Introductory course to GIS

Introduction to GIS

Overview course content

Introduction to GIS

1Basics of GIS2
2Spatial data4
3Spatial reference systems3
4Spatial data basic analysis3
5Data visualization2

Overview course content

Introduction to GIS

Learning outcomes:

  • Understand the basic concepts of Geographic Information Systems
  • Define terms related to raster and vector data models
  • Compare vector and raster data models
  • Understand the difference between geographic and projected coordinate systems
  • Select spatial objects using attribute and spatial queries
  • Perform simple analysis with geoprocessing tools
  • List map elements and basic principles of map creation
  • Create a thematic map using different methods of symbolization

1 | Basics of GIS

Introduction to GIS

#Content
1.1What is GIS?
1.2Uses of GIS

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1.1 | What is GIS?

Fig.GIS

GIS definition


Geographic Information System (GIS)

"is a computer system capable of capturing, storing, analyzing, and displaying geographically referenced information; that is, data identified according to location. Practitioners also define a GIS as including the procedures, operating personnel, and spatial data that go into the system."

USGS (United States Geological Survey)

"is a computer-based tool for mapping and analyzing things that exist and events that happen on earth. GIS technology integrates common database operations such as query and statistical analysis with the unique visualization and geographic analysis benefits offered by maps."

ESRI

The spatial (geographic) part differentiates a GIS from a standard computer database.

GIS components


A GIS consists of five key components: hardware, software, data, people, and methods.


Fig.Hardware Fig.Software Fig.Data Fig.People Fig.Methodes_Tools

GIS: main idea


Fig.GIS_Schema

The main goal of GIS is to provide spatial information to decision makers.

Data vs. Information


Data means simply facts or figures - pieces of information, but not information itself.

Data is collected and stored in databases. When data are processed, interpreted, organized, structured or presented so as to make them meaningful or useful, they are called information. Information provides context for data.

In a GIS, spatial analysis and modelling are the main source of information.

Spatial analysis - a set of methods and tools for performing operations on spatial data in order to obtain additional information.

1.2 | Uses of GIS

Software

Geospatial software and tools:

  • Desktop GIS (QGIS, SAGA GIS, GRASS GIS, ILWIS, IDRISI, Esri products: ArcGIS, ArcMap, ArcGlobe, GeoMedia, MapInfo, Bentley Systems: MicroStation, ENVI, ERDAS IMAGINE)
  • GIS as a service (ArcGIS Online, Mapbox, OpenStreetMap, Google Maps, Apple Maps, Here Maps, Bing Maps)
  • Spatial database management systems (MySQL, Oracle Spatial, Microsoft SQL Server, PostgreSQL)
  • Map servers (Geoserver, MapServer, Mapnik)


Fig.QGIS Fig.Software

Fields of GIS usage

Fig.GIS_example
  • urban planning
  • environment protection and management
  • land use monitoring
  • agriculture
  • transportation/logistics
  • emergency management
  • network infrastructure management
  • tourism
  • ...

Advantages of GIS


  • Ability to view, visualize and interpret data in the form of maps, charts and reports - relationhips and trends easy to see and understand
  • Improved decision making and problems solving through specific and detailed information regarding locations of features and phenomena
  • Reduce costs and increase efficiency
  • Improved communication between organisations or departments

2 | Spatial data

Introduction to GIS

#Content
2.1Definition and properties
2.2Vector data model
2.3Raster data model
2.4Comparing vector and raster data models

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2.1 | Definition and properties

From real world...

Fig.RealWorld

... to GIS

Fig.RealWorld_representation

Spatial data - definition


Spatial object means an abstract representation of a real-world phenomenon related to a specific location or geographical area.

Spatial data means any data with a direct or indirect reference to a specific location or geographical area.

Spatial data set means an identifiable collection of spatial data.

DIRECTIVE 2007/2/EC of the European Parliament ad of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE)

Data model


Data model is a set of guidelines to convert the real world (called entity) to the digitally and logically represented spatial objects consisting of the attributes and geometry.

The attributes are managed by thematic or semantic structure while the geometry is represented by geometric-topological structure.

Shunji, 1999

Spatial data - properties

Spatial data describes shape, location, spatial relationships and attributes of features related to the Earth's surface.

Fig.Spatial_data

Spatial data (representation) model

Two common spatial data models:

VECTOR

Fig.Data_vector

RASTER

Fig.Data_raster

2.2 | Vector data model

Three types of geometry

A vector data model defines discrete objects such as fire hydrants, rivers, lakes.

A vector data models divided into three basic types:

Fig.Types_of_geometry

All three of these types of vector data are composed of coordinates and attributes attached to the geometry.

Geometry: points

Fig.Geometry_points
  • 0-dimension objects
  • represented by a single pair of coordinates (X,Y)
  • associated attribute information is attached to the center of the point
  • used to represent objects with no length or area (e.g. light poles, trees) or
  • used to represent a geographic feature too small to be displayed as a line or area (e.g. the location of a city on a small-scale map)
  • symbolized by a point or other sygnature (symbol) in different sizes and colors

Geometry: lines

Fig.Geometry_lines
  • 1-dimension objects
  • defined by an ordered set of two or more coordinate pairs called vertices
  • used to model linear features with no area (e.g. county boundary lines) or
  • used to represent the shape of geographic features too narrow to be displayed as an area at the given scale (e.g. contours, street centrelines, streams)
  • symbolized by different types of line that have a color, width and style (solid, dashed, dotted, etc. ...)

Geometry: polygons

Fig.Geometry_polygons
  • 2-dimension objects
  • composed of three or more connected lines where the start and end point have the same coordinate
  • attribute information is attached to the center of the polygon
  • used to represent areas (e.g. lakes, forests, cities)
  • represent length and area, embody the idea of an inside and an outside

Geometry: spaghetti vs. topological model

Fig.Model_spaghetti_topology
  • easy to implement
  • duplicate data
  • difficult modeling topological relations
    		•
  • easy to modify (update)
  • defined topological relationships
    		•

    Topology

    Topology is required to determine spatial relationships between objects in a GIS.

    If the features are deformed (e.g. through projections or datum transformations), some properties change: area, shape, direction, distance, relative proximities.

    Other properties (topological properties) remain constant after distortion: adjacency, containment, connectivity.

    Benefits of topology:

    • storing data more effeciently
    • ensuring data quality
    • facilitating advanced spatial analysis (e.g. network analysis)

    Topology


    Fig.Topology

    Three examples of properties that remain constant after deformation

    Attribute table

    An attribute is a nonspatial information about a geographic feature in a GIS, usually stored in a table and linked to the feature by a unique identifier (ID).

    A database or tabular file containing information about a set of geographic features, usually arranged so that:

    • each row represents a feature
    • each column represents one feature attribute.

    The attribute values can be used to find, query, analyze and symbolize features.

    		 Fig.Attribute_table

    Attribute table - data types

    Each column in the database may contain different type of data.

    Fig.Attr_tab_data_types

    Basic data types:

    • NUMERIC: INTEGER (long int, short int) - numbers, code list
    • NUMERIC: FLOAT (double, real) - floating-point numbers
    • STRING (char, varchar, text) - names and other texts
    • DATE/TIME (date, time, year, timestamp) - data and/or time
    • BOOLEAN (0/1, true/false, yes/no) - logical expression
    • BLOB - multimedia files

    Vector data sources


    Fig.GPS Fig.Coordinates Fig.Vector_tools Fig.Database Fig.Map_topo

    Vector data sources

    (A - GPS measurements, B - list of coordinates, C - digitizing and conversion tools e.g. raster to vector, D, E - existing databases)

    Vector file formats

    • ESRI Shapefile - the most common geospatial file type developed by ESRI, consists of:
      • shp (feature geometry)
      • shx (shape index position)
      • dbf (attribute data)
      • prj (projection system metadata)
      • xml (associated metadata)
    • GML (Geography Markup Language) - XML based open standard for GIS data exchange
    • KML/KMZ (Google Keyhole Markup Language) - XML based open standard for GIS data exchange
    • GPX (GPS eXchange Format) - GPS data file
    • GeoJSON (Geographic JavaScript Object Notation) - a lightweight format based on JSON, used by many open source GIS packages

    2.3 | Raster data model

    Raster data model

    A raster data model defines continous data and phenomena.

    Raster's are:

  • digital aerial photographs and satellites imagery (spectral data),
  • continuous data represents phenomena - e.g. temperature, precipitation, elevation, slope,
  • digital pictures, scanned maps and plans.
    • Fig.Orto

    Raster data model: geometry

    A raster consists of a matrix of cells (or pixels) organized into rows and columns (or a grid) where each cell contains one value representing information such as temperature, elevation, or spectral data.

    Pixel - smallest visible element of an image.

    Grid - 2-D object feature that represents a single element of a continous surface.

    		 Fig.Raster_geometry

    Raster data model: georeferencing

    Cells are identified by their positions in the grid.

    Raster data is georeferenced by:

  • real world coordinates of the reference point,
  • cell size in real world distance,
  • using the upper-left or lower-left corner of grid as the reference point.
    		•  Fig.Raster_geometry

    Spatial resolution

    Fig.Resolution The same feature in images of different resolution

    A spatial resolution refers to the dimension of the cell size representing the area covered on the ground. Higher resolution means better feature quality but it means also bigger raster file size.

    Raster bands


    A raster dataset contains one or more layers called bands.

    A band is represented by a single matrix of cell values.

    For example, a digital elevation model (DEM) is a single-band raster (has one band holding elevation values) while satellite imagery is a multispectral image and has multiple bands.

    Three main ways to display single-band raster datasets:

  • binary image (each cell has a value of 0 or 1 and is often displayed using black and white),
  • grayscale image (each cell has a value from 0 to another number, such as 255),
  • color image (a set of values is coded to match a defined set of red, green, and blue (RGB) values).

    • Raster bands

    Fig.Raster_bands

    Three ways to display raster dataset (binary image, grayscale image and color image)

    Attribute table


    Raster data can also have attributes only if pixels are represented using a small set of unique integer values. Raster datasets that contain attribute tables typically have cell values that represent or define a class, group, category, or membership.

    In raster datasets, each row of an attribute table corresponds to a certain zone of cells having the same value.

    The attribute tables can be used to analyze datasets and symbolize raster cells.

    Note: Not all GIS raster data formats can store attribute information.

    Attribute table

    Fig.Raster_attribute_table

    An example of raster dataset with attribute table

    Raster data sources


    Fig.Ortophoto Fig.Satellite Fig.DEM Fig.Maps Fig.Raster_tools
    Raster data model sources

    (A - orthophoto, B - satellite imagery, C - DEM, D - scanned maps and plans, E - conversion and analysis tools e.g. vector to raster, interpolation)

    Raster file formats

    • GeoTIFF - TIFF variant enriched with GIS relevant metadata, may be accompanied by other files:
      • tfw (raster geolocation)
      • xml (metadata)
      • aux (projections and other information)
      • ovr (pyramid files improves performance for raster display)
    • IMG - ERDAS IMAGINE image file format
    • ESRI Grid - format developed by Esri, which has two varieties: binary or ASCII

    2.4 | Comparing vector and raster data models

    Comparing: vector vs. raster data model


    propertiesvectorraster
    depictdiscrete featurescontinous data
    geometrycoordinatescells organized into a grid
    attributesattribute table (with many attributes)cell value (only one attribute)
    analysisgeoprocessingmap algebra, overlays
    data structuremore complexmore simple
    sizecompact data structure – little storage spacegreater storage needed
    file formatsESRI Shapefile, GML, KML, geoJSON, GPXgeoTIFF, IMG, grid

    Which one is better?

    Fig.Comparing_vector_raster_1

    Which one is better?

    Fig.Comparing_vector_raster_2

    3 | Spatial reference systems

    Introduction to GIS

    #Content
    3.1Definition
    3.2Geographic Coordinate System
    3.3Projected Coordinate System

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    3.1 | Definition

    What is spatial reference?


    A spatial reference describes where features are located in the real world. It is a key component of spatial data and applications, and differentiates a GIS from a standard databases.

    A spatial reference system (SRS) or coordinate reference system (CRS) is a coordinate-based local, regional or global system used to locate geographical entities.

    Eiffel Tower - where is it?

    Fig.Eiffel_Tower

    Champ de Mars, 5 Avenue Anatole France, 75007 Paris, France

    48° 51' 29.1348''N; 2° 17' 40.8984''E = 48.858093; 2.294694

    448256.00 m E; 5411928.00 m N

    Types of coordinate systems used in a GIS


    Two common types of coordinate systems used in a GIS:

  • Geographical coordinate systems (GCS) – a global or spherical coordinate system based on latitude and longitude coordinates.

  • Projected coordinate systems (PCS) – such as Universal Transverse Mercator (UTM), provide different ways to project maps of the Earth’s spherical surface into a two-dimensional Cartesian coordinate plane.

    • Coordinate systems (both geographic and projected) provide a framework for defining real-world locations.

    3.2 | Geographic Coordinate System

    Geographic Coordinate System

    A geographic coordinate system is a reference system for identifying locations on the curved surface of the earth. Locations on the earth’s surface are measured in angular units from the center of the earth relative to two planes: the plane defined by the equator and the plane defined by the prime meridian (which crosses Greenwich England). A location is therefore defined by two values: a latitudinal value and a longitudinal value.

    Fig.Latitude_and_Longitude

    Latitude and Longitude (Wikimedia Commons)

    Geographic Coordinate System

    • The latitude of a point on the Earth’s surface is the angle between the equatorial plane and a line that passes through that point and is normal to the surface.

    • The longitude of a point on the Earth’s surface is the angle from a reference meridian to another meridian that passes through that point.
    		 Fig.Latitude_Longitude_relationship

    Latitude and Longitude - relationships
    (Wikimedia Commons)

    Geographic Coordinate Systems can only be used to measure angles, not distances or areas.

    3.3 | Projected Coordinate System

    Projection

    Projection is a method by which the curved surface of the Earth is portrayed on a flat surface. This requires a systematic mathematical transformation of the Earth’s graticule of lines of longitude and latitude onto a plane. All projection types can be aggregated into three groups: planar, cylindrical and conical.

    Fig.Projection

    The idea of projection - mapping the Earth on a flat surface

    In a projected coordinate system, locations are identified by X, Y coordinates on a grid.

    Unlike a geographic coordinate system, a projected coordinate system can be used to measure distances and areas.

    Planar projection

    Fig.Projection_planar

    A planar projection maps the Earth's surface to a flat surface (QGIS Documentation)

  • A planar (azimuthal) projection maps the Earth surface features to a flat surface that touches the Earth’s surface at a point or along a line of tangency.
  • This projection is often used in mapping polar regions but can be used for any location on the Earth’s surface.

    • Planar projection types

    Planar projections can be of three different types:

  • polar (using either north or south pole)
  • equatorial (using a point somewhere on the equator)
  • oblique (using any other point)
    • Fig.Projection_aspects

    Three different types of planar projection (polar, equatorial, oblique)

    Cylindrical projection

    Fig.Projection_cylindrical

    A cylindrical projection maps the Earth's surface to a flat surface (QGIS Documentation)

  • A cylindrical projection maps the Earth surface onto a map rolled into a cylinder (which can then be flattened into a plane).
  • The cylinder can be tangent to the equator or it can be oblique.
  • This is a popular projection used in defining the Universal Transverse Mercator (UTM).

    • Conical projection

    Fig.Projection_conical

    A conical projection maps the Earth's surface to a flat surface (QGIS Documentation)

  • A conical projection maps the Earth surface onto a map rolled into a cone.
  • Conical projections are popular PCS’ in European maps (e.g. Europe Albers Equal Area Conic and Europe Lambert Conformal Conic).

    • EPSG code


    The EPSG codes are 4-5 digit numbers that represent coordinate reference system definitions.

    Most geographic information systems use EPSG codes as Spatial Reference System Identifiers (SRIDs) and EPSG definition data for identifying projections and performing transformations between these systems.

    Common EPSG codes:

    • EPSG:4258 - ETRS89 (European Terrestrial Reference System 1989), geodetic coordinate system for Europe
    • EPSG:4326 - WGS 84, latitude/longitude coordinate system based on the Earth's center of mass, used by the Global Positioning System among others
    • EPSG:3857 - Web Mercator projection used for display by many web-based mapping tools, including Google Maps and OpenStreetMap

    4 | Basic analysis of spatial data

    Introduction to GIS

    #Content
    4.1Attribute query
    4.2Spatial query
    4.3Geoprocessing

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    4.1 | Attribute query

    Attribute query - definition

    Query is a request to select features or records from a database. Often written as a statement or logical expression.

    Attribute query is the process of searching and retrieving records of features in a database based on desired attribute values.

    Fig.Attribute_query

    Attribute query

    Typically, attribute query is performed using a criteria-based query language, most commonly SQL.

    SQL (eng. Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS).

    In most cases, the desired information can be given as a set of criteria based on the available attributes. These criteria are formatted in the appropriate query language as a Boolean expression, which can be validated as either true or false for each record in the database.

    Individual criteria can be constructed and combined using:

    • logical operators such as comparisons (>, <, =, >=, <=),
    • Boolean algebra (and, or, not),
    • functions (sin, cos, sqrt, etc.).

    Where? How many? Which one? Whose?

    Fig.Attribute_query
    • Where is Mr. Black's house located?
    • Which buildings are smaller than 150 m2?
    • Where are the buildings owned by Evans family located?
    • How many houses belonging to Mr. Smith are located on the Bell Street?
    • Whose buildings are located on the Homer Street?
    • How many buildings on the Lisson Street are bigger than 100 m2?
    • ...

    How to create an attribute query?

    An attribute query consists of three basic elements: attribute field, operator, and attribute value.

    1 element of the query is ALWAYS:

    SELECT * FROM "name of field" WHERE operator 'value'

    Examples:

  • All buildings owned by Mr. Smith: "owner" = 'Smith'
  • All buildings smaller than 100 m2: "area" < 100

    • Several elements of the query can be combined with operators: OR and AND.

    Simple queries - operators


    LIKE - search for a specified pattern in a column

  • "owner" LIKE 'Jones'
  • "owner" LIKE 'J%'

    • BETWEEN ... AND ... - select values within a given range (concerns numbers, text, or dates)

  • "area" BETWEEN 50 AND 100

    • IN (..., ...) - specify multiple values

  • "street" IN ('Bell St.', 'Homer St.')

    • IS (NOT) NULL - test for (non)empty values

  • "owner" IS NULL

    • Complex query - operator OR

    OR - result of query contains features which have one or another attribute value

    Fig.Attribute_query_OR

    "owner" = 'Smith' OR "owner" = 'Jones'

    Complex query - operator AND

    AND - result of query contains features which have two attributes at the same time

    Fig.Attribute_query_AND

    "owner" = 'Smith' AND "street" = 'Lisson St.'

    Complex queries

    Fig.Complex_attribute_query_1 Fig.Complex_attribute_query_2

    ("owner" = 'Evans' OR "owner" = 'Smith') AND "street" = 'Lisson St.'

    "owner" = 'Evans' OR ("owner" = 'Smith' AND "street" = 'Lisson St.')

    4.2 | Spatial query

    Spatial query - definition

    Query is a request to select features or records from a database. Often written as a statement or logical expression.

    Spatial query is the process of searching and retrieving records of features in a database based on location or spatial relationship.

    Fig.Spatial_query

    Basic spatial relations

    Spatial relationships between objects:

  • disjont
  • overlaps
  • intersects
  • touches
  • equals
  • contains
  • within

    • Theoretical example: different spatial relations between objects A (buildings) and objects B (landslides)

    		 Fig.Spatial_query_operators

    Operator: disjoint

    Select: buildings located outside of the landslide

    Spatial relation: objects A and B do not have any common space


    Result of request: 17 buildings

    		 Fig.Operator_disjoint

    Operator: overlaps

    Select: buildings located partially within the landslide

    Spatial relation: objects A and B overlap partially, but are not completely contained by each other


    Result of request: 4 buildings

    		 Fig.Operator_overlaps

    Operator: intersects

    Select: buildings located either fully or partially within the landslide

    Spatial relation: objects A and B share any portion of space


    Result of request: 11 buildings

    		 Fig.Operator_intersects

    Operator: contains

    Select: buildings containing the landslide (theoretical case)

    Spatial relation: objects A contain objects B within their boundaries


    Result of request: 2 buildings

    		 Fig.Operator_contains

    Operator: within

    Select: buildings located fully within the landslide

    Spatial relation: objects A are completely inside objects B


    Result of request: 5 buildings

    		 Fig.Operator_within

    Operator: touches

    Select: buildings touching the border of the landslide

    Spatial relation: objects A and B have at least one point in common, but their interiors do not intersect


    Result of request: 1 building

    		 Fig.Operator_touches

    Operator: equals

    Select: buildings with the same geometry as the landslide (theoretical case)

    Spatial relation: objects A and B have strictly equal geometries


    Result of request: 1 building

    		 Fig.Operator_equals

    4.3 | Geoprocessing

    Buffer

    A buffer is a zone around a map feature measured in units of distance or time.

    A buffer is useful for proximity analysis.

    Fig.Buffer

    Buffer tool and its parameters

    Clip and Intersect

    Fig.Clip_intersect

    Dissolve and Merge

    Fig.dissolve_merge

    Union and Erase

    Fig.union_erase

    5 | Data visualization

    Introduction to GIS

    #Content
    5.1Data visualization
    5.2Creating maps

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    5.1 | Data visualization

    Data visualization


    Data visualization is the graphic representation of data.

    Spatial data is usually presented in the form of maps. There are many different types of maps to show different types of information.

    In a GIS, one of the most common types of maps are thematic maps that can represent a variety of information including climate, vegetation, population, and many others.

    Main ways to represent spatial data

    A single vector layer can be represented in different ways.

    A GIS software provides many different methods of symbolization, e.g.:

    • single symbol
    • unique values
    • graduated colors
    • graduated symbols
    • charts
    • dot density
    • heat map

    You can also set other layer display properties such as:

    • transparency (0-100%),
    • labels: names of objects (e.g. names of rivers, streets) and numbers,
    • display scale.

    Single symbol

    Single symbol applies the same symbol to all features in a layer. This method of symbology is used for representing a layer with only one category.

    Properties of symbol according geometry types:

  • point: shape, color, size, angle, halo
  • line: color, line width, line style
  • polygon: color, shape fill, outline color, outline width
    		•  Fig.Single_symbology

    Unique values

    Unique values symbolize qualitative categories of values. Unique value symbology can be based on one or more attribute fields in the dataset, or you can write an expression to generate values on which to symbolize.

    Fig.Unique_values

    Graduated colors

    Graduated colors symbology is used to show a quantitative differences in features by varying the color of symbols. Data is classified into ranges that are each assigned a different color to represent the range.

    Fig.Graduated_color

    An example of graduated color map

    Graduated symbols

    Graduated symbols symbology is used to show a quantitative differences in features by varying the size of symbols. Data is classified into ranges that are each assigned a symbol size to represent the range.

    Fig.Graduated_symbols

    An example of graduated symbol map

    Chart

    A chart is a type of statistical graphic that represents data.

    Chart symbology show quantitative differences between attributes, with each part of the chart representing an attribute value that contributes to the overall whole set of values.

    Fig.Chart_map

    An example of chart map

    5.2 | Creating maps

    Map-making step by step


    • Content (select layers: turn on/turn off the relevant layers, add missing thematic layers, rename layers)
    • Symbology (choose the method of data visualization, add labels)
    • View setting (determine the scale of map content display, adjust the extent of the map window)
    • Map composition (create a new project in the print layout, compose a thematic map by adding elements such as map frame, legend, scale etc.)
    • Print (set printout parameters, save print project)

    Map elements

    A map can be composed of many different map elements.

    They may include:

    • main map body
    • inset or location map(s)
    • legend - a visual explanation of the symbols used on the map
    • title - a subject of the map
    • map scale - the ratio of a distance on the map to the corresponding distance on the ground
    • orientation indicator - the relationship between the directions on the map and the corresponding compass directions in reality (e.g. north arrow, graticule)
    • map source and additional information (text, graphic, data source, credits, authors, etc.)

    Map

    Fig.Map

    Basic principles of map creation (1/2)


    • Balance involves the organization of the map and other elements on the page. The various parts of a map layout should be distributed in a way that their weight is centered around the visual center of the map. Four types of balance: symmetrical, asymmetrical, radial and mosaic.

    • Legibility is the ability to be seen and understood. Legibility depends on good decision-making for selecting symbols and choosing sizes so that the results are easily seen and understood.

    • Clarity is the ease of recognition of map elements.

    Basic principles of map creation (2/2)


    • Visual contrast relates how map features and page elements contrast with each other and their background.

    • Figure-ground organization on the map is distinction between one or more objects of interest in the foreground (figure) and the remainder of the map (the ground). Using figure-ground contrast is an effective method to focus the map reader's attention on the most important elements of the map.

    • Hierarchal organization is to "separate meaningful characteristics and to portray likenesses, differences, and interrelationships" (Robinson, et al,. 1995). The internal graphic structuring of the map (and the page layout) is fundamental to helping people read your map.

    Thank you for your attention!


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