US RouteRestricted Access Highway, Off State Business RouteRestricted Access Highway, US Route AlternateRestricted Access Highway, US Route SpurRestricted Access Highway, State RouteRestricted Access Highway, State Route AlternateRestricted Access Highway, State Route LoopRestricted Access Highway, State Route SpurRestricted Access Highway, Off Interstate Business Route

Restricted Access Highway, Off US Business RouteRampRamp, CollectorRamp, TurnaroundStreet, US RouteStreet, Off State Business RouteStreet, Off Farm or Ranch Business RouteStreet, Farm to MarketStreet, Ranch to MarketStreet, Ranch RoadStreet, Park RoadStreet, Recreational RoadStreet, Farm to Market Spur

TableRoadsCartoDissolve_VVT


Allownulls

Object IDLong integer Yes 0Long integer Yes 0


Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Valid values for theTransCartoPoints feature class

Unique ID within valid value domain

Feature type name

List of attribute names and associated values valid for this feature type

Description for this kind of feature


Two primary design methods are used in transportation layers: drawing cased roads based on linear geometry and representing road structures, such as overpasses, complex highway interchanges, and bridges.

In the map on the right, you’ll notice that highways are drawn in red with a thin black road casing around them, and city streets are white with a thin black road casing. This effect is achieved by drawing each road twice—initially with a black road casing that is slightly thicker than the red or white interior line used to “fill” the interior space.

You’ll also notice that this map accurately depicts how roads are stacked on one another at their crossings. Roads that pass over others are drawn on top. The strategy is to add attributes that describe the road level, which can be used to specify the drawing order that represents the road structures. This can be useful for urban mapping applications.

transportatIon—stackIng road elements

It is possible to accurately represent highway overpasses, interchanges, bridges, and so

forth, using a combination of road types and levels. These, in turn, are used to control

the drawing order of all road segments from bottom (typically ground-level roads) to

top (overpasses). This is an example of a complex layer definition used to model and

represent road network connectivity.

Group layerRoads

Streets Level3 Fill Streets Level2 Fill Streets Level1 Fill Streets Ground Fill

Major Streets Level3 Fill Major Streets Level2 Fill Major Streets Level1 Fill Major Streets Ground Fill

Cul De Sac Level3 Fill Cul De Sac Level2 Fill Cul De Sac Level1 Fill Cul De Sac Ground Fill

Highway Level3 Fill Highway Level2 Fill Highway Level1 Fill Highway Ground Fill

Secondary Highway Level3 Fill Secondary Highway Level2 Fill Secondary Highway Level1 Fill Secondary Highway Ground Fill

Ramps Level3 Fill Ramps Level2 Fill Ramps Level1 Fill Ramps Ground Fill

Ramps Level3 Casing Ramps Level2 Casing Ramps Level1 Casing Ramps Ground Casing

Secondary Highway Level3 Casing Secondary Highway Level2 Casing Secondary Highway Level1 Casing Secondary Highway Ground Casing

Major Streets Level3 Casing Major Streets Level2 Casing Major Streets Level1 Casing Major Streets Ground Casing

Streets Level3 Casing Streets Level2 Casing Streets Level1 Casing Streets Ground Casing

Highway Level3 Casing Highway Level2 Casing Highway Level1 Casing Highway Ground Casing

Cul De Sac Level3 Casing Cul De Sac Level2 Casing Cul De Sac Level1 Casing Cul De Sac Ground Casing

Road casings and levels can be rendered using linear road features with simple linework and special cartographic attributes.


8

The order in which these layers are rendered on the map is essential to achieve the proper cartographic result. To draw an overpass correctly, the uppermost road features should be rendered after the lower road features. This requires classifi-cation of the initial centerline data, delineating and coding eachroadelementtohavethecorrectOverpassLevelfieldvalue. This should also be ground-truthed or photo-verified by knowledgeable local experts.

Once the data has been correctly delineated and coded for overpass levels and copied into the RoadsCartoDissolveclass, simple queries can be used to select the appropriate subsets of casing and fill elements in the desired order. For example, the query for a highway overpass is simply “road type 0 to 10 and level = 1,” where a road type of 0 to 10 refers to restricted access highways, and a level equal to 1 refers to the first level above ground level.

Finally, there is a priority ranking among the road types ateachverticallevel.Whereamajorroadcrossesaminorroad, the symbol for the major road takes precedence. For this reason, all the casing and fill layers are ordered as shown below.Withineachcolumnandacrossthecolumnsfromleftto right, the layers are shown in stack order. Thus ground fill layers are rendered on top of ground casing layers, level 1 layers are rendered after ground layers, and so on. Still, you may prefer to make some slight variation in this ordering to improve the appearance at a particular type of intersection with your own data.

Notice this approach requires no special programming to achieve the proper cartographic effect. The main effort involved is to edit the highway intersections in sufficient detail that standard queries can distinguish ramps, local streets, and highways at multiple levels. Once all the layers have been defined for your specific types of roadways, the map can be reused as a template simply by pointing the layers to a different database.

Note that a 1:24,000-scale map should have its reference scalesetto1:24,000(referencescaleisapropertyofthedataframeinArcMap).Sincethereferencescaleaffectsthesizeof map elements as you zoom in or out of the map, this is essential to set correctly, particularly if you are editing road levels or annotation.

Highway Level1 Fill

Ramps Level1 Fill

Highway Level1 Casing

Ramps Level1 Casing

Streets Ground Fill

Ramps Ground Fill

Ramps Ground Casing

Composite View

Streets Ground Casing


dynamic labeling

Inthisexample,autolabelingwithArcGISwasusedtodefineand render the correct highway shields or street names on corresponding road features. The figure at right shows the highway symbols, placement, and other parameters defining the “label classes” created for this purpose. For each major category of road used in the data, a representative symbol is chosen to complement the choice of line color and weight used for the line feature. In the case of local streets, the placement option is slightly different from that of highways, since street names are normally offset slightly above the roads they name.

TIP The default labeling approach typically places one label (suchasaU.S.highwayshield)onthemapforeachhighwayfeature, but often just one such label is not enough. To fix this, users may turn on labeling for both fill and casement layers, then move the second instance of the name down in layer priority so it draws after other important information is placed.Moreoftenthannot,thisresultsinthesecondlabelusing white space well away from the first label placement. This can be made to work independently of scale and inter-activelywithoutexternallabelingenginessuchasMaplex.

Annotation

Some users may wish to go beyond autolabeling to create annotation feature classes for greater flexibility in label placement. The one class shown in the schema overview, TransAnno,isaplaceholderforpotentiallymanyannota-tion classes.

Because of the need to handle multiple vertical levels of tunnels and overpasses, the actual set of annotation classes for this case study includes:

• RailroadOwnerAnno

• GroundInterstateAnno

• Overpass1InterstateAnno

• Overpass2InterstateAnno

• GroundUSRouteAnno

• Overpass1USRouteAnno

• Overpass2USRouteAnno

• GroundStateRouteAnno

• Overpass1StateRouteAnno

• Overpass2StateRouteAnno

• GroundCountyRoadAnno

• Overpass1CountyRoadAnno

• Overpass2CountyRoadAnno

• GroundStreetAnno

• Overpass1StreetAnno

• Overpass2StreetAnno

Other annotation classes may also be created, such as for Farm‑to‑Market (FM) routes, Ranch‑to‑Market (RM)routes,andRanchRoads(RR),allcommoninTexas.

Whileannotationpotentiallyrequiresmorepreparationtimethan dynamic labeling, it leads to much faster display. This is because the annotation is simply retrieved from the database and placed where intended, while labeling involves dynamic placement calculations every time the map is redrawn. The more text required in your map, the better annotation is likely to perform.

TIP TherearetwowaysofmakingtheseclassesinArcGIS.The simpler is to build up the label classes, then convert them to annotation classes. The other way is to create each annotation feature class independently and set its param-eters directly.

NotethatArcGIS9allowstheusertocreatesubtypesofannotation classes. Therefore, all of these annotations can be handledwithasingleannotationclass.Withthiscapability,it would make the most sense to have a single annotation class for each feature dataset.

transportatIon—labelIng roads

Different types of highways are distinguished by their iconic shields displaying the

highway number, while city streets are labeled with their names. These labels are either

centered on or parallel to the road feature. GIS software supports several approaches,

such as automatic labeling and the use of annotation feature classes.


8

Annotation feature classTransAnno Contains Z values

Contains M valuesGeometry

NoNo

Data typeField namePrec-ision Scale Length

Allownulls

OBJECTID Object IDSHAPE Geometry Yes

FeatureID Long integer Yes 0ZOrder Long integer Yes 0

AnnotationClassID Long integer Yes 0Element Blob Yes 0 0 0

SHAPE_Length Double Yes 0 0SHAPE_Area Double Yes 0 0

290

S1

Street Name

Label Class Name Interstate

Label Weight: HighFeature Weight: NoneRank: 18 of 22

Arial, Bold, 8.0 Pts

Remove duplicate labelsReturn overlapping labels: True

Buffer: 0

Text for Layer Roads (apply to sublayers as needed)

Define classes of labels, each with different properties

ExpressionPlacement On the line

Best placement along the lineLabels follow the curve of the line = FalseOrientation: Orient to the pageAngle: Horizontal

Weights and Rank

Method

[PlaceName.LABELSTR]SQL Query VVT_ID = 0

35

Label Class Name USRoute




Buffer: 0



Weights and Rank

[PlaceName.LABELSTR]

SQL Query VVT_ID = 1 OR VVT_ID = 3 OR VVT_ID = 14 ORVVT_ID = 45 OR VVT_ID = 55

Label Class Name StateRoute




Buffer: 0



Weights and Rank

[PlaceName.LABELSTR]SQL Query VVT_ID=5 OR VVT_ID=34 OR VVT_ID=49 OR VVT_ID=69

Label Class Name Street


Times New Roman, Normal, 6.0 Pts


Buffer: 0

ExpressionPlacement Above the line

Best placement along the lineLabels follow the curve of the line = FalseOrientation: Orient to the pageAngle: Along the line

Weights and Rank


SQL Query (VVT_ID >13 AND VVT_ID < 34) OR (VVT_ID > 34 AND VVT_ID < 45) OR(VVT_ID > 64 AND VVT_ID < 67)

290

E Anderson La

Ed Bluestein Blvd


Railroads

In this data model, there are three types of railroad features: railroads, sidings, and railroads in streets. These are divided into two layer groups so that railroad-in-road features can berenderedafter(ontopof)streetlayers,whiletheregularrailroad and siding features are typically rendered before (beneath)streetlayers.

The most appropriate labeling for railroads in the United States is to place the owner name along each feature, similar in style and placement to street names.

transportatIon—raIlroads and InFrastructure

Railroads are modeled with one feature class and two feature layers. This gives you the

flexibility to model a railroad network as well as meet cartographic requirements, such

as when railroads follow along streets. Topology rules are defined controlling the overlap

of roads and railroads. Infrastructure areas model large facilities, such as airports, at a

small scale.

Feature layer Transportation, Railroad in RoadSource Transportation : Railroad

NoneSymbology method

Symbology fields TYPE

Definition queryUnique values

Joins and relates None

Railroad in Road

Symbols Label

Feature layer Transportation, RailroadsSource Transportation : Railroad


Symbology fields TYPE



RailroadSiding

Symbols Label

Railroad lines

Type of railroad line

Basis of a join to the RevisionInfo table


Simple feature classRailroad Contains Z values


NoNo


Allownulls


Long integer Yes 0Double Yes 0 0

Long integer Yes 0

Double Yes 0 0

Field name

OBJECTIDShapeTYPE

SOURCETransID

Shape_Length

Defaultvalue

1601

Domain

String Yes 32OwnerName Name of railroad company

Text for Layer Transportation, Railroads

All features the same wayExpression

Method[PlaceName.LABELSTR]



Buffer: 0

Placement Above the lineBest placement along the lineLabels follow the curve of the line = FalseOrientation: Orient to the pageAngle: Along the line

Weights and Rank

Railroad NameTimes New Roman, Normal, 6.0 Pts


8

Infrastructure

Infrastructure areas are generally large transportation features such as airports or shipyards. Notice these are not outlined; this is to reduce clutter and confusion in the map.

TIP Asageneral rule to reduceclutter,noneof theareafeatures in this data model are outlined. The only time outlines are used for area features is when the outlines are linearfeaturesthemselves,suchascityboundaries(moreonthisintheAdministrativeBoundariestheme).

defining Topology

The goal of topology creation with these three feature classes is to ensure proper connectivity of the road network. The RoadsCartoDissolvefeatureclassinthisdatamodelwascre-ated to hold all streets, ramps, and highways in a single class, thus simplifying the processes of rendering and labeling for cartographic purposes. However, for data maintenance these three classes are kept distinct from each other to facilitate topological analysis.

The rules shown here are to enforce that any single road feature does not loop back on itself and that there are no internal junctionswithina single feature (mustbe singlepart).Besidesreducingerrorsinthedata,theserulesenablemore effective generalization of transportation networks (editingthedatatoproducesmaller‑scaleproducts).


Cluster tolerance 0.000247

Participating feature classes and ranks

Topology rules

Road

Road

Railroad

Railroad

Road

Origin feature class

Must not self-intersect

Must be single part

Must not self-overlap

Must not self-intersect


Topology rule

Railroad

Road

Feature class

1

1

Rank

Railroad Must be single part

One of the artifacts of the geometric network creation tools inArcGISisthegenerationofjunctionfeaturesattheinter-section of linear features in the topology.

TIP The junction features created by the topology are useful in the editing stages of delineating and coding highway ramps and overpasses. You can select these points and specific features by road type and location to help find classification errors(forexample,togetonlyramps).

Large area features that represent transportation infrastructure, such asairports or shipyards.

Type of feature

Class of feature


Agency responsible for a feature


Simple feature classInfrastructureArea Contains Z values

Contains M valuesGeometry Polygon

NoNo


Allownulls


Long integer Yes 0Long integer Yes 0

Double Yes 0 0Long integer Yes 0Long integer Yes 0 0

Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDShapeTYPE

CLASSSOURCE

JURISTransID

Shape_LengthShape_Area

Defaultvalue

8500

8012

Domain

Feature layer Infrastructure AreasSource Transportation : InfrastructureArea


Symbology fields None

Definition querySingle symbol

Joins and relates Join TransID to Names : FeatID

Structure

Symbols Label Label Weight: HighFeature Weight: NoneRank: 9 of 22


Return overlapping labels: TrueBuffer: 0

Text for Layer Infrastructure Areas

All features the same wayExpressionPlacement Remove duplicate labels

Weights and Rank


Area Name

Robert MuellerMunicipal Airport


Administrativejurisdictionboundariesareimportantin the support of road construction and maintenance, E-911 response planning, services distribution, urban planning, taxation, water and wastewater utilities, and general map production.

Administrativeboundariescanrepresentabroadsetofclasses. Texas separates administrative areas into two distinctthemes:districtboundaries(schooldistricts,voting precincts, legislative districts) and politicalboundaries (municipalities, counties, federal lands,andstateandlocalparks).Thisbasemapdatamodelillustrates the political boundaries theme but could easily be extended to include district boundaries as well.

This theme has some overlap with census data, since that theme includes many of the same kinds of bound-aryclasses.Censusdataisnormallyconsideredasepa-rate, distinct theme, partly because it is collected and distributedasacompletepackagebytheU.S.CensusBureau and partly because the locational accuracy of the census data does not always match the accuracy requirements for state and local data sources. However, the ability to link local and regional administrative units with their associated demographic statistics may justifytheefforttointegratethedata.Morediscussionof thecensusdatamodel is found inChapter3, ‘Censusunits and boundaries’.

Aswithsomeotherbasemapthemes,someadministrativeboundaries tend to change frequently, requiring continual updates from many state and local agencies. This leads to the need for greater integration among these agencies. Each state would benefit from propagating a common model for bound-ary feature classes to its county and municipal governments.

admInIstratIve boundarIes

Boundaries are used on base maps to distinguish between different kinds of zones,

such as cities, counties, state and local parks, and military and tribal reservations. This

theme corresponds to Political Boundaries in the Texas base map. This theme could

also tie in with census data, for example, to link administrative units with the extensive

demographic tables collected by the census.













Group layer

Boundaries





8


Cluster tolerance 0.000247


Topology rules

CountyBoundary

MilitaryResBoundary

Feature class

1

1

Rank

ParkBoundary

StateBoundary

1

1

MunicipalAreasCarto

LegalBoundary

Comparison feature class

LegalBoundary

MunicipalBoundary

CountyBoundary

ParkBoundary

StateBoundary


MilitaryResBoundary

Feature class Rank

MunicipalBoundary 1

LegalBoundary

MunicipalAreasCarto

1

1

Must be covered by boundary of




Topology rule


defining topology

Some administrative areas can be mosaicked to form a tessel-lated area covered completely by administrative areas, while others cannot. For areas that tessellate like this, topology can be used to improve map quality.

Notice that most of the administrative feature classes partici-pate in the same topology. These topology rules ensure that counties do not overlap other counties, states do not overlap other states, and linear features on boundaries are coincident with the boundaries of their respective area features.

TheMustnothave gaps rule can,optionally, beused incases where you are not sure if you have complete coverage of administrative features.


Park boundary lines

Object ID

Type of park


Permanent unique ID

Agency responsible for boundary

Indicates whether the boundary is disputed

Simple feature classParkBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1ShapeTYPE

SOURCECULTIDJURISD

DISPUTEDShape_Length

Defaultvalue Domain

AdminLegalBoundaries

AdminJurisdictionTrueFalse

Municipal boundary lines

Object ID

ID—Relic from shapefile <not needed>


Permanent unique ID



Simple feature classMunicipalBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1Shape

IDSOURCECULTIDJURISD


Defaultvalue Domain


Boundaries for military reservations

Object ID


Type of boundary


Permanent unique ID


Simple feature classMilitaryResBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD

Shape_Length

Defaultvalue Domain


AdminJurisdiction

County boundary lines

Object ID

Type of boundary

Basis for join to RevisionInfo table

Permanent unique ID


Length in common map units


Simple feature classCountyBoundary Contains Z values


NoNo


Allownulls



Double Yes 0 0Long integer Yes 0

String Yes 64Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD

SHAPE_LENGDISPUTED

NAMEShape_Length

Defaultvalue Domain

AdminBoundaries

AdminJurisdiction

TrueFalse

State boundary lineSimple feature classStateBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD


Defaultvalue Domain

AdminBoundaries


Coded value domainAdminBoundaries



Types of Admin BoundariesLong integerDefault valueDefault value

Description

State

County

Local or Regional

National

International Waters

Code

8020

8021

8022

8023

8024

Coded value domainAdminJurisdiction



Types of JurisdictionsLong integerDefault valueDefault value

Description

Unknown

County

Local

Private

Federal

State

Code

8012

8013

8014

8015

8010

8011

Coded value domainAdminLegalBoundaries



Types of Legal BoundariesLong integerDefault valueDefault value

Code

8040

8041

8042

8043

8044

8045

8046

8047

8048

8049

8050

8051

8052

8053

8054

8055

8056

8057

8060

8061

8058

8059

Description

National Park

National Forest

National Wildlife Area

National Wilderness Area

Indian Reservation

Military Reservation

Federal Prison

Misc. Federal Reservation

Non-National Forest System Lands

Forest Administration Area

Forest Service Ranger District

Misc. State Reservation

State Park

State Wildlife Area

State Forest

State Prison

Misc. County Reservation

Large Park, City, County, or Private

Small Park, City, County, or Private

Ahupuaa (Hawaii)

Hawaiian Homestead

Land owned by Forest Service but outsideof proclamation boundary

Name of county


The coded value domains below are used by some or all of the administrative feature classes.AdminBoundaries andAdminJurisdiction provide a range of political boundarytypes,whileAdminLegalBoundariesprovidesalistofparkand military reservation functions.

ThefieldCULTIDinthesefeatureclassesisthepermanentunique key used for relating each feature to records in the Names table.

admInIstratIve—lIne boundarIes

Boundaries may be captured as both line and polygon features. The linear boundary

feature classes are used primarily for cartographic purposes. Boundary lines are symbol-

ized based on their boundary type as presented in the administrative domains, such as

AdminBoundaries. Administrative polygons are used for both data maintenance and

cartography.


8

Park boundary lines

Object ID

Type of park


Permanent unique ID

Agency responsible for boundary


Simple feature classParkBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1ShapeTYPE

SOURCECULTIDJURISD


Defaultvalue Domain



Municipal boundary lines

Object ID



Permanent unique ID



Simple feature classMunicipalBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1Shape

IDSOURCECULTIDJURISD


Defaultvalue Domain


Boundaries for military reservations

Object ID


Type of boundary


Permanent unique ID


Simple feature classMilitaryResBoundary Contains Z values


NoNo


Allownulls



Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD

Shape_Length

Defaultvalue Domain


AdminJurisdiction

County boundary lines

Object ID

Type of boundary

Basis for join to RevisionInfo table

Permanent unique ID


Length in common map units


Simple feature classCountyBoundary Contains Z values


NoNo


Allownulls



Double Yes 0 0Long integer Yes 0

String Yes 64Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD

SHAPE_LENGDISPUTED

NAMEShape_Length

Defaultvalue Domain

AdminBoundaries

AdminJurisdiction

TrueFalse

State boundary lineSimple feature classStateBoundary Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0Long integer Yes 0

Double Yes 0 0

Field name

OBJECTID_1Shape

IDTYPE

SOURCECULTIDJURISD


Defaultvalue Domain

AdminBoundaries


Coded value domainAdminBoundaries



Types of Admin BoundariesLong integerDefault valueDefault value

Description

State

County

Local or Regional

National

International Waters

Code

8020

8021

8022

8023

8024

Coded value domainAdminJurisdiction



Types of JurisdictionsLong integerDefault valueDefault value

Description

Unknown

County

Local

Private

Federal

State

Code

8012

8013

8014

8015

8010

8011

Coded value domainAdminLegalBoundaries



Types of Legal BoundariesLong integerDefault valueDefault value

Code

8040

8041

8042

8043

8044

8045

8046

8047

8048

8049

8050

8051

8052

8053

8054

8055

8056

8057

8060

8061

8058

8059

Description

National Park

National Forest

National Wildlife Area

National Wilderness Area

Indian Reservation

Military Reservation

Federal Prison

Misc. Federal Reservation

Non-National Forest System Lands

Forest Administration Area

Forest Service Ranger District

Misc. State Reservation

State Park

State Wildlife Area

State Forest

State Prison

Misc. County Reservation

Large Park, City, County, or Private

Small Park, City, County, or Private

Ahupuaa (Hawaii)

Hawaiian Homestead

Land owned by Forest Service but outsideof proclamation boundary

Name of county



Feature layer Legal BoundariesSource Boundaries : LegalBoundary




Joins and relates Join AdminID to Names : FeatID

8040-43, 47-55, 57-58, 61 Park, Forest, or PreservePrison8056, 8046

8044 Indian ReservationMilitary8045

Symbols LabelValues

Feature layer Municipal Areas for LabelsSource Boundaries : MunicipalAreasCarto





None None

Symbols LabelValuesLabel Weight: HighFeature Weight: NoneRank: 6 of 22



Text for Layer Municipal Areas

All features the same wayExpressionPlacement One label per feature

Weights and Rank


City Name




Area Name

Text for Layer Legal Boundary Areas

All features the same wayExpressionPlacement Remove duplicate labels.

Weights and Rank


Municipal area features to supportplacing labels within the areas

Permanent unique ID

Simple feature classMunicipalAreasCarto Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDShape

CULTIDShape_Length

Shape_Area

Defaultvalue Domain

Polygons for regions that need tobe labeled with an interior label

Type of feature


Permanent unique ID



Simple feature classLegalBoundary Contains Z values


NoNo


Allownulls



Long integer Yes 0 0Long integer Yes 0Long integer Yes 0


Field name

OBJECTIDShapeTYPE

SOURCECULTIDJURISD

DisputedShape_Length

Shape_Area

Defaultvalue

8040

80120

Domain



Annotation feature classBoundaryAnno Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0Long integer Yes 0

BLOB Yes 0 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDSHAPE

FeatureIDZOrder

AnnotationClassIDElement

SHAPE_LengthSHAPE_Area

Austin

Boundary polygons are used for interior labeling, possibly with leader lines for small polygons. By judiciously using linear feature labels along boundaries and area feature labels in municipal area interiors, all map views can be well labeled.

TheLegalBoundaries feature class servesmuch the samepurpose as the MunicipalAreasCarto feature class but isintended for land use features other than municipalities. TheLegalBoundariesfeatureclassisdesignedfordynamicboundaries, for which revision tracking and dispute status maybeimportant(thisislesslikelyformunicipalbound-aries). These areas also tend to be less prominent thanmunicipal areas and, thus, use a smaller text label font size.

TIP Boundary polygons can be generated from linear fea-tureclasses inArcMapusingtheConstructFeaturetool.

admInIstratIve—area boundarIes

The polygon feature classes for boundaries are used in the map for cartographic label-

ing and to complement the linear boundary feature classes. Census data is a possible

source for cultural area features. While not intended for cartographic output, a link with

census data will enable you to include extensive summary demographic statistics with

your administrative area units.

Linearfeaturescanbemadefrompolygonfeaturesusingthe Planarize tool.

TIP Whenthemapincludesboundariesbetweenneighbor-ing districts, such as counties or states, place linear boundary feature labels for the neighboring regions directly across the boundary from each other.


8

Feature layer Legal BoundariesSource Boundaries : LegalBoundary





8040-43, 47-55, 57-58, 61 Park, Forest, or PreservePrison8056, 8046

8044 Indian ReservationMilitary8045

Symbols LabelValues

Feature layer Municipal Areas for LabelsSource Boundaries : MunicipalAreasCarto





None None

Symbols LabelValuesLabel Weight: HighFeature Weight: NoneRank: 6 of 22



Text for Layer Municipal Areas


Weights and Rank


City Name




Area Name

Text for Layer Legal Boundary Areas

All features the same wayExpressionPlacement Remove duplicate labels.

Weights and Rank


Municipal area features to supportplacing labels within the areas

Permanent unique ID

Simple feature classMunicipalAreasCarto Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDShape

CULTIDShape_Length

Shape_Area

Defaultvalue Domain

Polygons for regions that need tobe labeled with an interior label

Type of feature


Permanent unique ID



Simple feature classLegalBoundary Contains Z values


NoNo


Allownulls



Long integer Yes 0 0Long integer Yes 0Long integer Yes 0


Field name

OBJECTIDShapeTYPE

SOURCECULTIDJURISD

DisputedShape_Length

Shape_Area

Defaultvalue

8040

80120

Domain



Annotation feature classBoundaryAnno Contains Z values


NoNo


Allownulls



BLOB Yes 0 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDSHAPE

FeatureIDZOrder



Austin

TIP Make sure boundary tints are distinct and do notconflict with thematic tints of other map layers, such as cultural line tints.

The BoundaryAnno feature class is a placeholder for potentially many annotation feature classes. It is shown here as a reminder that you can convert any administrative class labels into annota-tion features for more flexible formatting and placement.


The cultural theme in this base map data model is intended to capture significant features used in topographic mapping products not already accounted for in other themes. Point features include schools, churches, towers, and landmarks. Linearfeaturesincludesignificantwalls,fences,andcom-municationsandpowerlines.Areafeaturesincludebuildingfootprintsandbuilt‑up(urban)areas,withdifferentcolorsused to distinguish educational, religious, health care, agri-cultural, and recreational land uses.

Culturalfeaturesareshownaspartofadatasetcontainingboth cultural and surface water (hydrographic) featureclasses. This is to take advantage of topology to prevent cultural areas, such as landmarks, from overlapping water bodies.

cultural Features

The cultural theme captures important landmarks, building footprints, communications

and power lines, and other significant cultural features not already in another theme.

Feature layer Cultural AreasSource Cultural : CulturalArea

LandMarkAreas.XPOLType <> 8510Symbology method

Symbology fields Type

Definition queryUnique values; match to style.

Joins and relates Join: CultID to Names : FeatIDSymbols LabelValues

Built-up or Other

Education

Healthcare

Agriculture

Religious

Recreation

8500

8501

8502

8504

8507

8509

Feature layer Structure PolygonsSource Cultural : CulturalArea

LandMarkAreas.XPOLType = 8510Symbology method

Symbology fields VVTID



0-16, 20-43, 115

Symbols Values

Structure

Label




Text for Layer Structure Polygons


Weights and Rank


Structure Name




Text for Layer Cultural Areas


Weights and Rank


Area Name


Permanent unique ID

Type of landmark area

Superclass for landmark areas

Simple feature classCulturalArea Contains Z values


NoNo


Allownulls

Geometry YesLong integer Yes 0




Field name

ShapeOBJECTID

SOURCECultIDVVTID

XPOLTypeShape_Length

Shape_Area

TableCulturalArea_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Valid values forCulturalArea feature class


Feature type name



University of Texas

OakwoodCemetery

ConcordiaCollege

MountCalvary

CemeteryTexasMemorialStadium



CulturalAreas

Feature class

2

Rank









Cultural Points





8

Feature layer Cultural AreasSource Cultural : CulturalArea

LandMarkAreas.XPOLType <> 8510Symbology method



Joins and relates Join: CultID to Names : FeatIDSymbols LabelValues

Built-up or Other

Education

Healthcare

Agriculture

Religious

Recreation

8500

8501

8502

8504

8507

8509

Feature layer Structure PolygonsSource Cultural : CulturalArea

LandMarkAreas.XPOLType = 8510Symbology method




0-16, 20-43, 115

Symbols Values

Structure

Label




Text for Layer Structure Polygons


Weights and Rank


Structure Name




Text for Layer Cultural Areas


Weights and Rank


Area Name


Permanent unique ID

Type of landmark area

Superclass for landmark areas

Simple feature classCulturalArea Contains Z values


NoNo


Allownulls





Field name

ShapeOBJECTID

SOURCECultIDVVTID

XPOLTypeShape_Length

Shape_Area

TableCulturalArea_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Valid values forCulturalArea feature class


Feature type name



University of Texas

OakwoodCemetery

ConcordiaCollege

MountCalvary

CemeteryTexasMemorialStadium



CulturalAreas

Feature class

2

Rank









Cultural Points




Aswiththetransportationtheme,culturalfeatureclassesuse valid value tables to define the set of detailed classifica-tions of feature types. In this data model, two key feature layersarebasedontheCulturalAreasfeatureclass,oneforstructure polygons, such as buildings, and the second layer for all other types of cultural areas. These are handled by separate layers because building structure labels might be drawn on top of another nearby cultural feature.

You may have noticed the Rank field in the lower right corner ofTextforLayerdefinitionsonthesepages.Thisrankrefersto the priority for the labeling only, not for feature rendering.

TIP Notice that Structure Polygons are dark gray but not black; it is important to make sure labels are always readable ontopof theirassociatedfeatures.Makesureallofyourlabels can float over the map and still be readable.


Cultural point features are generally rendered in black,while line features may have other colors. It is important, when choosing colors for these features, to ensure there is sufficient contrast and lack of color conflict between these features and other layers they may overlay.

TIP Points are rotated to match real-life orientation. In ArcGIS,usetheAdvancedRotationsymbologymethod.

cultural—poInts and lInes

Cultural points and lines are generally prominent structures, as shown in these layer

definitions.

Feature layer Cultural PointsSource Cultural : CulturalPoint




Joins and relates NoneSymbols LabelValues

Tower, TV25Tower, Communications29Tower, Microwave27Tower, Antenna26Tower, Radio24Tower23Building, School22Building, Religious21Building, General Case20Satellite Dish, Large19Pit, Unconsolidated Material16Cliff Dwelling14Historical Marker13Drill Hole12Tank6Mine or Mine Shaft1,5Quarry4Prospect3Mine Entrance or Adit0

Feature layer Cultural LinesSource Cultural : CulturalLine





Landmark, Fence0Landmark, Levee or Dike4Landmark, Powerline6Landmark, Seawall or Wall1, 2Landmark, Ski Lift9Landmark, Track7

Class Name Label by Name

Label Weight: HighFeature Weight: HighRank: 11 of 22


One label per featureReturn overlapping labels: True

Buffer: 0

Text for Layer Cultural Points

Define classes of features and label each class differently.

ExpressionPlacement Anywhere, above and right preferred

Weights and Rank

Method

[PlaceName.LABELSTRSQL Query [None]

Place Name

Class Name Label by Type




Buffer: 0


Weights and Rank

[VVT_ID]SQL Query [VVT_ID] = 6 OR [VVT_ID] = 23 OR [VVT_ID] = 24

Place Type


Permanent unique ID

Type of line

TableCulturalLine_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Simple feature classCulturalLine Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0

Double Yes 0 0

Field name

ShapeOBJECTID

SOURCECultIDVVTID

Shape_Length

Point landmarks

Rotation angle for symbol display


Permanent unique ID

Type of landmark

TableCulturalPoint_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Simple feature classCulturalPoint Contains Z values


NoNo


Allownulls


Short integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0

Field name

ShapeOBJECTID

ROTATION_ASOURCECultID

VVT_ID

Valid values forCulturalLine feature class


Feature type name

List of attributes and associated values valid for this feature type


Valid values forCulturalPoint feature class




Feature type name


8

Feature layer Cultural PointsSource Cultural : CulturalPoint





Tower, TV25Tower, Communications29Tower, Microwave27Tower, Antenna26Tower, Radio24Tower23Building, School22Building, Religious21Building, General Case20Satellite Dish, Large19Pit, Unconsolidated Material16Cliff Dwelling14Historical Marker13Drill Hole12Tank6Mine or Mine Shaft1,5Quarry4Prospect3Mine Entrance or Adit0

Feature layer Cultural LinesSource Cultural : CulturalLine





Landmark, Fence0Landmark, Levee or Dike4Landmark, Powerline6Landmark, Seawall or Wall1, 2Landmark, Ski Lift9Landmark, Track7





Buffer: 0

Text for Layer Cultural Points



Weights and Rank

Method

[PlaceName.LABELSTRSQL Query [None]

Place Name





Buffer: 0


Weights and Rank

[VVT_ID]SQL Query [VVT_ID] = 6 OR [VVT_ID] = 23 OR [VVT_ID] = 24

Place Type


Permanent unique ID

Type of line

TableCulturalLine_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Simple feature classCulturalLine Contains Z values


NoNo


Allownulls


Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0

Double Yes 0 0

Field name

ShapeOBJECTID

SOURCECultIDVVTID

Shape_Length

Point landmarks

Rotation angle for symbol display


Permanent unique ID

Type of landmark

TableCulturalPoint_VVT


Allownulls



Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Simple feature classCulturalPoint Contains Z values


NoNo


Allownulls


Short integer Yes 0Long integer Yes 0 0Long integer Yes 0 0Long integer Yes 0 0

Field name

ShapeOBJECTID

ROTATION_ASOURCECultID

VVT_ID

Valid values forCulturalLine feature class


Feature type name



Valid values forCulturalPoint feature class




Feature type name






Text for Layer Hydrography Lines



Best placements along the lineLabels follow the curve of the line = true

Weights and Rank

Method

[Names_.LABELSTR]SQL Query HydroLines.TYPE = 571





Expression

Weights and Rank

[HydroLines.Type]SQL Query HydroLines.TYPE <> 571

Stream or River Name

Line Type

Above the lineBest placements along the lineLabels follow the curve of the line = true

Placement

Feature layer Hydrography LinesSource Hydrography : HydroLine


Symbology fields Type, Class

Definition queryUnique values, Many fields

Joins and relates HydroID joined to Names : FeatIDSymbols LabelValues

Closure Line500, 0Stream or Channel, Perennial[550,552,571], 610Stream or Channel, Intermittent[550,552,571], 611Aqueduct[574,576], 610

Aqueduct, Tunnel[574,576], 612Flume575, 0Siphon577, 0Dam or Wier580, 0

Aqueduct, Elevated[574,576], 611

Feature layer Hydrography PointsSource Hydrography : HydroPoint





Gaging Station636, 637Geyser634Pumping Station638Spring630Water Intake/Recharge564Water Tank650Water Well, Flowing632Water Well, Non-Flowing631Windmill635

Lines along which water is conveyed

Type of hydro line

Class of water flow

Permanent unique ID

Basis for join to RevisionInfo

Simple feature classHydroLine Contains Z values


NoNo


Allownulls

Shape Geometry YesOBJECTID Object ID

TYPE Long integer Yes 0CLASS Long integer Yes 0

HYDROID Long integer Yes 0 0SOURCE Long integer Yes 0 0

Shape_Leng Double Yes 0 0Shape_Length Double Yes 0 0

Domain

HydroLinesHydroClass

Point hydrography features, such as wells, discharge, recharge,or monitoring stations.

Type of hydro point

Class of water flow

Permanent unique ID


Simple feature classHydroPoint Contains Z values


NoNo


Allownulls




Domain

HydroPointsHydroClass

Coded value domainHydroLines



Lines water flows inLong integerDefault valueDefault value

Code

550

551

552

571

572

574

575

576

577

578

580

Description

Channel, Undredged

Processing or Closure Line

Canal or Ditch

River or Stream

Braided Stream

Aqueduct or Pipeline

Flume

Penstock

Siphon

Channel, Dredged

Dam or Weir

Coded value domainHydroPoints



Types of hydro pointsLong integerDefault valueDefault value

Code

564

565

630

631

632

635

636

637

638

650

651

652

653

654

655

656

Description

Water Intake

Dam or Weir

Rock

Well, non-flowing

Well, Flowing

Well, Windmill

Gaging Station

Gaging Station, Tidal

Pumping Station

Water Tank

Cistern

Filtration Pond

Tailings Pond

Sewage Disposal Area

Aquaculture Pond

Duck Pond

Coded value domainHydroClassDescription


Merge policy

Types of flowLong integerDefault valueDefault value

Code

615

616

617

618

610

611

612

Description

Mineral or Hot

Salt

Fresh

Artesian

Perennial

Intermittent

Dry

Water Tank

Water Tank

User-defined length of feature





Point feature class

HydroPoint






Accurate, complete maps of surface water features areimportant for water resources, land use, and urban plan-ning; flood control; and agriculture. In some ways, this is one of the simpler themes in the base map: There are just a few feature classes, and each map layer corresponds to a separate feature class.

Hydrographic features include point sources, such as wells, springs, tanks, and windmills; linear objects, such as streams, canals, aqueducts, and dams; and areal objects, such as lakes, reservoirs, ponds, and marshes. Each of these may have a number of characteristics. This data model provides two descriptors for classification and cartographic purposes: the TYPE and CLASS fields. The TYPE field is for theprinciple function of the point, linear, or areal feature, whiletheCLASSfieldtakesonvaluesrelatedtothetypeof water or its flow.

HydrograpHy—poInts and lInes

Water features are important in topographic base maps. They can identify sources of

drinking water for hikers and resources for planning purposes as well as important

facilities, such as water treatment plants and sewage ponds. You can also incorporate

relevant portions of the Arc Hydro data model described in Chapter 2, ‘Streams and river

networks’, that is useful for a base map.


8





Text for Layer Hydrography Lines



Best placements along the lineLabels follow the curve of the line = true

Weights and Rank

Method

[Names_.LABELSTR]SQL Query HydroLines.TYPE = 571





Expression

Weights and Rank

[HydroLines.Type]SQL Query HydroLines.TYPE <> 571

Stream or River Name

Line Type

Above the lineBest placements along the lineLabels follow the curve of the line = true

Placement

Feature layer Hydrography LinesSource Hydrography : HydroLine





Closure Line500, 0Stream or Channel, Perennial[550,552,571], 610Stream or Channel, Intermittent[550,552,571], 611Aqueduct[574,576], 610

Aqueduct, Tunnel[574,576], 612Flume575, 0Siphon577, 0Dam or Wier580, 0

Aqueduct, Elevated[574,576], 611

Feature layer Hydrography PointsSource Hydrography : HydroPoint





Gaging Station636, 637Geyser634Pumping Station638Spring630Water Intake/Recharge564Water Tank650Water Well, Flowing632Water Well, Non-Flowing631Windmill635

Lines along which water is conveyed

Type of hydro line

Class of water flow

Permanent unique ID


Simple feature classHydroLine Contains Z values


NoNo


Allownulls





Domain

HydroLinesHydroClass

Point hydrography features, such as wells, discharge, recharge,or monitoring stations.

Type of hydro point

Class of water flow

Permanent unique ID


Simple feature classHydroPoint Contains Z values


NoNo


Allownulls




Domain

HydroPointsHydroClass

Coded value domainHydroLines



Lines water flows inLong integerDefault valueDefault value

Code

550

551

552

571

572

574

575

576

577

578

580

Description

Channel, Undredged

Processing or Closure Line

Canal or Ditch

River or Stream

Braided Stream

Aqueduct or Pipeline

Flume

Penstock

Siphon

Channel, Dredged

Dam or Weir

Coded value domainHydroPoints



Types of hydro pointsLong integerDefault valueDefault value

Code

564

565

630

631

632

635

636

637

638

650

651

652

653

654

655

656

Description

Water Intake

Dam or Weir

Rock

Well, non-flowing

Well, Flowing

Well, Windmill

Gaging Station

Gaging Station, Tidal

Pumping Station

Water Tank

Cistern

Filtration Pond

Tailings Pond

Sewage Disposal Area

Aquaculture Pond

Duck Pond

Coded value domainHydroClassDescription


Merge policy

Types of flowLong integerDefault valueDefault value

Code

615

616

617

618

610

611

612

Description

Mineral or Hot

Salt

Fresh

Artesian

Perennial

Intermittent

Dry

Water Tank

Water Tank






Point feature class

HydroPoint






Hydrography point features are given symbols represent-ing their primary function and class. The list shown for the Hydrography Points map layer on the previous page is sufficient for this case study; however, you may wish to shorten or extend this list to better suit your own environ-mental context.

Streams and rivers can be depicted both as linear and areal features. This is due to scale, such as to distinguish either the stream centerline or its channel. Streams, rivers, and lakes are either perennial, intermittent, or dry.

NoticeintheTextforLayerHydrographyLinesfigureontheright that two methods of displaying the label are shown. The first method is to show the actual name of the feature for the label;thisapproachisonlyusedforstreamsandrivers(Type=571).Theotherapproachistodisplaythefeaturetypeasits label; this is standard practice for aqueducts, dams, and other nonstream features.


Feature layer Hydrography AreasSource Hydrography : HydroArea





Alkali Flat

Reservoir

Reservoir, Covered

Glacier or Permanent Snowfield

Salt Flat

Inundation Area

Aquaculture Pond

500, 0

501, 0

502, 0

503, 0

504, 0

505, 0

506, 0

Industrial Water Impoundment

Area to be Submerged

Sewage Disposal Plant

Tailings Pond

Marsh, Wetland, or Swamp, Submerged

Marsh, Wetland, or Swamp

Marsh, Wetland, or Swamp, Wooded

507, 0

508, 0

509, 0

510, 0

511, 612

511, 0

511, 611

Mangrove

Cranberry Bog

Tidal Flat

Bay, Estuary, Gulf, or Ocean

Shoal

Soda Evaporator

512, 0

513, 0

514, 0

515, 0

516, 0

517, 0

Duck Pond

Filtration Pond

Foul Area

River or Stream

Lake or Pond, Perennial

Lake or Pond, Intermittent

Lake or Pond, Dry

518, 0

526, 0

527, 0

571, 610

580, 610

580, 611

580, 612

Lake or Pond, Salt

Spoil, Dredged, or Dump Area

580, 616

583, 0

Class Name Label by NameWater Body Name




Text for Layer Hydrography Areas


ExpressionPlacement One label per features

Weights and Rank

Method


SQL Query HydroAreas.TYPE = 571 OR HydroAreas.TYPE = 580 OR HydroAreas.TYPE = 515

Class Name Label by TypeWater Body Type




ExpressionPlacement One label per feature

Weights and Rank

[HydroAreas.Type]

SQL Query HydroAreas.TYPE <> 571 OR HydroAreas.TYPE <> 580 OR HydroAreas.TYPE <> 515

Feature layer ShorelinesSource Hydrography : Shoreline





540 Natural shorelineMan-made shoreline541

Symbols LabelValues

Shorelines

Type of shoreline

Class of shoreline

Permanent unique ID

Shore material


Simple feature classHydroShoreline Contains Z values


NoNo


Allownulls



HYDROID Long integer Yes 0 0SHOREMAT Long integer Yes 0

SOURCE Long integer Yes 0 0Shape_Leng Double Yes 0 0

Shape_Length Double Yes 0 0

Domain

HydroShoreHydroShoreClass

Area water features

Type of feature

Class of flow

Permanent unique ID


Simple feature classHydroArea Contains Z values


NoNo


Allownulls





Shape_Area Double Yes 0 0

Domain

HydroAreasHydroClass

Coded value domainHydroShore



Types of shorelinesLong integerDefault valueDefault value

Code

540

541

543

546

542

Description

Natural

Man-made

Indefinite

Apparent

Closure Line

Coded value domainHydroShoreClassDescription


Merge policy

Types of shore materialsLong integerDefault valueDefault value

Code

621

622

623

624

625

626

627

628

629

Description

Boulders

Sand

Gravel

Mud

Shell

Coral

Rock

Concrete

Cliff

Coded value domainHydroAreas


Merge policy

Long integerDefault valueDefault value

Description

Alkali Flat

Reservoir

Reservoir, Covered


Salt Evaporator

Inundation Area

Aquaculture Pond



Sewage Disposal Pond

Tailings Pond

Marsh, Wetland, Swamp, or Bog

Mangrove Area

Cranberry Bog

Tidal Flat

Bay, Estuary, Gulf, Sea, or Ocean

Shoal

Soda Evaporator

Duck Pond

Cable Area

Pipeline Area

Cable and Pipeline Area

Pipeline Obstruction Area

Gut

Dry Dock Area

Filtration Pond

Foul Area

Mine Danger Area

Stream or River

Lake or Pond

Reef

Sand in Open Water


Description

514

515

516

517

518

520

521

522

523

524

525

526

527

528

571

580

581

582

583

Code

Code

500

501

502

503

504

505

506

507

508

509

510

511

512

513



Shorelines are another type of hydrography line. These are managed as a separate feature class because it is often important to know their material composition for boat navigation, recreation, or other purposes. Shoreline features are also used to model coastlines of water bodies that border a map’s area of interest.

Hydrography areas have the widest variability among the hydro features in this data model, as evident in the legend ofsymbolsforHydroAreasonthenextpage.Amongthesesymbols, you will see some that represent a combination of HydroAreasTYPE and CLASS, such as the entry abouthalfwaydown,“511,612Marsh,Wetland,orSwamp,Sub-merged”. The 511 refers to the marsh or wetland, while 612 isfromtheHydroClasseslistonthepreviouspage,meaning

HydrograpHy—sHorelInes and areas

Shorelines complete the discussion of hydrography lines. This section also covers

hydrography areas, which have a rich classification and symbology scheme. As with

the other hydrography features, hydrography areas are classified in terms of major and

minor codes (TYPE and CLASS fields), which allow many kinds of hydrography areas to

be represented in a simple, extensible way in the GIS database.

“dry.”FartherdownthelistareseveralentriesforLakeorPond,eachwithadifferentHydroClassvalue.

AswithHydroLines,thetextlabelsforHydroAreasmaybeeitherthenameofthefeature(forrivers,lakes,orlargeseas)or the feature type name.

TIP Whenchoosingcolors forhydrography featuresandtext, be sure that area fills are lighter in color tint than boundary features, and that text is darker than either the fill or the boundary.


8

Feature layer Hydrography AreasSource Hydrography : HydroArea





Alkali Flat

Reservoir

Reservoir, Covered


Salt Flat

Inundation Area

Aquaculture Pond

500, 0

501, 0

502, 0

503, 0

504, 0

505, 0

506, 0



Sewage Disposal Plant

Tailings Pond

Marsh, Wetland, or Swamp, Submerged

Marsh, Wetland, or Swamp

Marsh, Wetland, or Swamp, Wooded

507, 0

508, 0

509, 0

510, 0

511, 612

511, 0

511, 611

Mangrove

Cranberry Bog

Tidal Flat

Bay, Estuary, Gulf, or Ocean

Shoal

Soda Evaporator

512, 0

513, 0

514, 0

515, 0

516, 0

517, 0

Duck Pond

Filtration Pond

Foul Area

River or Stream

Lake or Pond, Perennial

Lake or Pond, Intermittent

Lake or Pond, Dry

518, 0

526, 0

527, 0

571, 610

580, 610

580, 611

580, 612

Lake or Pond, Salt


580, 616

583, 0

Class Name Label by NameWater Body Name




Text for Layer Hydrography Areas


ExpressionPlacement One label per features

Weights and Rank

Method


SQL Query HydroAreas.TYPE = 571 OR HydroAreas.TYPE = 580 OR HydroAreas.TYPE = 515

Class Name Label by TypeWater Body Type




ExpressionPlacement One label per feature

Weights and Rank

[HydroAreas.Type]

SQL Query HydroAreas.TYPE <> 571 OR HydroAreas.TYPE <> 580 OR HydroAreas.TYPE <> 515

Feature layer ShorelinesSource Hydrography : Shoreline





540 Natural shorelineMan-made shoreline541

Symbols LabelValues

Shorelines

Type of shoreline

Class of shoreline

Permanent unique ID

Shore material


Simple feature classHydroShoreline Contains Z values


NoNo


Allownulls



HYDROID Long integer Yes 0 0SHOREMAT Long integer Yes 0

SOURCE Long integer Yes 0 0Shape_Leng Double Yes 0 0

Shape_Length Double Yes 0 0

Domain

HydroShoreHydroShoreClass

Area water features

Type of feature

Class of flow

Permanent unique ID


Simple feature classHydroArea Contains Z values


NoNo


Allownulls





Shape_Area Double Yes 0 0

Domain

HydroAreasHydroClass

Coded value domainHydroShore



Types of shorelinesLong integerDefault valueDefault value

Code

540

541

543

546

542

Description

Natural

Man-made

Indefinite

Apparent

Closure Line

Coded value domainHydroShoreClassDescription


Merge policy

Types of shore materialsLong integerDefault valueDefault value

Code

621

622

623

624

625

626

627

628

629

Description

Boulders

Sand

Gravel

Mud

Shell

Coral

Rock

Concrete

Cliff

Coded value domainHydroAreas


Merge policy

Long integerDefault valueDefault value

Description

Alkali Flat

Reservoir

Reservoir, Covered


Salt Evaporator

Inundation Area

Aquaculture Pond



Sewage Disposal Pond

Tailings Pond

Marsh, Wetland, Swamp, or Bog

Mangrove Area

Cranberry Bog

Tidal Flat

Bay, Estuary, Gulf, Sea, or Ocean

Shoal

Soda Evaporator

Duck Pond

Cable Area

Pipeline Area

Cable and Pipeline Area

Pipeline Obstruction Area

Gut

Dry Dock Area

Filtration Pond

Foul Area

Mine Danger Area

Stream or River

Lake or Pond

Reef

Sand in Open Water


Description

514

515

516

517

518

520

521

522

523

524

525

526

527

528

571

580

581

582

583

Code

Code

500

501

502

503

504

505

506

507

508

509

510

511

512

513




Elevation points are usually benchmarks for ground control referenceorelevationsofsignificantfeatures.Whatconsti-tutes a significant feature can vary with the surrounding terrain. For example, a hill that rises 200 feet above a valley may be significant in a relatively flat region but completely unnoticeable in a mountainous region.

Contours are lines of constant elevation. These may bederivedfromDEMsorfromstereophotogrammetry.Topol-ogy is used to verify that contour lines do not self-intersect or cross other contours.

HypsograpHy—elevatIons

Vector topographic data includes elevation points and contour lines, which have many

applications, including hydrographic modeling, flood hazard mapping, slope analysis,

transportation planning, and recreation.

Elevation points

Elevation point features can be based on numerous types of data, as shown in the feature layer definition diagram and the domain table on the next page. The symbols can have threetextualelements:theterm“BM”forbenchmarks,theelevation numeric value, and the units of measurement. In ArcGIS,theseelementscanbecombinedtoformacharactermarker symbol that allows flexible construction and font size of the numeric value, units, and benchmark code. The text content of a character marker symbol scales as you zoom in or out of the map.

TIP Alwaysincludeunitsofmeasurementinelevationpointsymbols; while it may be obvious to the cartographer that the elevations are in feet or meters, it is almost certain that the values will be less obvious to some readers.



Topology rules1

Rank

Contour

Feature class

Contour


Must not intersect

Topology rule

Contour Must not self-intersect


Contour_VVTTable











8


Arial, Normal, 6.0 Pts


Buffer: 0

Text for Layer Surface Elevation Points

All features the same wayExpressionPlacement Anywhere; above and right preferred

Weights and Rank

Method[ELEVATION] & " " & [UNITS]

ELEV units

Feature layer Surface Elevation PointsSource Hypsography : ElevationPoint





Boundary Monument, Tablet

Horizontal Control Station, Better than 3rd Order, Checked Spot Elevation

Horizontal Control Station, Better than 3rd Order, Vertical Angle Benchmark

Horizontal Control Station, Less than 3rd Order

Horizontal and Vertical Control Station, Better then 3rd OrderHorizontal and Vertical Control Station, Less than 3rd Order

Spot Elevation, Less than 3rd Order

Vertical Control Station, No Tablet

Vertical Control Station, Tablet

13

4

5

2,3

11

10

0,1

6,7

8,9

Boundary Monument, No Tablet12

Coded value domainElevationPoints



Types of Elevation Points (VVT)DoubleDefault valueDefault value

Description

Spot Elevation, Ground Level, Less than 3rd Order

Spot Elevation, On Bridge, Less than 3rd Order

Horizontal Control Station, Less than 3rd Order, Checked Spot Elevation

Horizontal Control Station, Less than 3rd Order, Vertical Angle Benchmark

Horizontal Control Station, Better than 3rd Order, Checked Spot Elevation

Horizontal Control Station, Better than 3rd Order, Vertical Angle Benchmark

Vertical Control Station, No Tablet, Recoverable

Vertical Control Station, No Tablet, Permanent

Vertical Control Station, Tablet, Recoverable

Vertical Control Station, Tablet, Permanent

Horizontal and Vertical Control Station, Less than 3rd Order

Horizontal and Vertical Control Station, Better than 3rd Order

Boundary Monument, No Tablet

Boundary Monument, Tablet

Code

0

1

2

3

4

5

6

7

8

9

10

11

12

13

Elevation of point

Units of measurement


Permanent unique ID

Type of elevation point

TableElevationPoint_VVT


Allownulls

Object IDLong integer Yes 0Long integer Yes 0


Field name

OBJECTIDVVTIDFCODE

ACODESDESCRIPTIO

Simple feature classElevationPoint Contains Z values


NoNo


Allownulls


Double Yes 0 0String Yes 4

Long integer Yes 0 0Long integer Yes 0Long integer Yes 0 0

Defaultvalue

0

Field name

OBJECTIDShape

ELEVATIONUNITS

SOURCESURFIDVVTID

Domain

ElevationPoints

Valid values forElevationPoint feature class


Feature type name



152.7 m

166.12 m

162.76 m


Feature layer Surface Contours 20' IntervalSource Hypsography : Contours

[Index20] = 1Symbology method

Symbology fields VVTID, LabelYN

Definition queryUnique values; many fields


Intermediate0, 0Intermediate, Depression, Carrying1, 0Intermediate, Depression2, 0Intermediate, Carrying3, 0Index4, 0Index, Depression, Carrying5, 0Index, Depression6, 0Index, Carrying7, 0Supplemental8, 0Supplemental, Depression, Carrying9, 0Supplemental, Depression10, 0Supplemental, Carrying11, 0Submerged12, 0Submerged, Depression, Carrying13, 0

Submerged, Depression14, 0Submerged, Carrying15, 0Ice Surface16, 0Ice Surface, Depression, Carrying17, 0Ice Surface, Depression18, 0Ice Surface, Carrying19, 0

Elevation of contour line



Permanent unique ID

Whether a segment should be labeled

Whether a segment is a 20-foot interval

Type of contour line

Simple feature classContours Contains Z values


NoNo


Allownulls


Double Yes 0 0 Double Yes 0 0

String Yes 4Long integer Yes 0Short integer Yes 0Short integer Yes 0 Double Yes 0 0

Double Yes 0 0

Field name

OBJECTIDShape

ELEVATIONSOURCE

UNITSSurfID

LabelYNIndex20

VVTIDShape_Length

Defaultvalue

f

0

0

Domain

Units

EnabledDomain

Contours

TableContours_VVT


Allownulls

Object ID Double Yes 0Long integer Yes 0


Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Valid values for Contours feature class

Unique ID within domain

Feature type name

List of valid attributes and values


Class Name Default




Buffer: 0

Text for Layer Contour Lines 20' Interval


ExpressionPlacement Centered on line

Best location along lineFollow along the line = No

Weights and Rank

Method

[Elevation]SQL Query [LabelYN] = 1

ELEV

Coded value domainContours


Merge policy


Code

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

Description

Contour, Intermediate

Contour, Intermediate, Depression, Carrying

Contour, Intermediate, Depression

Contour, Intermediate, Carrying

Contour, Index

Contour, Index, Depression, Carrying

Contour, Index, Depression

Contour, Index, Carrying

Contour, Supplemental

Contour, Supplemental, Depression, Carrying

Contour, Supplemental, Depression

Contour, Supplemental, Carrying

Contour, Underwater

Contour, Underwater, Depression, Carrying

Contour, Underwater, Depression

Contour, Underwater, Carrying

Contour, Ice Surface

Contour, Ice Surface, Depression, Carrying

Contour, Ice Surface, Depression

Contour, Ice Surface, Carrying

Annotation feature classHypsoAnno Contains Z values


NoNo


Allownulls



Blob Yes 0 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDSHAPE

FeatureIDZOrder



Defaultvalue Domain

Contour labeling seems straightforward until you try todoit.Duetothewidevariabilityindensityandcurvatureof contour lines for a given terrain, it is difficult to write a general purpose algorithm for placing all contour labels in “good places.”

Since contour lines should be rendered beneath most other map layers, you may need to make some layers partially transparent to allow the contours to show through. In this example,contourswererenderedafter(ontopof)surfaceoverlays and administrative areas, and before (beneath)hydrography, transportation, and administrative line fea-tures. Elevation points are rendered last, to be on top of all other layers.

TIP For the best labeling results, annotation should be placedmanuallytomanageproperorientation(parallelandcenteredoncontourline)andtodistributelabelsforbestreadability(avoidlabelinginareasofdensecontours,andstaggerlabelswhenclosetogether).

TIP Here is an approach that works well for labeling a specific set of contours, although it involves a couple of intermediate geoprocessing tasks:

1. Create some graphic lines perpendicular to the contour lines, intersecting them where they would ideally be labeled.

2. Buffer those graphic lines, creating a new feature class. Experi-ment to get the best buffer distance that allows the complete elevation value to display without a lot of excess space.

3. Create another polygon feature class that has only one poly-gon surrounding the desired contour features.

4. Union the feature class created in step 3 with the buffers from step 2 as a geoprocessing operation.

5. Start editing the result of step 4: a. Select the big polygon with all the holes. b. Switch the selection. c. Delete the holes that are now selected. d. Stop editing and save your edits.

6. Intersect the contours with the buffers (in ArcGIS, this is done using the Geoprocessing wizard). This produces lines that will be the segments to be labeled.

7. Intersect the contours with the polygon feature from step 5 to produce a line feature class that has the segments that should be labeled.

8. In each of the feature classes resulting from steps 6 and 7, add a new field called LabelYN (short integer). Set the values in the feature class from step 6 to be 0 (zero), and from step 7 to be 1 (one).

9. Finally, merge the feature classes resulting from steps 6 and 7 to create the final output.

10. By setting a label query to display the labels only for con-tour features with LabelYN=1, the desired contours will be labeled.

HypsograpHy—contour lInes

For cartographic purposes, contour lines are divided into several groups, as shown in the

feature layer definition below. The choice of index elevations depends on the contour

interval, which, in turn, depends on both the map scale and the relative relief of the terrain.


8

Feature layer Surface Contours 20' IntervalSource Hypsography : Contours

[Index20] = 1Symbology method

Symbology fields VVTID, LabelYN

Definition queryUnique values; many fields


Intermediate0, 0Intermediate, Depression, Carrying1, 0Intermediate, Depression2, 0Intermediate, Carrying3, 0Index4, 0Index, Depression, Carrying5, 0Index, Depression6, 0Index, Carrying7, 0Supplemental8, 0Supplemental, Depression, Carrying9, 0Supplemental, Depression10, 0Supplemental, Carrying11, 0Submerged12, 0Submerged, Depression, Carrying13, 0

Submerged, Depression14, 0Submerged, Carrying15, 0Ice Surface16, 0Ice Surface, Depression, Carrying17, 0Ice Surface, Depression18, 0Ice Surface, Carrying19, 0

Elevation of contour line



Permanent unique ID

Whether a segment should be labeled

Whether a segment is a 20-foot interval

Type of contour line

Simple feature classContours Contains Z values


NoNo


Allownulls


Double Yes 0 0 Double Yes 0 0

String Yes 4Long integer Yes 0Short integer Yes 0Short integer Yes 0 Double Yes 0 0

Double Yes 0 0

Field name

OBJECTIDShape

ELEVATIONSOURCE

UNITSSurfID

LabelYNIndex20

VVTIDShape_Length

Defaultvalue

f

0

0

Domain

Units

EnabledDomain

Contours

TableContours_VVT


Allownulls

Object ID Double Yes 0Long integer Yes 0


Field name

OBJECTIDVVTID

FCODEACODES

DESCRIPTIO

Valid values for Contours feature class

Unique ID within domain

Feature type name

List of valid attributes and values


Class Name Default




Buffer: 0

Text for Layer Contour Lines 20' Interval


ExpressionPlacement Centered on line

Best location along lineFollow along the line = No

Weights and Rank

Method

[Elevation]SQL Query [LabelYN] = 1

ELEV

Coded value domainContours


Merge policy


Code

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

Description

Contour, Intermediate

Contour, Intermediate, Depression, Carrying

Contour, Intermediate, Depression

Contour, Intermediate, Carrying

Contour, Index

Contour, Index, Depression, Carrying

Contour, Index, Depression

Contour, Index, Carrying

Contour, Supplemental

Contour, Supplemental, Depression, Carrying

Contour, Supplemental, Depression

Contour, Supplemental, Carrying

Contour, Underwater

Contour, Underwater, Depression, Carrying

Contour, Underwater, Depression

Contour, Underwater, Carrying

Contour, Ice Surface

Contour, Ice Surface, Depression, Carrying

Contour, Ice Surface, Depression

Contour, Ice Surface, Carrying

Annotation feature classHypsoAnno Contains Z values


NoNo


Allownulls



Blob Yes 0 0 0Double Yes 0 0Double Yes 0 0

Field name

OBJECTIDSHAPE

FeatureIDZOrder



Defaultvalue Domain

HypsoAnno is a placeholder for potentially numerous annotation classes, each one corresponding to a contour label type. With ArcGIS, these are most conveniently generated from the label class definitions themselves.


Topographic relief can be one of the most distinctive aspects of a base map. This theme adds elevation detail to a map in both raster and vector forms.

The most essential form of topographic data is the digital elevation model. This consists of a grid of elevation points with uniform spacing. A wealth of analytical tools hasevolved to take advantage of this form of data, such as for delineating watersheds, flood modeling, slope determination and hillshading, communication tower placement, viewshed analysis,andutilitiesplanning.ManybasemapsuseaDEMwith30‑meterspacingbetweenelevationpoints,basedondata collected by the U.S. Geological Survey and other data providers. Plans include enhancing this data to 10-meter spacing interval.

There are three main methods of terrain depiction in maps. The first is just to show that local relief exists. This can be achievedusingahillshadedDEMoverlaywithatranspar-

HypsograpHy—raster

Hypsography, or topographic relief, can be expressed as raster data, such as DEMs, or

as vector data, such as elevation points and contour lines. DEMs are used as source data

for numerous derived products, such as hillshaded relief, watershed delineation, and

contour lines.

ency between 60 and 75 percent. The symbology of thehillshade should use a subtle color ramp, such as from yucca yellow to 40 percent gray, from the esri.style color palette.

The second method is to show relief and elevation with hyp-sometriccoloringusingtwogrids,aDEMandahillshade.OnewaytomakethisworkistorendertheDEMwithagradation of color well suited for your elevation ranges, then overlay with any polygon layers that are important with a transparencybetween30–45percent.Finally,overlaythehillshadewithatransparencyof35–55percent.

The third method to show terrain is a naturalistic depiction of relief and elevation. This is like the second way just men-tioned but with the addition of a vegetation or land cover grid that is classified by vegetation or land cover type, with each type rendered in the most natural color according to itsnature.ThislayercanbeoverlaidontheDEMwithatransparencyof40–75percent—you’llneedtoexperimentfor best results.


8

Digital elevation model of central Austin; yellows represent higher elevations, and greens represent lower.

The same DEM with the addition of hillshade and cultural layers; the hillshade

adds a sense of depth to the map.

R as ter Datas etDEM

G eometry R as te r Digital elevation model used for hypsometric tintingR esolution 30 me te r

R as ter Datas etHillshade

G eometry R as te r Hillshade derived from DEMR esolution 30 me te r


Image base refers to three types of remotely sensed data: aerial photography from which orthoimagery is derived; satellite imagery; and scanned maps.

oRThoIMAGERy

Aerialphotographyprovidesawealthofdatathatwouldbeprohibitively expensive to collect from ground level. This information is used as a general map background as well as for land cover change detection, property appraisals, environmental analysis, feature extraction to create other geographic themes, and many other purposes.

To be useful in a GIS, this image data is orthorectified. This involves first correcting distortions introduced by the photographic equipment and the airplane’s flight path, then imposing an earth-based coordinate system.

SATEllITE IMAGERy

Digitalimageryfromearth‑observingsatellitescanbecol-lected on a constant, ongoing basis and is useful in creating irrigated farmland maps, assessing urban growth patterns, and planning park management programs. For emergency response, postdisaster imagery may be useful in document-ing losses and future planning of mitigation efforts.

SCANNEd MAPS

The earliest forms of digital maps were scanned from paper orMylarmaps.Theseareoftenusefulforhistoricalcom-parison. Scanned maps may be found in various formats; forexample,theUSGSDRGformatwasusedforscannedtopographic quad sheets.

TIP To improve readability of vectors and text over imagery, trytoningdownrasterlayersbyreducingcontrast(‑22)andincreasing brightness (+26). This shows vector and textoverlays better, and the image prints with less ink.

Image base

Aerial photography and satellite imagery are widely used as backdrops for overlaid

features. They have also become a cost-effective means of collecting and updating vast

amounts of information on a regular basis. To georeference this data, including all the

other data sources present in a GIS, a network of ground survey control points is also

needed. Two main approaches to building this control network are to use ground-based

data collection and remotely sensed data collection.


8

Scanned maps can be useful for historical records and comparison.

DOQQ imagery is useful for proofing and updating the base map.


land cover

This theme is used for distinguishing broad categories of vegetation and surface material. The exact content of this theme may vary widely across regions, states, and countries. Such an overlay can be useful for wildlife management, flood control, drought management, nutrient and pesticide runoff modeling, city and county planning, and fire protection.

TheschemastructureforLandCoverisshownonthefol-lowing page. The Type field holds a value corresponding to the type of land cover.

In this data model, land cover polygons are not expected to overlap, so a topology is created to enforce this condition. However, it is conceivable that land cover areas could overlap, depending on the land cover types created and the nature of the land. In this case, a topology would not be needed.

surFace overlays and IntegratIve tHemes

Many other themes can be imagined and created in addition to those described so far.

The surface overlays theme provides a placeholder for any number of additional themes,

such as land cover, soils, and flood hazard zones. Other, more complicated themes are

good candidates for cross agency coordination, such as critical infrastructure, wetlands

delineation, census data, parcel index, place names, and addressing.

AddITIoNAl ovERlAyS

In addition to land cover, several other overlays are consid-ered useful enough to mention here, although they were not included in the example schema.

Soil survey

TheU.S.DepartmentofAgriculture’sNaturalResourcesConservationServicehascompiledcounty‑levelDigitalSoilSurveyGeographic(SSURGO)datasetsupdatedfromolder1:24,000 paper surveys. These are useful in land appraisal, site selection, agriculture, construction, transportation planning, and estimation of groundwater contamination susceptibility.

flood hazard

Flood hazard information is used in repetitive flood claims. TNRIS plans to compile a dataset of 100-year and 500-year floodplain boundaries. This would be used to support activi-ties related to construction and financing, transportation risk planning, disaster preparedness, and floodplain insurance.

Feature layer Surface CoverSource LandCover : LandCover





Scrub

Woods/Brushland

Sand

Scattered Trees

Lava

Gravel

251

250

255

254

257

258

Vegetative and nonvegetativenatural land cover

Type of land cover

Defines an M:1 relationship class to add source information from RevisionInfo table

Unique identifier

Simple feature classLandcover Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0


Field name

OBJECTIDShapeTYPE

SOURCESURFID


Defaultvalue

250

Domain

Landcover

Coded value domainLandcover



Type of land coverLong integerDefault valueDefault value

Description

Forest or Brushland

Scrub

Cropland

Vineyard

Scattered Trees

Sand

Orchard or Plantation

Lava

Gravel

Moraine

Code

250

251

252

253

254

255

256

257

258

259

TopologyLandCover_Topology


Topology rules1

Rank

LandCover

Feature class

LandCover


Must not overlap

Topology rule


8

Feature layer Surface CoverSource LandCover : LandCover





Scrub

Woods/Brushland

Sand

Scattered Trees

Lava

Gravel

251

250

255

254

257

258

Vegetative and nonvegetativenatural land cover

Type of land cover

Defines an M:1 relationship class to add source information from RevisionInfo table

Unique identifier

Simple feature classLandcover Contains Z values


NoNo


Allownulls


Long integer Yes 0Long integer Yes 0 0Long integer Yes 0 0


Field name

OBJECTIDShapeTYPE

SOURCESURFID


Defaultvalue

250

Domain

Landcover

Coded value domainLandcover



Type of land coverLong integerDefault valueDefault value

Description

Forest or Brushland

Scrub

Cropland

Vineyard

Scattered Trees

Sand

Orchard or Plantation

Lava

Gravel

Moraine

Code

250

251

252

253

254

255

256

257

258

259

TopologyLandCover_Topology


Topology rules1

Rank

LandCover

Feature class

LandCover


Must not overlap

Topology rule

Census boundaries and demographics

TheU.S.CensusBureaupublishesextensivelocationalanddemographic data on a regular basis. The locational data consists of built and natural features that form boundaries for census blocks, block groups, tracts, and jurisdictional boundaries. The demographic data is tabular in nature, but each record can be linked to a given census block, block group,tract,orjurisdictionalarea.Censusmapsandasso-ciated demographics are used by all levels of government, as well as private businesses, to plan and provide services.

Since this data is collected and published at the national level, it would be useful and cost-effective for each state and local government to create a single resource that can be shared among the agencies at that level. This data could then be overlaid on other base map themes according to the user’s immediate requirements.

INTEGRATIvE ThEMESCertain other themes that are useful overlays are morecomplicated than those mentioned above, requiring multia-gency coordination and integration. These include critical infrastructure, addressing, parcel index, and census data.

Critical infrastructure

In the United States and many other nations, it is increas-ingly important to distinguish “critical infrastructure” for purposes of emergency preparedness and management, including mitigation, planning, monitoring, response, and recovery.

This could include a wide range of facilities in the transpor-tation, energy, agriculture, telecommunications, chemical, defense, public health, and other sectors. Such a resource requires considerable integration of available data among multiple agencies. For security purposes, public access to portions of this data may be restricted.


Each base map will have some strategy for text and label placement on the map. Two key design tasks are to define the text label properties for each map layer and collate all the text for all map layers into an integrated labeling specification for the map. This includes setting text symbol properties (colors,fonts,pointsizes,andsoon),aswellasspecificationsforhowfeaturesarelabeled(forexample,whethernamesare splined along roads or whether administrative areas are labeledwithinthearea,alongadjacentboundaries,orboth),and how to deal with labeling priorities and conflicts.

Labelingcanbeassimpleasaddinganamefieldtoafeatureordefininglabelpropertiesforeachmaplayer.Manydatamodels manage place names as annotation feature classes. This often has difficult data maintenance issues for extents wherenamesundergoconsiderablechange.Moresophisti-cated designs can be implemented where the place names database(builttoholdofficialnames,alternatenames,andproposednames)isintegratedwiththeGIS.

The more sophisticated design was not used in this data model. However, if you have an interest in such a design, you can investigate some useful methods presented in the addressdatamodelinChapter4,‘Addressesandlocations’.This comprehensive address data model has design concepts similar to geographic place names. For example, the address

geograpHIc place names

A key design question you’ll encounter is how sophisticated your place names data

model needs to be. Geographic features have names, often several, that are used for

map labeling and other applications, such as maintaining a place name gazetteer. In

addition, many cartographic agencies have the responsibility of maintaining the official

place names registry for a jurisdiction. With increasing frequency, many place names

databases need to hold geographic locations for place names—either a geographic

feature or something as simple as a latitude–longitude coordinate.

data model includes a comprehensive names table and illus-trates how names can be associated with multiple feature classes in the geodatabase. It also demonstrates how each feature could be associated with many possible addresses (including its name) and how a name could potentiallybelong to many features.

More work in this area is needed, but early results lookpromising. Here is a design for a names database that is independent of the GIS.

National GNIS

The larger the organization, the greater the need for a consistent, up-to-date, shared resource of place names. In response to this need, and to consolidate the numerous place names databases currently in use, the USGS and the U.S. Board on Geographic Names have embarked on a long-term program called the Geographic Names Information System, a national database of geographic place names.

GNIS Phase 1, a compilation of names appearing on USGS 1:24,000 topographic maps, has been completed for all 50 states. Phase 2, now in progress, consists of virtually all other known place names, particularly names from other federal maps, names that are historical but no longer used, and those with variant spellings. GNIS now contains infor-

TablePlaceName


Allownulls

Geographic place names

Object ID

Long integer Ye s 0 0 Foreign key to ObjectID of associated feature

String Ye s 254 Place name in all uppercase for use in searching

String Ye s 254 Place name in upper/lowercase for map display

Long integer Ye s 0 Status of place name in GNIS

Long integer Ye s 0 Foreign key to list of revision verification methods

Date Ye s 0 0 8 Date revision was verified

Defaultvalue

0

902

Field name

OBJECTID

FEAT_ID

NAMESTR

LABELSTR

GNISSTATUS

VERIMETHOD

VERIDATE


8

allows for testing consistency between GIS layers that may be integrated from multiple agencies.

mation on approximately 2 million physical and cultural geographic features in the United States.

The information for any geographic name in the GNIS Websiteincludes:

• Federallyrecognizedfeature name

• Feature type

• Elevation(whereavailable)

• Estimated 1994 population of incorporated cities and towns

• States and counties in which the feature is located

• Latitude and longitude of the feature location

• ListofUSGS7.5‑minutex7.5‑minutetopographicmaps on which the feature is shown and names other than the federally recognized name by which the feature may be or have been known

• Linkstositesofferingmap viewers for graphical display of the feature

• Linkstositesofferinginformationaboutthewatershed area in which the feature is located

TheWebsitealsoallowsuserstodownloadasetofaddi-tional gazetteer data to further extend the usefulness of the GNIS data.

Thisisapromisingstep,butmoreworkisneeded.Manypublic federal spatial data sources do not contain names or links to names. The sample data in this model has names from state and local sources, as well as manual data entry for hydrographic areas.

PlaceName table

The NAMESTR field values are in all uppercase letters,makingiteasiertomatchnamesinqueries.TheLABELSTRfield values are in mixed, upper- and lowercase letters, to be usedtoproducelabelsorannotation.VERIMETHODandVERIDATEarefieldsusedinverifyingthecorrectnessofthenamesdata.TheGNISSTATUSfieldreferstotheinclusionof each record in the national GNIS.

Chapter 4, ‘Addresses and locations’, contains anotherexample of a names table, in this case, to support names for addressing of streets, parcels, buildings, and other points of interest. Users are encouraged to anticipate as many uses for the names data as possible when deciding on the most appropriateschemafortheirownorganizations.Also,keepin mind that managing names in a normalized names table



There might be private inholdings within the boundariesof the national or state reservations shown on the map.


TN

MN

5º 21’



1 2 3

4

7

5

6 8

1 0 10.5

Miles

1,000 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Feet

0 1 20.5

Kilometers

SCALE: 1:24,000



THIS MAP COMPLIES WITH NATIONAL MAP ACCURACY STANDARDSFOR SALE BY TEXAS NATURAL RESOURCES INFORMATION SYSTEM, PO BOX 13231, AUSTIN, TX 78711-3231

A FOLDER DESCRIBING TOPOGRAPHIC MAPS AND SYMBOLS IS AVAILABLE ON REQUEST.

Latitude-longitude graticule with lat-lon tics (stock components)

Projection information (stock component) North arrow with

magnetic declination indicator (hand assembled)

Quadrangle locator (hand assembled)

Graphical scalebars (stock components)

Datum text (stock)

Contour interval text (stock)

Scale shown as a representative fraction, called a scale text element in ArcMap (stock component)


Street or Road...................


BM


Interstate.....................

US Route.....................


Scrub.............................



Education......................

Healthcare......................

Religious........................

Recreation......................

Park...............................



Fence Line....................

Levee or Dike...............

Railroad.............................

Radio Tower.................



Major Street......................

Ramp.................................


Military..........................


Other Tank....................

S1

Page layout for maps is not yet captured as part of the geodatabase. This section provides tips for cartographic elements and their placement on the map page. It is time to summarize the choices made and steps taken to create the topographic map discussed early in this chapter.

Elements of a map specification

The specification for the finished map in this case study contains several elements:

• Title,logo,contactinformation,andversiondate

• Mapwindow,latitude–longitudereferencegraticulewithtic marks and labels

• Geodeticdatumandprojectionparameterdescriptions

• Northarrow,magneticdeclination,andquadrangleloca-tor

• Scaletextandbars,contourinterval,andlegend

Of these, the magnetic declination indicator, quadrangle locator, and legend were assembled manually, and they can also be automated with programming. The rest were created usingtheArcMapdefaultstyleandpropertysheets(refertoBasemap.style,includedwiththecasestudydatabase).

page layout desIgn

The design of a map and its surrounding map elements helps determine the effectiveness

and elegance of a cartographic product. Most of the elements in the map specification

used for this case study are easily assembled using out-of-the-box ArcMap capabilities,

while three of the elements are manually constructed. Templates created to implement

a map specification further simplify the task of generating the final output.


8


There might be private inholdings within the boundariesof the national or state reservations shown on the map.


TN

MN

5º 21’



1 2 3

4

7

5

6 8

1 0 10.5

Miles

1,000 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Feet

0 1 20.5

Kilometers

SCALE: 1:24,000



THIS MAP COMPLIES WITH NATIONAL MAP ACCURACY STANDARDSFOR SALE BY TEXAS NATURAL RESOURCES INFORMATION SYSTEM, PO BOX 13231, AUSTIN, TX 78711-3231

A FOLDER DESCRIBING TOPOGRAPHIC MAPS AND SYMBOLS IS AVAILABLE ON REQUEST.

Latitude-longitude graticule with lat-lon tics (stock components)

Projection information (stock component) North arrow with

magnetic declination indicator (hand assembled)

Quadrangle locator (hand assembled)

Graphical scalebars (stock components)

Datum text (stock)

Contour interval text (stock)

Scale shown as a representative fraction, called a scale text element in ArcMap (stock component)


Street or Road...................


BM


Interstate.....................

US Route.....................


Scrub.............................



Education......................

Healthcare......................

Religious........................

Recreation......................

Park...............................



Fence Line....................

Levee or Dike...............

Railroad.............................

Radio Tower.................



Major Street......................

Ramp.................................


Military..........................


Other Tank....................

S1

The legend and other manually created components can be reused on any number of maps. Thus, the investment in making the first finished map can be leveraged with other mapsheetsintheseries(morethan4,000inTexas).

AGPS‑ready latitude–longitude graticulewas chosen forthe reference grid, since this is the most widely used and understoodbythegeneralpublic.Agridofticswasusedinstead of a mesh of lines because this leaves the map much less cluttered and easier to read. The tics are distinctive enough from the other symbology to find easily but discreet enough that they do not distract the map reader.

Legend is hand assembled but a single graphic that is the same on all maps

Create a template

Withtheabilitytoautomatemuch,ifnotall,ofthemapspecification elements, a GIS-based map document can be made into a template for a given map product. This template can be used with any number of GIS datasets, as long as each dataset schema supports the layer definitions in the map template. In addition, multiple templates could be designed for the same datasets. For example, one template could be used for topographic base maps, and a different template might be used for thematic maps using much of the same data layered on the digital orthophoto reference layer.


color model

The colors selected for this map represent a conscious intent to think differently about a topographic map.

Contemporary topographic map colors

The design of this map with respect to colors attempts to address the evolution of how topographic maps are used. Colors are selected to balance the natural with the builtenvironment. Highways, roads, and place names are promi-nent, but elements, such as graticules, are less prominent because they are not how most people find locations. This evolution will continue with the widespread adoption of GPS technology.

The colors were chosen to be pleasant yet still convey cultural expectations.Areassuchasparksandopenspaceshouldbegreen.Urbanareasareastuccocolor(versusgraypavementoraboysenberrystainasontraditionaltopographicmaps).CertainkindsofculturalfeaturesnowintheUSGSdata,such as educational, religious, and recreation areas, are given different colors that are easier to locate on maps.

In general, this set of distinct colors was chosen to be small enough to learn easily, particularly if users already knew something about topographic maps. They were chosen to be unambiguous so major kinds of geographic features could be easily distinguished from their neighbors if a strong dif-ference existed; and if two kinds of activity were similar, the difference for their colors would be less distinct. Buildings were specifically treated with gray instead of black so black text labels for those buildings could overstrike the buildings, if necessary, and not lose their legibility.

Whilethisdiscussionhasemphasizedtheuseofcolorsinfilling polygons, these colors are also used in point, line, and other symbols.

The colors on a topographic map are designed to visually discriminate thematic layers;

identify objects through natural colors; and emphasize important features, such as

major roads and rivers. Here are some of the colors used in the TNRIS prototype with

their RGB values.


8

Topographic base map color modelColors defined with RGB values

R:G:B:

204246255

Surface water

R:G:B:

10147252

Natural shorelines and hydro text

R:G:B:

211255190

Background for some hydro areas

R:G:B:

137112

68

Foreground for some hydro areas

109187

67

R:G:B:

Foreground for some hydro areas

R:G:B:

000

Black, used for many symbols

R:G:B:

153204153

Park areas

R:G:B:

225190153

Prison areas

R:G:B:

222140140

Military areas

R:G:B:

245202122

Native American reservations

R:G:B:

255235190

Built up and infrastructure areas

R:G:B:

232190255

Education area

R:G:B:

122182245

Health care area

R:G:B:

230230

0

Religious area

R:G:B:

182252179

Recreation area

R:G:B:

255255190

Agriculture area, yellow stripe

R:G:B:

211255190

Agriculture area, green strip, or woods

R:G:B:

215215158

Scrub

R:G:B:

189247135

Scattered trees background

R:G:B:

215194158

Lava background

R:G:B:

787878

Lava foreground

R:G:B:

225225225

Gravel background

R:G:B:

164121

22

Contour lines

R:G:B:

25500

Fences and road fills

R:G:B:

156156156

Major street fills

R:G:B:

104104104

Structure polygons

R:G:B:

102205171

Submerged contour lines

R:G:B:

170170170

Boundary line, wide backgrounds


It has been difficult in the past to keep complete and current documentation for GIS projects describing such details as:

• Whichfeatureswereeditedforagivenpurpose

• Thesourceoftheupdates

• Thecollectionmethodused

• Theaccuracyof thenewdata (and themethod itwasbasedon)

• Possibly feature‑level metadata, such as a voice clip,scannedfax,XMLdata,orotherdocumentsprovidingcontext for the change to a particular feature

It can be tedious, if not difficult, to collect and maintain this kind of information, but this documentation can provide crucial information for later audits of a geographic dataset. It may become important to identify and revise a particular set of edits later because of a change in policies, procedures, or business requirements. It may also become important to substantiate past decisions, for example, to help resolve con-flicts between the maintenance authority and its customers.

revIsIon management

It is important to not only manage current data, but it is also becoming increasingly

important to enable the review and comparison of historical data with current data.

Now that GIS databases can store the evolution of data over time, organizations should

consider the most appropriate methods for managing historical updates to the database.

Animportantsteptowardthisgoalistheabilitytomanageversioned data in the geodatabase to maintain an archive of all previous states of each dataset. The initial driver for this capability has been to support the editing of a single GIS database by multiple users at the same time.

Revision information

This base map data model implements the basic concept of storing revision information. To accomplish this, many ofthefeatureclasseshaveanattributecalledSource(longinteger).ThisisaforeignkeytotheRevisionInfotable(seeschemabelow).TheObjectIDservesasarevisionIDandprimary key field for joins with other tables having a Source foreign key.

This table can be used across local, state, and federal levels of government. However, the level of government can affect the frequency of database updates. For example, for 1:24,000 topographic map data at the local level, the number of updates on any given day might be high. For 1:24,000 map data at the state and regional levels, however, updates might be aggregated and summarized monthly or even less frequently.

TableRevisionInfo


Allownulls

Revision tracking metadata

Object ID

Long integer Ye s 0 Collection method (key to lookup table)

Long integer Ye s 0 Accuracy measurement

Long integer Ye s 0 Positional accuracy value

Long integer Ye s 0 Foreign key to associated revision information sources

Date Ye s 0 0 8 Date revision was begun

Date Ye s 0 0 8 Date feature name verified

Date Ye s 0 0 8 Date positional accuracy verified

Date Ye s 0 0 8 Date of last verification

Date Ye s 0 0 8 Retirement date

Long integer Ye s 0 Minimum applicable map scale

Long integer Ye s 0 Maximum applicable map scale

Long integer Ye s 0 Maintenance authority (key to lookup table)

Long integer Ye s 0 0 Feature metadata ID, foreign key to metadata table

Field name

OBJECTID

CollMeth

AccMeas

PosAcc

Source

EntryDate

IDDate

PosAccDate

LastVerDate

EndDate

MinScale

MaxScale

Authority

FMID


8

The RevisionInfo table is intended to support GIS data as it moves between local, state, and federal agencies. The Sourcefieldinthistable,aswellastheAuthorityfield,areexpected to vary in usage across different states; the Source field could be a link to additional reference information, and theAuthorityfield could indicate the responsible agencyassociated with each revision record.

Other fields, such as those having to do with collection method, accuracy, and appropriate scales of use, are most likely to be known and maintained at the local level.

Thefeature‑levelmetadataidentification(FMID)fieldisaforeign key to additional tables not shown here. This needs to be managed consistently throughout all levels of govern-ment for uniform access to the metadata.


It can be challenging for a cartographer to model hundreds or possibly thousands of different types of geographic features in a GIS, as many cartographic products require. Supporting a rich classification scheme in a database runs counter to conventional wisdom for database design, which is to reduce the number of tables for performance reasons.

One of the most complex classifications is contained in the Digital Geographic Information Exchange Standard(DIGEST),aninternationalstandardprimarilyusedamongNorthAtlanticTreatyOrganization(NATO)nationalmap-pingagencies.OnecomponentofDIGESTistheFeatureand Attribute Coding Catalog (FACC) data dictionary,which defines a system for associating meaning with geo-graphic features.

This standard is based on a set of feature codes, which can then be further modified by other parameters. For example, an intermittent stream would be described as “River/Stream, hydrologicalcategory=intermittent”(BH140,hyc=6).Achurch would be described as “Building, function = house of worship, house of worship type = church” (AL015,bfc=7,hwt=4).InFACC,theprimaryfeaturecode,suchasBH140andAL015,iscalledtheFCODE,whileadditionalparameters,suchashyc,bfc,andhwt,arecalledACODEs.This system provides a standard, general, and extensible mechanismfordescribingfeatures.TheuseofACODEstoparameterize the feature codes overcomes the limitations of a single linear or hierarchical coding system.

TheFACCdesignationforafeaturecanbeconsideredasanattribute of the feature. It is a complex attribute, because it consistsofanFCODEandoneormoreACODEs,butitislogicallyasingleproperty.Asetoflinefeatures,withtheirFACCcode,couldbemodeledlikethis:

descrIptIve classIFIcatIon model

In a data model with a relatively flat hierarchy of feature types, database designers

can use domains (lookup tables) to help distinguish and describe features. The use of

subtypes can add another level of hierarchy to the classification scheme. Many agen-

cies have developed more complex taxonomies of feature types with rich descriptions.

Prudent database design, however, leans in the direction of reducing the number of

feature classes for several reasons. This section presents an approach for managing a

rich set of feature types within a limited number of feature classes.

In this case, the feature class represents a drainage network of rivers, streams, and canals. Each drainage network element iscodedwiththeappropriateFACCfeaturecode.

As this example illustrates, FACC defines a standard forassigning meaning to features, but it does not dictate any particular organization of features into classes or the actual structure of a GIS data model. In particular, it is not neces-sary that the logical or physical schema of a GIS database design reflect the logical structure of the coding standard. FCODEsdonotdefine featureclasses,andACODEsdonot define feature class fields. The only requirement is that astandardcodeordescription(suchasinFACC)canbeassociated with any feature represented in the database.

ItisnotappropriatetousethedescriptivelogicofFACCoranother coding standard to control the structure of the GIS data model. Other aspects, such as the geographic representa-tionoffeatures(linesorganizedinanetwork,areaswhichshare topology,andsoon); theneedtomodelreal‑world

Contours_VVT is a lookup table that can be used for data valida-tion and symbology definition. For example, FCODE=2 refers to intermediate contours. Two ACODE values, DEP and CAR, further qualify the feature classification.

ID Shape FACC101 xy...xy BH140, hyc=6102 xy...xy BH140, hyc=8103 xy...xy BH140,hyc=8,exs=32


8

objects; or the feature extraction specifications are usually more important factors to consider in defining feature classes inadatabasedesign.Abettermethodistouseassociatedtables that contain the feature and attribute codes.

vAlId vAlUE TABlE APPRoACh

The solution to this issue is called the valid value table approach. In this design, an auxiliary lookup table (theVVT) is associated with each feature class. Examples inthischapterincludeRoadsCartoDissolve_VVT,TransCar-toPoints_VVT,CulturalLines_VVT,CulturalPoints_VVT,CulturalAreas_VVT, Contours_VVT, and Elevation-Points_VVT.

AportionofContours_VVTdataisshownonthepreviouspage.TheVVTIDisthekeyfieldusedforjoinswiththeContourstable.EachrecordhasasinglevalueforFCODEand one or more values separated by a vertical bar “|” symbol forACODEs.Inthistable,therearetwoACODEs,DEPandCAR,foreachFCODEvalue.

This table was used to construct and enumerate a tax-onomy of contour types. Once the types are enumerated, theVVTIDandDescriptionvaluesareplugged into thegeodatabase properties as a domain value lookup table. This

approach requires no additional programming and uses the most efficient method for managing the description lookup.

However,thissimpleuseoftheVVTtableisforassigningfeature symbols and drawing rules, not for rich feature descriptions.SomeVVTtableshaveasmanyas20ACODEsqualifyinga singleFCODE,and itbecomes increasinglyimportant to supportqueries against individualACODEvalues. In this latter case, some additional user program-ming is required to extend and enable the editor and query toolstohavevisibilityintotheVVTtableanditsACODEScolumndirectly.AnArcGISfeaturecodingextensionhasbeenwrittenforthispurposeandisavailableonline(seethetechnicalpaper,FeatureCodingStandardsandGeodatabaseDesign,ESRI2002,andthe‘Furtherresources’sectionattheendofthischapter).

TakingtheVVTconceptonestepfurther,itispossibletouse a small set of auxiliary tables to define a complete feature classification system for the entire GIS database. Such a foundationcouldbeusedtovalidateindividualVVTtables,such as the one just described. The schema for these tables is shown below, with examples on the next page.

TableFCODE


Allownulls

VVT reference table of all valid ACODEvalues for each FCODE

OBJECTID Object ID

FCODE Long integer Ye s 0 Unique feature classification code

ACODERANGE String Ye s 254 Set of all valid ACODEs and values for one FCODE

DESCRIPTIO String Ye s 254 Feature classification description

Default value Domain

TableATTDESC


Allownulls

VVT reference table of unique ACODEsand their descriptions

OBJECTID Object ID

ACODE String Ye s 8 ACODE name

DESCRIPTIO String Ye s 254 Description of this ACODE name


TableATTVAL


Allownulls

VVT reference table of valid ACODEvalues, independent of the feature type

OBJECTID Object ID

ACODE String Ye s 8 ACODE name

VALUE_ Long integer Ye s 0 One valid value of this ACODE

DESCRIPTIO String Ye s 254 Description of this ACODE value

NOTES String Ye s 254 Alternate or supplemental description of this ACODE



a classIFIcatIon model Illustrated

The FCODE table defines the complete set of ACODEs and ACODE values that are valid for each FCODE (partial table content shown).

The ATTDESC table lists and describes each ACODE (partial table content shown).

The tables on these pages effectively define a complete feature classification foundation.

One set of these tables could be used to support any number of cartographic products

on multiple GIS databases. The beauty of this design is the flexibility with which features

can be classified. Few database tables are needed to manage a rich classification system

that allows a variable number of parameters to define any given feature type. This leads to

simpler data models that would not need structural modifications just to accommodate

an evolving classification scheme.

Three tables define any given feature classification system, FCODE,ATTDESC,andATTVAL.Thesetablesaretobe populated by the user/database administrator for use by theArcGISfeaturecodingextensionmentionedpreviously.

To populate these tables, first start with theATTDESCandATTVALtables,creating them as simple tables in a spreadsheet or personal database docu-ment. Next, create an intermediate tablelistingtheACODEsusedbyeachFCODE,withoneFCODE–ACODEpair per record. It is then relatively straightforward to write a program that walks through this intermediate table and the ATTVAL table to generatethe ACODERANGE column of theFCODE table. Some FCODEs mayrequire manual editing, such as those for Buildings in the table shown here (seelastfourrecordsinthediagram).EachoftheseFCODEshasthesameACODEbutwithadifferent range of values. However, these descriptions can alsobeaddedprogrammatically,aslongastheFCODEandeachACODEhavedescriptions.

The FCODE table would be manually edited further toaddtheFCODEdescriptionsandremoveinvalidACODEvalues. It is generally a good idea to have the fewest number ofACODEfieldsnecessary for eachFCODE.ThemoreACODEs there may be for a single FCODE, the moredifficult becomes the task of validating all the values and combinationsofvaluesacrossalltheACODEsforagivenFCODErecord.

IMPlICATIoNS of A vvT APPRoACh

If your database requires the use of an extensive classification system,suchaswithDIGESTFACCorUSGSDigitalLineGraph(DLG),thenyoushouldconsiderusingVVTs.The

approachdescribedherecanaccommodateboththeFACCandDLGclassificationschemesandhelpsensuresemanticintegrity in the database design. It also offers advantages for enhanced database use and for multiscale and multipurpose database specifications.


8

The ATTVAL table lists and describes every value of each ACODE (partial table content shown).

Enhanced database use

Having a more sophisticated classification system embod-ied in the GIS can lead to more expressive queries, feature symbology, and quality assurance during data entry and update.ByincorporatingFCODEsandACODEs(ormajorandminorcodes,aswithUSGSDLG)intotheschema,youcan take advantage of these codes when selecting features for export. These tables essentially form a coded value domain for enforcing data integrity across combinations of multiple attributes on features and other objects. Thus, a user can assign major and minor code values to the data yet be prevented from assigning invalid combinations. For example, a user should be able to create “a new road that is paved and has a median” but not to create “a new road that is dirt and has a median.”

Multiscale use

Using major and minor codes are usually independent of featuregeometrytype(point,line,polygon).Thisisespe-cially useful for multiscale databases in which features may change in geometry type as the display scale changes. For example, a building could be represented as a polygon at a large scale, as a point at a smaller scale, and be aggregated with other nearby buildings into a built-up area polygon at astillsmallerscale.WiththeVVTapproach,thefeature–attribute combinations are not representation dependent and can be applied regardless of the geometry type needed at any given moment.

Multipurpose use

VVTs could be used for multiple data and cartographicproductsaswell.Forexample,aVVTcouldbeusedtodefinehow features are shown on different types of maps and to help define different symbology for each of these products. ThiscanbeachievedbyaddingcolumnstotheVVTtableitself, such as a column for the product type or other context.

Withappropriatequeries,themap’sappearancecould then reflect the user’s current purpose with the least effort to change data layers.


tHe model In actIon

Muchofthebasemapcartographicproductdescribedsofar in this chapter has been based on the organization and symbology of data for the standard USGS topographic map series.WhiletheTNRISprojectteamfavoredthesedesignconcepts, all of which were implemented in a working pro-totype, its firm goal was to fully automate the map produc-tionprocess,whichnecessitatedasimplerdesign.Anotherguiding principle for TNRIS was to make updates to the source database to update associated map products, both at thestatelevelandfortheUSGSNationalMap.

A TAlE of TWo SERIES

In thinking about the most maintainable organization of data for its map products, the TNRIS team took into account both the intended use of the maps, as well as the availability of high-resolution(1meter)aerialphotography.Insteadofproducinga single map series, TNRIS settled on two: one based on a simplification of the USGS topographic map series and another series having a detailed DOQQ backdrop. The simplifiedtopographic map presents an easy-to-read view of many types ofphysicalfeatures,whiletheDOQQ‑basedseriessupportsfine resolution and dynamic data, such as urban detail.

This approach has led to several simplifications in the base map design that may be of as much interest to readers as the concepts presented earlier. These simplifications can be summarized as:

• RefinementandupdateoftheUSGSGNISdatatosup-port map layers for landmarks and other cultural point features

• EliminationofdatacollectionandrenderingforfootprintsofbuildingsinfavoroftheDOQQbackdropwithGNISnames overlaid

• Useofdatabaseviewstodistinguishthevariouscategoriesof streets and highways for display in the map editor

• Eliminationoftopologycreationormaintenance

TNRIS collects data for its statewide mapping program through collaboration with

many state agencies, federal agencies, and local governments. To make the most use

of its limited budget and staff resources, TNRIS sought to fully automate its strategic

base map database, called StratMap, by streamlining several of the design concepts

presented in this chapter.

• Elimination(fornow)oftheVVTapproachinfavorofsimple feature classifications and symbology

• Useofstandardfeaturelabelinginsteadoffeature‑linkedannotation

• LicensingofGeographicDataTechnology(GDT)datafor labeling of city streets

GNIS and the Texas Names Gazetteer

Fundamental to both map series, TNRIS augments GNIS (a tabulardataset)bymaking thenames intogeographicfeatures to support labeling of key buildings and other land-marks in orthophotos. These place name features are called theTexasNamesGazetteer.Withthisgazetteer,errorsaremore easily found, and updates to the names dataset directly affect related map products.

GNIS data collection in Texas continues in a multiyear, multiphase project with the USGS. TNRIS staff have compiled well over one hundred reference sources for the names and, as a result, have found it necessary to prioritize the types of features included in the names database. The most important are schools, hospitals and clinics, parks, malls, courthouses and other key government buildings, andpopulatedplaces(PPLs),whichincludemetropolitanutility districts and colonias (small, primarily Hispanicvillages).Theemphasisisonwidelyrecognizedstructuresand other important landmarks that can serve as aids to navigation. Hydrographic features, such as rivers, springs, and dams, are also included. Over time, other interesting and useful landmarks, such as museums, libraries, and golf courses, may be added.

doQQ backdrop

In addition to its use in proofing vector data, the use of high-resolution aerial photography addresses an important need—offering more current and correct data for the highly dynamic urban landscape. It is easier to simply update the photo than to redraw and proof building footprints.


8

database views

The practice of using multiple layers for transpor-tation features, as described earlier, can be carried out in a number of ways. In the early prototype, on-the-fly relationships were used for each of the many transportation layers. Each relate resulted in a query of the roads feature class to select a particular subsetof road features.Witha largedatabase of detailed road features, however, on-the-fly relationships did not provide adequate performance. Instead, the database administra-tor created database views for subgroups of road features. Corresponding map layers for theseviews were created, one map layer per database view. This provided the performance needed in the production database.

Topology

TNRIS chose not to create any topologies. This was largely because TNRIS does not have authority to alter the data for many of the feature classes but is simply publishing the data compiled from its many sources.

valid value Tables

The TNRIS team chose to use a simple classification scheme fortheirfeatures,precludingtheneedfortheVVTapproachdescribed earlier in this chapter. This allows them to keep the database structure similar to the map structure, which their customers are using when they place orders. It also reduces the potential for classification errors when entering data into the database.

feature labeling versus annotation

The TNRIS team chose to use automatic label-ing based on feature attributes, rather than using annotation features. For area features such as city, county, and state boundaries, they created both polygon and line feature classes, the polygon for shading and for a centered label, and the line features for labeling along the boundary.

licensing GdT data

For a fee, TNRIS licensed the use of Geographic DataTechnologycitystreetdataforthestateofTexas. This was not for the actual street lines, whichcomefromTxDOT,butforthelocalstreetnames,which arenot included in theTxDOTdata. TNRIS makes the GDT line featurestransparent but turns on labels, thus annotating theTxDOTstreetdata.

Detail of Southlake and Grapevine, Texas, showing organization and symbology for 1:24,000 scale topographic base map

Detail of Southlake–Grapevine DOQQ and vector features for map series that can be used effectively at larger scales than 1:24,000. Note the different colors used for easier identification of major roads, rail, and landmark points against the DOQQ backdrop.


tHe model In actIon, contInued

TNRISandStratMaprequireasimpledatamodelthatcansupport integration of multiple data sources because the source content comes from several state, regional, and local agencies.TheTexasDepartmentofTransportationprovidesthe greatest share of data, but TNRIS has literally hundreds of sources for all the feature classes shown here.

The same thematic layers and broad categories of feature classes presented at the

beginning of this chapter still hold, but the specific feature classes and map layers have

changed for the current TNRIS work in progress, primarily for simpler organization.

Feature dataset Landmarks and boundaries

Line feature classStateBoundaryLine

Polygon feature classStateBoundaryArea

Polygon feature classRecreationArea

Polygon feature classPublicLandsArea

Polygon feature classLandmarkArea

Polygon feature classIndianReservationArea

Polygon feature classGovernmentFacilityArea

Polygon feature classEducationFacilityArea

Line feature classCountyBoundaryLine

Polygon feature classCountyBoundaryArea

Line feature classCityBoundaryLine

Polygon feature classCityBoundaryArea

Polygon feature classAquacultureArea

Feature dataset Hydrography

Line feature classSurfaceWaterName

Polygon feature classNHD_waterbody

Polygon feature classNHD_stream

Point feature classHydroPoint

Feature dataset Infrastructure

Polygon feature classHazardousMaterialsFacility

Polygon feature classHealthCareArea

Polygon feature classMilitaryArea

Feature dataset Reference

Polygon feature classImageCatalogIndex

Polygon feature classUSGS24K_QuadIndex

Polygon feature classNAD83_DoqqIndex

Feature dataset Transportation

Polygon feature classAirTransArea

Polygon feature classPortFacilityArea

Line feature classRailroadLine

Line feature classTrans_view_cntyrd

Line feature classTrans_view_ihwy

Line feature classTransGDT_street

Line feature classTrans_view_street

Line feature classTrans_view_secroute

Line feature classTrans_view_parkrec

Line feature classTrans_view_majorhwy

Point feature classLandmarkPoint

Landmarks and BoundariesThese feature classes capture the principal cultural layers. The Texas Names Gazetteer is integrated with landmark points, allowing easier proofing and updating. Multiple

layers are created for most of these classes, one for use over DOQQ and a second for use without DOQQ.

Hydrography and HypsographyRivers, streams, and water bodies are collected at 1:100,000 from NHD, and at 1:24,000 from enhanced NHD. An extensive springs dataset is incorporated into the Texas Names Gazetteer, as well as surface water names. Contour intervals vary from 5 to 40 feet.

InfrastructureInfrastructure features are for important land uses not normally considered cultural.

ReferenceReference datasets include an index to the USGS 1:24,000 topographic map quad sheets, a DOQQ index, and a 1-degree latitude–longitude grid, which is an index to the DOQQ image catalog.

TransportationHighways, streets, and railroads are provided by TxDOT. These are accurate enough to overlay on 1-meter orthophotos. Multiple layers are created for major highways and railroads, one for use over DOQQ and a second for use without DOQQ.

Feature dataset Hypsography

Point feature classSpotElevation

Line feature classContourLine


8

Feature dataset Landmarks and boundaries

Line feature classStateBoundaryLine

Polygon feature classStateBoundaryArea

Polygon feature classRecreationArea

Polygon feature classPublicLandsArea

Polygon feature classLandmarkArea

Polygon feature classIndianReservationArea

Polygon feature classGovernmentFacilityArea

Polygon feature classEducationFacilityArea

Line feature classCountyBoundaryLine

Polygon feature classCountyBoundaryArea

Line feature classCityBoundaryLine

Polygon feature classCityBoundaryArea

Polygon feature classAquacultureArea

Feature dataset Hydrography

Line feature classSurfaceWaterName

Polygon feature classNHD_waterbody

Polygon feature classNHD_stream

Point feature classHydroPoint

Feature dataset Infrastructure

Polygon feature classHazardousMaterialsFacility

Polygon feature classHealthCareArea

Polygon feature classMilitaryArea

Feature dataset Reference

Polygon feature classImageCatalogIndex

Polygon feature classUSGS24K_QuadIndex

Polygon feature classNAD83_DoqqIndex

Feature dataset Transportation

Polygon feature classAirTransArea

Polygon feature classPortFacilityArea

Line feature classRailroadLine

Line feature classTrans_view_cntyrd

Line feature classTrans_view_ihwy

Line feature classTransGDT_street

Line feature classTrans_view_street

Line feature classTrans_view_secroute

Line feature classTrans_view_parkrec

Line feature classTrans_view_majorhwy

Point feature classLandmarkPoint

Landmarks and BoundariesThese feature classes capture the principal cultural layers. The Texas Names Gazetteer is integrated with landmark points, allowing easier proofing and updating. Multiple

layers are created for most of these classes, one for use over DOQQ and a second for use without DOQQ.

Hydrography and HypsographyRivers, streams, and water bodies are collected at 1:100,000 from NHD, and at 1:24,000 from enhanced NHD. An extensive springs dataset is incorporated into the Texas Names Gazetteer, as well as surface water names. Contour intervals vary from 5 to 40 feet.

InfrastructureInfrastructure features are for important land uses not normally considered cultural.

ReferenceReference datasets include an index to the USGS 1:24,000 topographic map quad sheets, a DOQQ index, and a 1-degree latitude–longitude grid, which is an index to the DOQQ image catalog.

TransportationHighways, streets, and railroads are provided by TxDOT. These are accurate enough to overlay on 1-meter orthophotos. Multiple layers are created for major highways and railroads, one for use over DOQQ and a second for use without DOQQ.

Feature dataset Hypsography

Point feature classSpotElevation

Line feature classContourLine


tnrIs transportatIon

The transportation feature dataset has certain distinctions worth mentioning, including the use of database views, a single elevation for all roads, the use of multiple fill layers to achieve dashed-line road symbols, simplification of sym-bologyforuseoverorthophotos,andtheuseofGDTstreetdata for labeling.

database views

TNRIS uses six categories of roads: interstate highways; U.S. andstatehighways;secondaryroutes,suchasFMsandRRs,county roads; park and recreation roads; and local streets. These categories are revealed to the GIS as database views. Adatabaseviewisanamedselectionofrecordsfromarela-tionaldatabasesuchasOracle,IBMDB2,orMicrosoftSQLServer.TheseviewsappearasseparatetablestoArcSDEandare much faster in operation than using on-the-fly selection queriesfromArcMap.

Single elevation for all roads

Notice the close-up view of a highway interchange in the figure on the next page. TNRIS creates multiple layers for drawing the different classes of roads but has fewer such layers for transportation than was discussed earlier in this chapter. This is to simplify and streamline data updates and map generation. For example, all road and ramp segments in the interchange shown appear to be at the same elevation inthisfigure.Atascaleof1:24,000,thedetailofrepresent-ing all overpasses and underpasses correctly was considered unnecessary,andatlargerscales(zoomedintothemap),theorthophoto can provide this level of detail.

Creating dashed‑line road symbols

The red–white dash pattern used for major highways isaccomplished by assigning two fill layers, the first having the red dash and the second having the white dash, as can be seen in the figure’s layer list.

TNRIS transportation data is based on TxDOT, GDT, and other sources. The TxDOT data is

detailed and is updated on a regular basis. This is well suited for overlaying on 1–meter

resolution orthophotos.

orthophoto symbolization

TheTxDOTtransportationdataissufficientlydetailedfor1:24,000-scale topographic maps and as overlays on 1-meter orthophotosatmuchlargerscales(upto1:10,000scale).Adifferentrepresentationisusedforsometransportationfeatures when the roads are displayed over an orthophoto backdrop. Given the red tint in many aerial photographs, the dashed red symbol used for major highways is difficult toreadoverDOQQs,sotheseroadsarechangedtoasolidwhite fill.

local street labels

Notice the local street names in this figure. These are the labelsfromGDTstreetdata,forwhichtheGDTstreetlinesthemselveshavebeenmadetransparent,sotheTxDOTroadlines are the principal data source.

Transportation areas

TNRIS includes air and water facilities, such as airports and seaports, to be part of the transportation feature dataset as separate feature classes. The layers made visible are shown at the bottom of the layer list in the figure.


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tnrIs landmarks and boundarIes

The TNRIS landmarks and boundaries dataset has its own set of issues: how to label the edges as well as the centroid of administrative areas, how to symbolize over an orthophoto, and how to deal with multiple noncoincident boundary features along the same path. Again, keep in mind thisorganization is still a work in progress and is subject to change. In particular, the boundary types are in flux at the time of this writing.

Administrative area boundaries

TNRIS uses both polygon and line features and layers to represent administrative areas, such as city, county, regional council of governments, and state jurisdictions. The polygon feature provides an anchor for interior labeling of the area, while the line feature provides an anchor for labeling parallel to,andonbothsidesof,acountyorstateline.Citypolygonfeatures only are shown in the figure on the next page; the line features are added as needed for cartographic finishing.

orthophoto symbolization

The orthophoto shown earlier illustrates the symbolization usedforlandmarkfeatureswhenviewedoverDOQQ.Mostof the point symbols in the layer list for the map at right are coloredyellowforviewingoverDOQQ.

dealing with multiple, almost coincident features

Manyjurisdictionsthroughoutthestatehaveoverlappinginterests incertainboundaries.Acommoncaseofthis iswhereTxDOTmaintainsacountyboundarydatabaseinsupport of its road maintenance and other contracts. The pertinent city and county governments will also have their version of the county boundaries. Since these are collected and maintained independently of each other, these bound-aries often do not coincide. Since TNRIS does not have authority to change these boundaries, it finesses this issue by using lines for the boundaries that are thick enough to mask most discrepancies.

Landmarks and boundaries in the TNRIS database are grouped together in the same

feature dataset. Integrated with the landmark data is the Texas Names Gazetteer, which

is a geographic extension and refinement of GNIS.


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tnrIs HydrograpHy and HypsograpHy

Nhd hydrography

For layer display, TNRIS simplifies the hydrographic fea-turesfromArcHydrointoasmallnumberofclassesbasedontheNHDdata fromtheUSGS.This includesstreamflow lines, pipelines, connections, and water bodies. Several types of water bodies are shown in the figure on the next page’s layer list.

Springs database

AnextensivedatabaseofspringsisalsomaintainedbytheTexasWaterDevelopmentBoardinconjunctionwiththeUSGS. Since these point features are also included in the Texas Names Gazetteer, they are displayed as part of the landmarks layer described earlier.

hypsography

ContourdataistakenandrefinedfromUSGSDLGsources,withcontourintervalsvaryingfrom5to40feet.Asimpleset of contour line types is used for these layers.

Asingleclassofelevationpointfeaturesisused,basedonspotelevationdatafromUSGSDLGs.

Hydrography for TNRIS comes primarily from the U.S. National Hydro Data-set. This has, until recently, been collected at a scale of 1:100,000 but is now being enhanced and updated with 1:24,000 data. Hypsogra -phy for contour lines and spot elevations is based on USGS data at a scale of 1:24,000.


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cartograpHIc data model summary

Cartographicproductsareinevitablyrepresentationsofreal-ity chosen carefully by the cartographer to make the map as readable as possible. For example, a road next to a river might be displaced on the map from its actual physical location to distinguish it from the river it follows and to accurately place theseobjectsrelativetooneanother(“theroadrunsalongthewestsideoftheriver”).Formillennia,cartographicmapshave been the product of human manual skill and labor. But in recent decades, it has become possible to automate more and more aspects of cartography.

In the context of a topographic base map data model, you have now seen numerous elements of a cartographic data model. This is an additive data model in the sense that it can be added to essentially any kind of landscape data model, where the term landscape refers to a locationally accurate representationofsomeareaofinterest.Acartographicdatamodel can include any number of the following elements: additions to the schema and content of geographic feature classes, a descriptive classification scheme, a cartographic data collection specification, a map layout specification, and any number of map layers. These are discussed further below.

To meet the cartographic requirements that might be imposed on a GIS, a complete

cartographic data model should be considered. This data model potentially consists

of several kinds of extensions to the landscape data model.

Additions to schema

Several of the feature classes in this base map data model have additional attributes used just for cartographic purposes. The OverpassLevelattributeontransportationclassesisintendedto support accurate depiction of street and highway over-passesandunderpasses.TheVVTIDattributeofnumerousfeature classes is a foreign key to a classification record used to control symbology. The VVT tables are necessary tosupportthisuse.TheRoadsCartoDissolvefeatureclassisanentire feature class made to support accurate representation of streets and highways. These are just a few of the ways that the base map schema has been extended.

Additional features

In many cases, new features must be added to the database to reflect cartographic adjustments to locationally accurate fea-tures without losing the accurate source data. For example, new features may be created from geoprocessing original source features, such as to generalize selected features for use at a different scale.

descriptive classification system

Adetailed,hierarchicalfeatureclassificationschemeisanimportant part of many cartographic data models, par-ticularly for national mapping agencies (NMAs), whichgenerally require the use of established standard coding schemes for feature types and attribute values, as discussed earlier in the chapter.

Cartographic specification

Atascaleof1:24,000,lakesofatleast1squarekilometerinarea can be drawn as polygons; if they have less area, then they may be drawn as point locations or omitted entirely. Acartographerappliesdatacollectionrulessuchasthistovirtually every type of feature in the database.

It tells the truth by lying, like a poemWith bold hyperbole of shape and line —

A masterpiece of false simplicity.Its secret meanings must be mulled upon,

Yet all the world is open to a glance.With colors to fire the mind, a song of names,A painting that is not at home on the walls

But crumpled on a station wagon floor,Worn through at folds, tape patched

and chocolate smudged(What other work of art can lead you home?)

— A map was made to use.

Juliana O. Muehrcke


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Map layout specification

Asdemonstratedpreviously,therearemanyelementsinahardcopy map layout, such as the grids and graticules, mag-netic North arrow direction, map legend, and so on. These could be based on a national standard, such as the USGS 1:24,000 topographic map series, or you could design your own. Implementing such a map layout specification may involve still more additions to the geodatabase schema, but the more that can be integrated within the database, the easier it will be to share it with other data providers and users.

Map layers

Finally, the map layers themselves in the GIS can form an important part of a cartographic data model. In the trans-portation feature dataset of this base map data model, there were numerous map layers used to represent road casing and fill for each overpass or underpass level in the dataset. Each of these layers invoked a query to the database and imposedaparticularsymbologyonthequeryresult.Maplayer properties also determine the valid scale range and transparency for displaying a given feature class. The layers essentially implement the cartographic specification rules.

All of these elements together complete the cartographicdata model. You are free to use any combination of these that suit your application requirements, keeping in mind standard practices and guidelines for achieving high-quality cartographic results.


reFerences

REfERENCES ANd fURThER REAdINGDataUsersGuide1:DigitalLineGraphsFrom1:24,000‑

ScaleMaps.1990.Reston,Virginia:U.S.Departmentofthe Interior, U.S. Geological Survey.

Dent,BordenD.1998.Cartography: Thematic Map Design. McGraw‑Hill.

DigitalGeographicInformationExchangeStandard,Part4,AnnexC,AlphabetizedContentListingofAllFeaturesand Attributes, edition 2.1. 2000. Washington, D.C.:DigitalGeographicInformationWorkingGroup.URL:http://www.digest.org/html/DIGEST_2‑1_Part4_AnnexC.pdf.

Digital Texas: 2002 Biennial Report on GIS Technology. 2002. Austin:TexasGeographicInformationCouncil.

Feature Coding Standards and Geodatabase Design. 2002. ESRITechnicalPaper,URL:http://arconline.esri.com/arconline/whitepapers/ao_/Feature_Coding_Standards_and_Geodatabase_Design.pdf.

Imhoff, Euard. 1982. Cartographic Relief Presentation.DeGruyter, New York.

NationalMappingProgramTechnicalInstructions,Part2AttributeCoding,StandardsforRevisedPrimarySeriesQuadrangleMaps.2001.Reston,Virginia:U.S.Depart-ment of the Interior, U.S. Geological Survey, National MappingDivision.

National Mapping Program Technical Instructions, Part3AttributeCoding,StandardsforDigitalLineGraphs.1998.Reston,Virginia:U.S.DepartmentoftheInterior,U.S.GeologicalSurvey,NationalMappingDivision.

National Mapping Program Technical Instructions, Part5 Publication Symbols, Standards for 1:24,000- and 1:25,000‑Scale Quadrangle Maps. 2002. Reston, Vir-ginia:U.S.DepartmentoftheInterior,U.S.GeologicalSurvey,NationalMappingDivision.

National Mapping Program Technical Instructions, Part6 Publication Symbols, Standards for 1:24,000- and 1:25,000‑Scale Quadrangle Maps. 2001. Reston, Vir-ginia:U.S.DepartmentoftheInterior,U.S.GeologicalSurvey,NationalMappingDivision.

National Mapping Program Technical Instructions,Standards for1:24,000‑ScaleDigitalLineGraphsandQuadrangleMaps.2001.Reston,Virginia:U.S.Depart-ment of the Interior, U.S. Geological Survey, National MappingDivision.

StratMapTexas,DigitallyRemastered:DraftTransporta-tionDataDescription,Version4.2000.Austin,Texas:GIS/Trans,Ltd.

ACkNoWlEdGMENTS

DeepthankstotheTNRISstaff:DrewDecker,MarcyBer-brick,ErikaBoghici,DavidPimentel,BrentPorter,FeliciaRetiz,andChrisWilliams;toRonPigottoftheTexasWaterDevelopmentBoard, toDawnOrtizof theUniversityofTexasCenterforSpaceResearch,andtoMichaelOuimetoftheTexasDepartmentofInformationResourcesinAustin,Texas, for sharing data, time, and experience working with theTNRISdatamodels.CharlieFryeandAileenBuckleyof ESRI provided content for this chapter.

fURThER RESoURCES

Follow the Basemap link from ESRI ArcOnline at http://support.esri.com/datamodels for further information on this data model.

The Feature Coding Extension for ArcGIS version 8.3and higher is available at http://arcobjectsonline.esri.com. ClickonSamplesintheTopicslist(leftcolumn),thenonGeodatabase,thenonArcGISExtensionforfeaturecodingstandards. Links todownload the VisualBasic and C++versions will then appear.


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TheU.S.EPAiscollectingandupdatingnationwidelandcoverdataandotherthemesaspartofitsMulti‑ResolutionLandCharacteristicsConsortium.Seehttp://www.epa.gov/mrlc/data.html for more information.

Manygeographicnameinventorieshavebeencompiledatthe national level; one of these is the USGS Geographic Names Information System. See http://geonames.usgs.gov/ for more information.

base maps require a data model that supports the...

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