ADVANCED CARTOGRAPHYLecture delivered at BMS College of Engineering

Course – Advanced GISNovember 27,2011

Dr S NatarajanProfessor and Key Resource Person

Department of Information Science and EngineeringPES Institute of Technology

Bangalore

ADVANCED CARTOGRAPHY

• Labels• Map Making• Metadata file

Feb 18, 2000

Map Design

• A map is useless unless it is read• People will read and study attractive,

informative maps• It takes time to create a good map or you

need a template that you can use over and over

• Analyze other people’s and groups’ maps

Feb 18, 2000

Map Design

• Keep the map as clear as possible– Make it easy to read

• Make the map as legible as possible– Make it easy to understand

• Use a hierarchical structure for your maps– Show most important information first in

legend– Attention span is inversely proportional to the

weight on a person’s feet

Feb 18, 2000

Map Design

• Use appropriate patterns– Limestone– Sandstone– Make it easy to distinguish adjacent patterns

not

or

Definitelynot

Feb 18, 2000

Map Design

• Use appropriate and consistent line weights

Appropriate

ConsistentAppropriate

Inconsistent and

inappropriate

Feb 18, 2000

Map Design

• Use different sizes of the same symbol to indicate relative values, e.g., – number of superfund sites in a city– value of property

<10 10-100 >100<$100K

<$500K

>$500K

Feb 18, 2000

Map Design

• Use a good color scheme– Use colors that are familiar to users– Do not use bright colors without the good

reason

Feb 18, 2000

Clarity and Legibility

• Use appropriate graphical elements to delineate between map features– Use contrasting colors to distinguish features– Use lines to seperate features– Use patterns that are easy to distinguish

Feb 18, 2000

Visual Contrast

• Is defined as the crispness or sharpness of the distinction between map symbols

• Use different size symbols• Use primary colors, which contrast more

with each other than with other colors• Don’t take contrast to excess, keep your

maps from looking ‘busy’

Feb 18, 2000

Visual Balance

• Is the relative weight of the basic graphic components and shapes in a map– Components of a map = title, legend,

explanatory text, photographs, north arrow, scale

• Use organizational standard for technical maps, e.g. USGS, city

Feb 18, 2000

Hierarchical Structure

• Differentiate between broad classes or types of information in the map

• Help the reader focus on specific themes from several that may be shown

Feb 18, 2000

Thematic MapsUSGS Geologic maps use standard colors for rock types and ages, use a recent published USGS map to color code your maps

Color code the map according to the age of the rocks

Use shades of the same color for rock units with the same age designation

Geologic Map of the U.S.

Feb 18, 2000

Map Posters• Layer text and photos on maps• Place text at right angles in complementary

color• Keep it simple

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ADVANCED CARTOGRAPHY

Three label placement categories Point labelling Line labelling Area labellingLabelling complexity• The point labelling problem is proven to be

NP-complete

Example

Eduard Imhof (1895-1986)

- Swiss Cartographer- “Positioning Names on

Maps” (1962/1975)

Rules according to Imhof

Problematic cases

Problem visibility highway 20

Problem association Thunder Bay and point

Problem readability name

Another problematic case

University Ave. is interrupted 4 times

Specific rules point labels• Label must be close to point,

preferably to right and above• Labels are placed horizontal,

no extra spacing• No overlap with other labels,

except perhaps in the spacing of the areal label

• Label may intersect line feature; then line must be interrupted

• Points at a large body of water must have their label in the water. In other cases there may be no line between a point and its label

• If it cannot be avoided, a name may be split over two lines of text

Specific rules line labels• Label must follow shape of river• Label should not bend upwards

and downwards consecutively• At long line features the label

must be repeated• No or little extra spacing

between characters, spacing between words of the label is allowed

• For vertical line features: upward reading direction left on the map and downward right on the map

• Contour lines: labels must interrupt contour line; top of label points to higher regions

Specific rules areal labels• Horizontal labeling is good unless

this conflicts with the dominant shape of the region

• Non-horizontal labels must be curved

• Monotonous curving; no inflection points

• Label should be spread over whole region

• Adjacent regions preferably have same shape of label (both horizontal, e.g.)

• Sometimes an areal label may be outside its region, but not in another labeled region

• Small areal features treated as point features

Strategies for automatic label placement

• Compute for each feature various candidate positions according to the rules

• Choose for each feature one candidate position, such that the chosen positions do not overlap

• Sometimes a feature cannot be labeled, and sometimes the label of a feature must be repeated

Reasons for removal

Utrecht

Utrecht

Utrecht

Utrecht

UtrechtZeist

Zeist

Readability text

Visibility features

Association

Utrecht

poor

good

Choosing from the candidates

• Translate to a graph problem (graph G):- each candidate position of each feature is a node in G- two nodes have an edge in G if their candidate positions intersect- two nodes have an edge in G if their candidate positions are of the same feature

Computing intersecting candidates

• Each candidate is (approximately) a simple geometric shape

• Determine all pairs of intersecting candidates using a plane sweep algorithm

• O((n+k) log n) time, with k the number of intersecting pairs

• Typically: k = O(n)

Label Placement-- IntroductionRule-based algorithms• Best computer algorithms are those that emulate an experienced human cartographer

Experienced cartographer repeats road names several times for long roads

Cartographers work based on accepted conventions and rules and they place labels in order of

importance - For example, New York City, Vienna, Berlin, Paris, or Tokyo must show up on country

maps because they are high-priority labels

Once those are placed, the cartographer places the next most important class of

labels, for example major roads, rivers, and other large cities

In every step they ensure that

(1) the text is placed in a way that the reader easily associates it with the feature,

and

(2) the label does not overlap with those already placed on the map.

Other algorithms• The simplest greedy algorithm places consecutive labels on the map in positions that result in

minimal overlap of labels • Its results are not satisfactory even for very simple problems, but it is extremely fast

Slightly more complex algorithms rely on local optimization to reach a local optimum of a placement

evaluation function -- in each iteration placement of a single label is moved to another position,

and if it improves the result the move is preserved.

It performs reasonably well for maps that are not too densely labelled

Slightly more complex variations try moving 2 or more labels at the

same time. The algorithm ends after reaching some local optimum

Label Placement-- Introduction• The algorithm that yields good results with relatively good performance –

 simulated annealing - is very simple.

It works like local optimization, but it may keep a change even if it worsens the result.

The chance of keeping such a change is  , where ΔE is the change in the evaluation function, T is the temperature

When the temperature is high, simulated annealing performs almost random changes to the label placement, being able to escape a local optimum

Later, when hopefully a very good local optimum has been found, it behaves in a manner similar to local optimization

Another class of direct search algorithms are the various evolutionary algorithms,

e.g. genetic algorithms

If a map labeling problem can be reduced to a situation in which each remaining label has only two potential positions in which it can be placed then it may be solved efficiently by using an instance of 2-satisfiability

Algorithms for Label Placement

Most familiar algorithms• Random placement• Exhaustive search algorithms• Greedy algorithms• Local search algorithms• Tabu search• Stochastic search (Simulated annealing)• Overlap vectors• Mathematical programming• Genetic algorithms

29

Label Placement Rules

• Area features

• Point features

• Line features

Label placement most difficult

Label placement least constrained

30

Label Placement Quality Metrics

• Aesthetics

• Label visibility

• Feature visibility

• Association

R i ve r

R i v e r

City City

ATownBTown

ATown

BTown

PeakPeak Peak

Based on Van Dijk et al. (1999)

31

Label Placement Quality Metrics

• Aesthetics 5 of 20 papers reviewed

• Label visibility 20

• Feature visibility 10

• Association 11

32

Automating Label Placement

• Area features

• Point features

• Line features

Label placement most difficult

Label placement least constrained

Frequent research target for label placement automation

33

Automating Label Placement

• Area features

• Point feature label placement

• Line features

models

algorithms

34

Automated Point Feature Label Placement Models

1

3

2

4

Discrete label position priorities: Yoeli (1972)

6 5

8

7

Slider model: Van Kreveld et al. (1999)

Continuous circumferential movement: Hirsch (1982), Kameda & Imai (2003)

35

Automated Point Feature Label Placement Algorithms

Local Search

Global Optimization

36

Automated Point Feature Label Placement Algorithms

Local Search• Rule-based exhaustive search• Gradient descent

Global Optimization• Force-directed• Simulated annealing

37

Exhaustive Search

Rule

Rule

Rule

…

• Place labels according to rules until violation• Backtrack and adjust to maximize number of labels

placed

x

Local Search Algorithms

Exhaustive Search: Freeman & Ahn (1984, 1987); Jones (1989), Cook & Jones (1990); Doerschler & Freeman (1992)Rule-based, with backtracking (place labels until overplot occurs, backtrack and adjust). Practical only for small problems (e.g. 50 points features per Christensen et al 1995)

38

Local Search Algorithms

• Develop initial label placement• Compute overlap vectors to guide

next movement• Iterate From Hirsch (1982), p. 13

Gradient Descent

Gradient Descent: Hirsch (1982) After an initial, trial placement, choose from available operations (label movements) that which provides most immediate improvement. Iterate. Tends to cycle around local minima without being able to escape and find overall optimum labeling

39

Local Search Algorithms

• Develop initial label placement• Compute overlap vectors to guide

next movement• Iterate• Can cycle between

local minima (a) and (b)

without finding

preferred placement (c)

From Christensen et al. (1995), p. 213

(a) (b)

(c)

From Hirsch (1982), p. 13

Gradient Descent

40

Automated Point Feature Label Placement Algorithms

Local Search• Rule-based exhaustive search• Gradient descent

Global Optimization• Force-directed• Simulated annealing

41

From Stadler et al. (2006), p. 211

Global Optimization Algorithms

Force-Directed

Force-Directed: Uses repulsive forces between labels, to prevent placement of labels close to one another. Ebner et al. (2003); Stadler et al. (2006) Simulated annealing as a follow-up can result in near-optimal label placement, and relatively fast solutions to large problems

42

Global Optimization Algorithms

Based on Zoraster (1997) and Christensen et al. (1995)

Simulated Annealing

43

Automated Label Placement Software

Yoelipriorities

Slidermodels

Simulatedannealing

Iteration andbacktracking

Optimization

Imhof (and others’)labeling rules

Force-directedmethods

Label / featurevisibility

Association

Aesthetics

9.2

ADVANCED CARTOGRAPHY

• Labels• Map Making• Metadata file

What is a map?

• A generalized view of an area, usually some portion of Earth’s surface, as seen from above at a greatly reduced size

• Any geographical image of the environment• A two-dimensional representation of the

spatial distribution of selected phenomena

Why make maps?

• To represent a larger area than we can see• To show a phenomenon or process we can’t

see with our eyes• To present information concisely• To show spatial relationships

Represent a larger area

Show what we

can’t see

Present info concisely

Show spatial relationships

How do we read maps?

• Maps are selective views of reality• Size of the map relative to reality (scale)• What’s on the map (symbolization)• Shape of the map (projection)

Map scale

• Ratio of the distance on the map to the distance on the ground

• Scale is a fraction• Larger area covered means larger

denominator• Larger denominator means smaller fraction• So a large-scale map covers a small area

Large-scale

Small-scale

Map scale

• Ratio of the distance on the map to the distance on the ground

1. Graphic:

• Stays the same when photocopied• Might not be right for the whole map

Map scale

2. Verbal:

1 inch equals 10 miles

• Easy to understand• Can change if photocopied

Map scale

3. Representative fraction or ratio:

1:24,000

• Units don’t matter• Can change if photocopied

Map symbolization

• Symbols are a code instead of text• Three kinds: point, line, area• Consider shape, size, orientation, pattern,

color, value

Point symbols

• Every symbol counts as one occurrence• Qualitative points

– Indicate location– Can also describe that location

• Quantitative points– Show a distribution– Indicate a value (graduated symbols)

Indicate locationDescribe location

Show a distribution

Indicate a value

Line symbols

• One-dimensional• Mostly taken for granted (borders, roads)• Isolines connect same values• Flow-line maps indicate value by width of

line

Isolines(Contour

lines)

Flow-line maps

Area symbols

• Each territory or region has one value• Differences in kind• Differences in value

– Choropleth maps – Usually, darker indicates more

• Cartograms distort area to show value

Differences in kind

Differences in kind

Differences in value(Choropleth)

ADVANCED CARTOGRAPHY

• Labels• Map Making• Metadata file

Why Metadata?

Metadata makes spatial information more useful to all types of users by Making it easier to document and locate data sets.

The growing availability of data of all kinds from many different sources has helped GIS technology become more useful and widely adopted

With metadata support, data producers can publish information about data, and data consumers can search for the data they need.

Why Metadata? (Cont…) Spatial data is important for GIS- it is important to

know if the data will meet user’s needs Data users need metadata to locate appropriate data

sets Metadata provides information about the data

available within an organization or from Catalog services Clearinghouses Other external sources

Metadata not only helps find data, but once data has been found, it also tells how to interpret and use data

Publishing metadata facilitates data sharing Sharing data between organizations stimulates

cooperation and a coordinated, integrated approach to spatially related policy issues.

Metadata and GIS Management From a data management perspective, metadata is

important for maintaining an organization's investment in spatial data

Metadata benefits an organization in the following ways: Provides an inventory of data assets Helps determine and maintain the value of data Helps you determine the reliability and currency of data Supports decision making Documents legal issues Helps keep data accurate and helps verify accuracy to

support good decision making and cost savings Helps determine budgets because it provides a clearer

understanding of when or if data needs to be updated or repurchased

What is Metadata? Metadata is a summary document providing

Content Quality Type Creation Spatial information about a data set

It can be stored in any format: Text file Extensible Markup Language (XML) database record

Metadata is more easily shareable (Small size) By creating metadata and sharing it with others, information about

existing data becomes readily available to anyone seeking it Metadata makes data discovery easier and reduces data duplication ESRI stores metadata with the data set it details and may additionally

index metadata in a central database for sharing ESRI software uses the XML standard for metadata processing.

Metadata Standards

In United States, FGDC (Federal Geographic Data Committee) Content Standard for Digital Geospatial MetadataPublished in 1998.

The International Organization for Standardization has also created a spatial metadata standard-- ISO

ESRI Supported Metadata For both the FGDC and

ISO standards, ESRI provides a set of tools. A metadata editor Style sheets that present

the metadata in various report formats

A synchronizer that automatically records a data set's properties in the appropriate metadata elements for that standard

ESRI Supported Metadata Metadata services are built on the functionality of

three existing ESRI products. The ArcGIS ArcCatalog™ application is used for

creating and authoring metadata and sending to a metadata service.

ArcIMS and ArcSDE™ ArcIMS hosts the metadata service ArcSDE is the interface to the relational database that

stores metadata documents. ArcCatalog, Metadata Explorer, Web browsers, or

Z39.50 clients can access metadata stored in a metadata service.

Authoring Metadata ArcCatalog automatically captures some core

metadata and updates metadata automatically when possible, e.g. spatial extent and coordinate system can be automatically supplied. ArcCatalog automatically attaches metadata to the data set to ensure

integrity ArcCatalog will fill in as much information as it can using the data's

properties when the data changes

ArcCatalog can send data to the ArcIMS metadata service, which requires at least the following metadata items: Title Publisher Spatial extent Data theme Content type

Supported Data Types ArcGIS has been designed to create metadata for any data

set supported/created by ArcGIS as well as any other data set identified and cataloged by the user (e.g., text, CAD files, scripts). Supported data sets include the following:

MapsWorkspaces Folders Layers NFO™ tables dBASE® tables DBMS tables Projections Text files Programming scripts

ArcInfo™ coverages ESRI shapefiles CAD drawings Images GRIDs TINs PC ARC/INFO® coverages ArcSDE geodatabases Personal ArcSDE

Publishing Metadata

The ArcIMS metadata service makes metadata created with ArcCatalog available on the Internet.

The ArcIMS metadata service uses an ArcSDE database as the repository into which all published metadata documents are stored.

Digital Communication Standards ESRI software creates metadata in XML format XML is a metamarkup language

but unlike HTML, it describes structured data content rather than display properties

XML is an open industry standard: platform neutral and oriented to publishing and distributing information through Internet

Any metadata published in valid XML will be accepted by any metadata service.

Z39.50 is an open, well-established communications protocol for information sharing on wide area networks Clients and servers can send and receive requests and responses

using the Z39.50 protocol. The FGDC uses Z39.50 to implement the NSDI

Clearinghouse, which enables searches for spatial data over the Internet.