Slide 1

Data Modeling for Large Scale Maps Data Modeling for Large Scale Maps and Map Productionand Map Production

Charlie Frye, ESRI RedlandsCharlie Frye, ESRI RedlandsAileen Buckley, PhD, ESRI RedlandsAileen Buckley, PhD, ESRI Redlands

Cartographic Research and Special Projects GroupCartographic Research and Special Projects Group

Abstract: In this session, we focus on the requirements for modeling data to produce large

scale maps. Defining an appropriate data model for map compilation and production

assures consistent and appropriate maps for local, regional and municipal resource

management, as well as the more recently required monitoring and management of

information for homeland security. Topics include: using high resolution imagery to

derive cartographic data, such as physiography and hydrography; deriving cultural

cartographic features from parcel and other municipal data; defining the semantic models

for data at various scales; and procedures for extracting smaller scale data from larger

scale data. These techniques and concepts are applied in particular to the use of local

scale GIS data to make high quality cartographic products that meet the various needs of

its users.

Slide 2

Session OverviewSession Overview

•• Show examples that highlightShow examples that highlight–– How to model cartographic information in GISHow to model cartographic information in GIS–– A systematic approach to modeling data facilitates A systematic approach to modeling data facilitates

map productionmap production–– How to solve common cartographic design problems, How to solve common cartographic design problems,

particularly for large scale maps particularly for large scale maps –– The methodologies for creating cartographic dataThe methodologies for creating cartographic data

What should be common techniques for modeling cartographic information in a GIS

database

One of our main goals is to develop methods for automating map production in GIS

through effective data management

Slide 3

Who We Are and What We DoWho We Are and What We Do

•• Cartographic Research and Special Projects Cartographic Research and Special Projects GroupGroup–– Find and document / publish best practices in GISFind and document / publish best practices in GIS--

based cartographybased cartography•• Importance of this sessionImportance of this session

–– Lack of a common model for maps in the U.S. (in Lack of a common model for maps in the U.S. (in particular) at scales larger than 1:24,000 particular) at scales larger than 1:24,000

–– The volume of The volume of ““local scalelocal scale”” data is very high, but is it data is very high, but is it usable for mapping?usable for mapping?

•• Lots of assumptions like, Lots of assumptions like, ““it should just workit should just work””•• Could you make your maps with your neighborCould you make your maps with your neighbor’’s data?s data?•• What if you had to go to the USGS (TNM) to get yours or What if you had to go to the USGS (TNM) to get yours or

your neighboryour neighbor’’s data?s data?

Before we go off half-cocked down that path, the real point is, is that all other things

being equal, is the data you are publishing (to The National Map) good enough for

somebody else to make a good map? The reason we’re here is to show you what we’d

hope our neighbors have for data.

Slide 4

What is What is ““Large ScaleLarge Scale””??

•• 1:5,000 1:5,000 (at or near)(at or near)–– Insets maps likely to happen at 1:1200 to ~1:2000Insets maps likely to happen at 1:1200 to ~1:2000

•• What activities are supported by maps at this What activities are supported by maps at this scale?scale?

PublicPublic•• Local Local ““eventevent””

managementmanagement•• SecuritySecurity•• Planning and Planning and

decision decision makingmaking

PrivatePrivate•• LBS supportLBS support•• High quality High quality

navigation navigation systemssystems

Poll on who’s (categorically) attending.

Slide 5

1:5,0001:5,000

Slide 6

1: 25,0001: 25,000

Slide 7

1:100,0001:100,000

Slide 8

Examples for TodayExamples for Today

•• Cultural Cultural –– Buildings & StructuresBuildings & Structures–– Cultural AreasCultural Areas–– Place NamesPlace Names

•• AdministrativeAdministrative–– BoundariesBoundaries–– NamesNames

•• TransportationTransportation–– Centerlines vs. PolygonsCenterlines vs. Polygons

•• TerrainTerrain–– Data Sources: LIDAR to Data Sources: LIDAR to

DEMsDEMs–– HillshadingHillshading–– ContoursContours

•• HydrographyHydrography–– Data SourcesData Sources

•• Ortho ImageryOrtho Imagery

Warn that there’s lots of material and that we’re sacrificing some “good presentation”

strategies in favor of providing content on the CD.

Slide 9

Cultural: Buildings and StructuresCultural: Buildings and Structures

•• As scale increases more information can be As scale increases more information can be shownshown

•• On general reference mapsOn general reference maps–– 25K base map model had 43 building types 25K base map model had 43 building types

•• A few are symbolized uniquely and very few have namesA few are symbolized uniquely and very few have names–– 5K base map model has 194 building types5K base map model has 194 building types

•• Most are symbolized by a major type category and labeled Most are symbolized by a major type category and labeled by nameby name

–– Over 50% of nonOver 50% of non--residential buildings have namesresidential buildings have names

•• On special purpose maps (e.g., Natural Disaster On special purpose maps (e.g., Natural Disaster Response & Management)Response & Management)–– Specific information about buildings or about a Specific information about buildings or about a

specific class of buildings may be neededspecific class of buildings may be needed

One issue here that is not obvious is that many of the 43 types of buildings on the 25K

maps should be differentiated on the maps, and currently they are not on USGS maps.

For instance the locations of police and fire stations, paramedics, hospitals, etc…

We used Google Maps to find many of the names, searching by business type and by

location

Slide 10

Cultural: Major Building Types (1:5,000)Cultural: Major Building Types (1:5,000)

•• Major types of buildings (194)Major types of buildings (194)–– General Case (37)General Case (37)–– Commercial (26)Commercial (26)–– Agricultural (6)Agricultural (6)–– Educational (14)Educational (14)–– Industrial/Utility (22)Industrial/Utility (22)–– Governmental (35)Governmental (35)–– Military (14)Military (14)–– Residential (11)Residential (11)–– Religious (13)Religious (13)–– Healthcare (16)Healthcare (16)

Slide 11

Building Labels (1:5,000)Building Labels (1:5,000)

Slide 12

Buildings Label ManagerBuildings Label Manager

Slide 13

Buildings: Label Manager Class SQLBuildings: Label Manager Class SQL

Slide 14

Cultural: Labeling Buildings (1:5,000)Cultural: Labeling Buildings (1:5,000)

•• Goal: Balance building size with label sizeGoal: Balance building size with label size

•• Large buildings (> 20,000 ft2)Large buildings (> 20,000 ft2)–– Stack, Reduce Font Size, Overrun (24pts), May not Stack, Reduce Font Size, Overrun (24pts), May not

place outside, Position = Horizontalplace outside, Position = Horizontal•• Smaller buildings (8,000 Smaller buildings (8,000 -- 20,000 ft2)20,000 ft2)

–– Stack Reduce font size, overrun(24pts), May place Stack Reduce font size, overrun(24pts), May place outside, Has leader line symbol, Position = Horizontaloutside, Has leader line symbol, Position = Horizontal

•• Smallest buildings (< 8,000 ft2)Smallest buildings (< 8,000 ft2)–– Stack Reduce font size, overrun(24pts), May place Stack Reduce font size, overrun(24pts), May place

outside, Has leader line symbol, Position = Offset outside, Has leader line symbol, Position = Offset HorizontalHorizontal

University of Boise Example; not all buildings are completely contained. Intersects may

save more time. Naming then becomes an issue. “BSU - ??????” for buildings outside

and no “BSU –” for buildings inside.

Slide 15

Cultural: Labeling Buildings (1:5,000)Cultural: Labeling Buildings (1:5,000)

•• Building complexesBuilding complexes–– Attribute containing T or F for building inside complexAttribute containing T or F for building inside complex–– Automated based on select by location and calculateAutomated based on select by location and calculate–– Label classes for buildings in complexes have lower Label classes for buildings in complexes have lower

priority ranking (below below complex labels)priority ranking (below below complex labels)•• Important buildingsImportant buildings

–– Always labeled, in separate classes and given Always labeled, in separate classes and given highest priorityhighest priority

–– Manual based on local knowledgeManual based on local knowledge

Slide 16

Cultural AreasCultural Areas

•• U.S. mapping tradition for land cover is U.S. mapping tradition for land cover is ““safesafe””, , but at expense of useful contentbut at expense of useful content–– Land cover does not always sufficiently express land Land cover does not always sufficiently express land

useuse–– Intended land cover/use like zoning is misleading on Intended land cover/use like zoning is misleading on

reference mapsreference maps•• Robustly classified cultural areas fill this gapRobustly classified cultural areas fill this gap•• ESRI 1:5,000 scale model has 8 major classes ESRI 1:5,000 scale model has 8 major classes

and 177 specific typesand 177 specific types–– USGS model has less than 20 that are drawn on USGS model has less than 20 that are drawn on

mapsmaps–– About 80 exist, but for the most part are not usedAbout 80 exist, but for the most part are not used

Slide 17

Cultural Areas: Major Types (1:5,000)Cultural Areas: Major Types (1:5,000)

•• Major types of cultural areas (177)Major types of cultural areas (177)–– Agricultural (16)Agricultural (16)–– Archeological (6)Archeological (6)–– Building Complexes (33)Building Complexes (33)–– Natural Resources (33)Natural Resources (33)–– Utility/Industrial (23)Utility/Industrial (23)–– Recreation (45)Recreation (45)–– Religious (6 conservative effort)Religious (6 conservative effort)–– Special Areas (15) Special Areas (15)

Slide 18

Cultural: Place NamesCultural: Place Names

•• Centrally managed normalized names tableCentrally managed normalized names table–– Sets organizational standard for namesSets organizational standard for names–– Joined to features using Joined to features using Name_IDName_ID fieldfield–– Exported to Exported to ““Cartographic DataCartographic Data””

•• Cartographic representations of namesCartographic representations of names–– Names are joined and result is exported to become a Names are joined and result is exported to become a

cartographic datasetcartographic dataset–– LabelStrLabelStr field: Contains string representation for mapsfield: Contains string representation for maps

•• Example: Example: ““Interstate 84Interstate 84”” is shown with just is shown with just ““8484””•• Example: Example: ““SasquatchSasquatch MountainMountain”” is abbreviated as is abbreviated as

““SasquatchSasquatch MtnMtn””–– FeatTypeFeatType field: Used in SQL Query Option to set up field: Used in SQL Query Option to set up

Label Classes, and is basis for text symbolLabel Classes, and is basis for text symbol

Slide 19

DemoDemo

NamesNames

Show BuildRelationships.mxd. Have ArcCatalog open with the PGDM_DCM directory showing.

This is a demo of the address data model and it is used here to show a centrally managed names database

that allows you to get the name for your maps from different points of entry.

BuildRelationships.mxd

What you are seeing here is cultural areas, parcels, buildings and address points. I’ll use the identify tool

and I’ll move the window separator so we can see the left side a little better.

If I identify on one of these larger buildings, we can take a look at some of its attributes. I’ll click on some

of the drop downs and you can see that:

“has street” contains the street name

“is named” shows you that it is actually encoded now to carry some of the cartographic attributes in the

database

Some of the other feature attributes can also be used for naming.

Now let’s look at ArcCatalog. Here we’ll look at the Ada_TopoBase geodatabase – this is a database we

are using from Ada County, Idaho to test some fo thee methods and to further develop the data model. I’ll

use the Preview Geography window to show you Feature Names – this has 794 items, and Street Names –

this has over 7300 items. But the point is that these are the centrally managed names database that are used

to label the features on our map. And the Feature Names really isn’t all that long – at least for Ada County!

Slide 20

Cultural Features: LabelingCultural Features: Labeling

•• Even features that donEven features that don’’t have names often get t have names often get labelslabels–– Label by feature type Label by feature type

•• Make sure feature type descriptions are Make sure feature type descriptions are ““MapMap--worthyworthy””•• Shortcut is to add these descriptions to the Shortcut is to add these descriptions to the LabelStrLabelStr field field

when no name existswhen no name exists

•• Label placement follows similar placement Label placement follows similar placement strategy as large buildingsstrategy as large buildings

Slide 21

Cultural Features: SymbologyCultural Features: Symbology

•• Three Layers Three Layers (based on CFT_ID field)(based on CFT_ID field)1.1. Cultural Overlays: Tracks, ball fields, ball courts, etc.Cultural Overlays: Tracks, ball fields, ball courts, etc.2.2. Building Complexes (complexes can fall inside of Building Complexes (complexes can fall inside of

other cultural areasother cultural areas3.3. All other cultural AreasAll other cultural Areas

Aileen Demo this with TestMap_5K_D_Series.mxd

Slide 22

BoundariesBoundaries

•• RepresentationRepresentation–– Typically GIS representation is polygonTypically GIS representation is polygon–– Cartographic line work is more effective based on Cartographic line work is more effective based on

lineslines–– Labeling should be based on polygons using MaplexLabeling should be based on polygons using Maplex

•• Labeling based on sizeLabeling based on size–– Large Areas: using boundary placement option Large Areas: using boundary placement option –– Small Areas: place label inside areaSmall Areas: place label inside area–– Tiny Areas: place label outside and use leader lineTiny Areas: place label outside and use leader line

Slide 23

Boundaries: LabelingBoundaries: Labeling

Slide 24

1:5,000 Map Labeling Parameters for 1:5,000 Map Labeling Parameters for BoundariesBoundaries

•• Large areasLarge areas–– SQL Query: SQL Query: ““[[Shape_AreaShape_Area] > 1500000] > 1500000”” (Units = feet)(Units = feet)–– Boundary Label PlacementBoundary Label Placement–– Make sure Make sure ““May Place Label OutsideMay Place Label Outside…”…” option is option is OffOff–– Stack Labels is Stack Labels is OffOff

•• Small areasSmall areas–– SQL Query: SQL Query: ““[[Shape_AreaShape_Area] > 100000 AND [] > 100000 AND [Shape_AreaShape_Area] < 1500000] < 1500000””

(Units = feet)(Units = feet)–– Horizontal Label PlacementHorizontal Label Placement–– Make sure Make sure ““May Place Label OutsideMay Place Label Outside…”…” option is option is OffOff–– Stack Labels is Stack Labels is OnOn

•• Tiny areasTiny areas–– SQL Query: SQL Query: ““[[Shape_AreaShape_Area] < 100000] < 100000”” (Units = feet)(Units = feet)–– Horizontal Label PlacementHorizontal Label Placement–– Make sure Make sure ““May Place Label OutsideMay Place Label Outside…”…” option is option is OnOn–– Stack labels is Stack labels is OnOn

Slide 25

Producing Boundary LinesProducing Boundary Lines

•• Polygon to Line tool (not Feature to Line)Polygon to Line tool (not Feature to Line)–– Produces lines that are similar in character to what Produces lines that are similar in character to what

the the ArcInfoArcInfo Coverage stored in line feature classesCoverage stored in line feature classes–– Includes left and right FID from the original polygonsIncludes left and right FID from the original polygons

Slide 26

Transportation (1:5,000)Transportation (1:5,000)

•• Centerlines: LabelsCenterlines: Labels•• Curb Lines/Pavement Polygons: Stronger Curb Lines/Pavement Polygons: Stronger

cartographic representation through ~1:30,000cartographic representation through ~1:30,000–– Centerlines still used for labels though lines are not Centerlines still used for labels though lines are not

drawndrawn–– Producing polygons using Feature to Polygon tool is Producing polygons using Feature to Polygon tool is

not perfect and requires some hand editingnot perfect and requires some hand editing•• Would ideally be created when curb lines are capturedWould ideally be created when curb lines are captured•• Susceptible to topological inconsistencies in curb linesSusceptible to topological inconsistencies in curb lines

Slide 27

Transportation: Road PolygonsTransportation: Road Polygons

Slide 28

Transportation: Labeling Streets and Transportation: Labeling Streets and HighwaysHighways

•• For Highway Shield SymbolsFor Highway Shield Symbols–– Use marker symbols based on ESRI Shields fontUse marker symbols based on ESRI Shields font–– Jim MossmanJim Mossman’’s s ddvCoyoteddvCoyote Application for the Application for the

ultimate level of graphical qualityultimate level of graphical quality

Slide 29

Transportation: Labeling Streets and Transportation: Labeling Streets and Highways (1:5,000)Highways (1:5,000)

•• Highways (shields)Highways (shields)–– Placement = HorizontalPlacement = Horizontal–– Repeat Labels ~5,000 ft, Remove Duplicates ~4,000 ftRepeat Labels ~5,000 ft, Remove Duplicates ~4,000 ft

•• Streets (inside street polygons using centerlines)Streets (inside street polygons using centerlines)–– Placement = CurvedPlacement = Curved–– Stacking = No, Street Placement = NoStacking = No, Street Placement = No–– Repeat Labels ~4,000 ft, Remove Duplicates ~1,200 ftRepeat Labels ~4,000 ft, Remove Duplicates ~1,200 ft–– SQL Query: [SQL Query: [Shape_LengthShape_Length] > 120 ] > 120 (units = feet)(units = feet)

•• Street (spurs / Street (spurs / culcul de sacs)de sacs)–– Placement = StraightPlacement = Straight–– Stacking = Yes, Street Placement = No, Overrun = 16 Stacking = Yes, Street Placement = No, Overrun = 16

pts, Font Reduction = Yespts, Font Reduction = Yes–– SQL Query: [SQL Query: [Shape_LengthShape_Length] <= 120 ] <= 120 (units = feet)(units = feet)

Slide 30

Slide 31

Terrain: Elevation Model Data SourcesTerrain: Elevation Model Data Sources

•• 1:5,0001:5,000–– 2m pixel bare earth DEM from LIDAR2m pixel bare earth DEM from LIDAR–– 22--10 foot contour intervals10 foot contour intervals

•• 1:25,0001:25,000–– 10m (1/3 Arc Second) pixel DEM (barely adequate*)10m (1/3 Arc Second) pixel DEM (barely adequate*)–– 1010--50 foot contour intervals50 foot contour intervals

•• 1:100,0001:100,000–– 30m (1 Arc Second) pixel DEM (barely adequate*)30m (1 Arc Second) pixel DEM (barely adequate*)–– 2020--100 foot contour intervals100 foot contour intervals

*Use Bilinear Interpolation *Use Bilinear Interpolation resamplingresampling methodmethod

Slide 32

Raster Layer Interpolation MethodRaster Layer Interpolation Method

Slide 33

Terrain: HillshadingTerrain: Hillshading

•• 1:5,000: 1:5,000: –– Default Hillshade tool works wellDefault Hillshade tool works well

•• 1:25,000: 1:25,000: –– DEM Quality can be an issue* DEM Quality can be an issue* –– Use Cartographic Hillshading techniques**Use Cartographic Hillshading techniques**

•• 1:100,0001:100,000–– DEM QualityDEM Quality……–– Cartographic Hillshading techniques**Cartographic Hillshading techniques**

*Smooth your DEM using: Neighborhood Statistics Tool, *Smooth your DEM using: Neighborhood Statistics Tool, Circle, Mean, r = 6 (henceforth referred to as Circle, Mean, r = 6 (henceforth referred to as ““Smoothed Smoothed DEMDEM””

** http://support.esri.com/data models > base map data ** http://support.esri.com/data models > base map data model > Hillshade toolsmodel > Hillshade tools

Slide 34

LIDARLIDAR--based Hillshade (1:5,000)based Hillshade (1:5,000)

Slide 35

Default HillshadeDefault Hillshade

Slide 36

Default with Tweak 285 Default with Tweak 285 -- 5050

Slide 37

Cartographic Hillshading TechniqueCartographic Hillshading Technique

Slide 38

Terrain: Contour LinesTerrain: Contour Lines

•• There are no USGS contour lines for 1:5,000 There are no USGS contour lines for 1:5,000 mapsmaps

•• Default contours in GIS lackDefault contours in GIS lack–– Supplementary contours (in flat areas)Supplementary contours (in flat areas)–– Carrying contours (in steep areas)Carrying contours (in steep areas)–– Adequate drawing performanceAdequate drawing performance–– Depression contours (more depressions at 1:5,000)Depression contours (more depressions at 1:5,000)–– Index contour identificationIndex contour identification–– Good cartographically placed labelsGood cartographically placed labels

Slide 39

Terrain: Slow Contour LinesTerrain: Slow Contour Lines

•• Use the smoothed DEM from hillshade workUse the smoothed DEM from hillshade work•• Result from Contour Tool is excessively denseResult from Contour Tool is excessively dense

–– Generalize using DouglasGeneralize using Douglas--PeuckerPeucker Advanced mode Advanced mode field calculatorfield calculator

Dim Dim pCurvepCurve as as IPolyCurveIPolyCurveDim Dim pGeompGeom as as IGeometryIGeometryDim pc as IntegerDim pc as IntegerDim i as IntegerDim i as IntegerSet Set pCurvepCurve = [Shape] = [Shape]

if not if not pCurve.isEmptypCurve.isEmpty thenthenpCurve.Generalize(200) pCurve.Generalize(200) ‘‘Generalize method uses DouglasGeneralize method uses Douglas--PeuckerPeucker

end ifend ifSet Set pGeompGeom = = pCurvepCurve

Slide 40

Terrain: Slow Contour LinesTerrain: Slow Contour Lines•• StepsSteps

1.1. Start EditingStart Editing2.2. Zoom in on a portion of an undulating contour lineZoom in on a portion of an undulating contour line3.3. Select it using the Edit Tool Select it using the Edit Tool 4.4. Set the Edit Task to Modify Feature (this will show the vertexesSet the Edit Task to Modify Feature (this will show the vertexes

and youand you’’ll see how densell see how dense5.5. Use the Measure tool to measure the distance (curve radius Use the Measure tool to measure the distance (curve radius

between 3 vertexes you want to use to maintain your shape)between 3 vertexes you want to use to maintain your shape)6.6. Now set your zoom level to be your mapNow set your zoom level to be your map’’s scales scale7.7. Use the above field calculator on the shape field to calculate aUse the above field calculator on the shape field to calculate a

new shape for the selected feature. The number you got from new shape for the selected feature. The number you got from the measure tool is what you should put into the generalize the measure tool is what you should put into the generalize commandcommand’’s parameter (200 is used above). On 25K contours s parameter (200 is used above). On 25K contours when units are Decimal Degrees I used 0.00001, when units when units are Decimal Degrees I used 0.00001, when units are feet, I used 4 feet.are feet, I used 4 feet.

8.8. If itIf it’’s too much, click UNDO and try again until you get a good s too much, click UNDO and try again until you get a good thinning of points without changing your shape (as you donthinning of points without changing your shape (as you don’’t t want topological inconsistencies to arise from this process)want topological inconsistencies to arise from this process)

9.9. Once you find a good radius value stop editing and do not save Once you find a good radius value stop editing and do not save your editsyour edits

10.10. Use the field calculator again on your shape field to generalizeUse the field calculator again on your shape field to generalizeall the shapesall the shapes

Slide 41

Zoom to Area with CurvesZoom to Area with Curves

Slide 42

Isolate Typical Curve to be MaintainedIsolate Typical Curve to be Maintained

Slide 43

Start Editing & Select Contour LineStart Editing & Select Contour Line

Distance for Distance for Generalize MethodGeneralize Method

Slide 44

Calculate Shape FieldCalculate Shape Field

Slide 45

Set Generalization LevelSet Generalization Level

Slide 46

Review ResultReview Result——Undo/Repeat until HappyUndo/Repeat until Happy

Slide 47

Terrain: Contour Line Symbol WidthTerrain: Contour Line Symbol Width

•• Using Smoothed DEMUsing Smoothed DEM–– Create Slope GRID (Use Percent Rise Option)Create Slope GRID (Use Percent Rise Option)–– ReclassReclass Slope Grid into 4 ClassesSlope Grid into 4 Classes

•• < 3,250,000 (flat areas; consider making supplemental contours)< 3,250,000 (flat areas; consider making supplemental contours)•• 3,250,000 3,250,000 -- 15,000,000 (general case)15,000,000 (general case)•• 15,000,000 to 24,000,000 (fairly steep)15,000,000 to 24,000,000 (fairly steep)•• > 24,000,000 (very steep)> 24,000,000 (very steep)

–– Convert reclassified slope to polygonsConvert reclassified slope to polygons–– Use Identity tool with slope polygons on contour linesUse Identity tool with slope polygons on contour lines–– Use the Unique Values multiple fields symbology method, Use the Unique Values multiple fields symbology method,

include your include your ““identityidentity”” field which is effectively the slope category field which is effectively the slope category –– Set the symbol width of the contours in the higher slope Set the symbol width of the contours in the higher slope

categories to be narrower by 20%categories to be narrower by 20%--25% than the neighboring 25% than the neighboring lesser slope categorylesser slope category

Slide 48

Width Narrows in Steeper RegionsWidth Narrows in Steeper Regions

Slide 49

Terrain: Supplemental ContoursTerrain: Supplemental Contours

•• Example: Adding 5Example: Adding 5’’ supplemental contours to a supplemental contours to a contour line data set with a 10contour line data set with a 10’’ contour intervalcontour interval

1.1. Create 10Create 10’’ contour dataset with a base contour of 0 (zero)contour dataset with a base contour of 0 (zero)2.2. Create another contour 10Create another contour 10’’ contour line dataset with a base contour line dataset with a base

contour of 5contour of 53.3. Identity using polygons from previous slide (see Identity using polygons from previous slide (see

supplemental contour line reference)supplemental contour line reference)4.4. Select and delete contour lines whose Select and delete contour lines whose ““identityidentity”” is not in the is not in the

flattest classflattest class5.5. Select and delete short supplemental contours (may need Select and delete short supplemental contours (may need

to use Multipart to to use Multipart to SinglepartSinglepart tool first).tool first).

Slide 50

Supplemental ContoursSupplemental Contours

Slide 51

Terrain: Contour Line LabelingTerrain: Contour Line Labeling

•• Use Maplex with the Street Placement optionUse Maplex with the Street Placement option–– Use Repeat Labels optionUse Repeat Labels option–– Use Remove Duplicates option (75Use Remove Duplicates option (75--80% of distance 80% of distance

specified in Repeat Labels option)specified in Repeat Labels option)•• Create masks: use the Feature Outline Masks Create masks: use the Feature Outline Masks

tool (in Cartography Tools toolbox)tool (in Cartography Tools toolbox)•• Use Masks with Advanced Drawing Options to Use Masks with Advanced Drawing Options to

mask contour lines (right click in TOC on data mask contour lines (right click in TOC on data frame) frame)

Slide 52

Slide 53

Terrain: Index ContoursTerrain: Index Contours

•• Add Short Integer Field called Add Short Integer Field called IndexYNIndexYN•• Calculated usingCalculated using

Dim k As StringDim k As Stringk = Right( k = Right( StrStr( [CONTOUR] ),2 )( [CONTOUR] ),2 )Dim d As IntegerDim d As Integerd = d = val(kval(k))p = d mod 25p = d mod 25if p > 1 then if p > 1 then

p = 0p = 0elseelse

p = 1p = 1endifendif

Slide 54

HydrographyHydrography

NHD Medium ResolutionNHD Medium Resolution1:100,000 to ?1:100,000 to ?

NHD High ResolutionNHD High Resolution1:25,000 to 1:100,0001:25,000 to 1:100,000

Local data captured at ~1:500Local data captured at ~1:5001:1000 1:1000 –– 1:2?,0001:2?,000

DATA SOURCEDATA SOURCESCALE RANGE OF USESCALE RANGE OF USE

•• Lessons LearnedLessons Learned–– At smaller scales, NHD data required finer line At smaller scales, NHD data required finer line

weights too avoid looking unrefined/inappropriateweights too avoid looking unrefined/inappropriate–– Selected subset of larger local scale data with slight Selected subset of larger local scale data with slight

simplification of geometry would be much better at simplification of geometry would be much better at 1:25,000 than the NHD High Resolution1:25,000 than the NHD High Resolution

Slide 55

1:5,000 Hydro 1:5,000 Hydro (matches (matches orthoimageryorthoimagery))

Slide 56

NHD HighNHD High--ResolutionResolution

Slide 57

NHD Medium ResolutionNHD Medium Resolution

Slide 58

Ortho ImageryOrtho Imagery

PRINTED OUTPUT PRINTED OUTPUT RESOLUTIONRESOLUTION

ORTHO IMAGE ORTHO IMAGE RESOLUTIONRESOLUTION

SCALESCALE

600 DPI600 DPI2 Meter Pixel2 Meter Pixel1:100,0001:100,000

300 DPI300 DPI2 Meter Pixel2 Meter Pixel1:250001:25000

600 DPI600 DPI1 Meter Pixel1 Meter Pixel1:250001:25000

600 DPI600 DPI0.3 Meter Pixel0.3 Meter Pixel1:50001:5000

Slide 59

Thank you!Thank you!

http://http://support.esri.com/datamodelssupport.esri.com/datamodels -->>Base Map Data ModelBase Map Data Model