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CP6514 Lecture 3 Map Representation


Maps are abstractions of reality. Spatial objects in the real world are represented as ... Maps use cartographic objects to represent real world objects ... – PowerPoint PPT presentation

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Title: CP6514 Lecture 3 Map Representation

UST/ENV/PAD/PDD 642/742 Introduction to
Geographic Information Systems
Lecture 3 Spatial Data and Symbology
Basic Cartographic Concepts
Maps are abstractions of reality Spatial
objects in the real world are represented as
points, lines, areas, and surfaces.
Source DeMers, 2005, page 22.
Spatial Measurement Levels
Spatial entities can be represented at the
nominal, ordinal, interval, and ratio levels
Source DeMers, 2005, page 26.
Map Elements and Concept of Scale
  • Three elements of the map scale, projection,
  • symbolization (each element is a source of
  • Scale
  • Real-world objects reduced by representation
  • Scale amount of reduction found in maps
  • Definition of scale the ratio of distance on
    the map to
  • the distance on the earth

Ratio Scale Verbal Scales 19,600
One inch represents 9,600 inches (800
feet). 124,000 One inch represents
24,000 inches (2,000 feet). 150,000
One centimeter represents 50,000 centimeters (500
meters) 1250,000 One inch represent
(approximately) 4 miles 12,000,000 One
centimeter represents 20 kilometers Ex) A scale
of 19,600 is larger (more detail) than a scale
of 150,000
Map Presentation
  • A map is a scale model representation of
  • Cartography is the science of making maps
  • Maps use cartographic objects to represent real
    world objects
  • A GIS map typically combines multiple layers or
    themes of information
  • Each theme has its own set of symbols
  • Care has to be taken to ensure that no
    information is lost when themes are placed in
    some drawing order on a map

Map Basics
  • A map is the primary language of geography
  • A map is a model of spatial phenomena
  • A map is an abstraction of reality
  • Two primary types of maps
  • - General reference maps
  • - Thematic maps
  • A Paradigm shift in cartography
  • - Traditional maps were the final product
  • - GIS maps maintain the raw data for later
  • and flexibility

Science of Map-Making
  • Translating Reality
  • Streets are abstracted and represented using
    line symbols of different weights to delineate
    different real street categories
  • Buildings are abstracted and represented
    using polygon symbols to delineate real
    building footprints
  • Customers are abstracted and represented
    using point symbols to delineate their real
    home locations
  • Each of these is an independent layer or
    theme, and a set of themes along with their
    respective symbologies constitutes a map

Functions of Maps
  • Communication devices in transferring
    information from source to receiver
  • Artifacts reflecting history and culture
  • Graphic presentations
  • Political documents
  • Creators of features like country boundaries
  • Tools

Layers or Themes
  • Presenting Information
  • Maps consist of one or several themes drawn
    in some order
  • The map schematic shown alongside shows
    several themes
  • Each theme represents some set of real world
  • Themes like soils and topography represent
    natural real-world features
  • Themes like political districts, zoning,
    parcels and utilities represent artificial
    real world features
  • Features that have a physical manifestation
    in the real world trees, buildings, fences
    are planimetric and can be seen from
  • Features that are politically or legally
    defined in the real world parcels, counties,
    zoning are cadastral and cannot be seen
    from above, because they have no physical

Metadata Information about the data such as
Description of Files types, storage, formats,
locations, etc. Description of Graphic
Data types, formats, layers, source, accuracy,
dates, precision, projection and coordinates,
shifts, extents, etc. Description of Attribute
Data fields, formats, types, widths, source,
dates, accuracy, currency, etc. Development
Procedures methods, outputs, etc.
Necessary Cartographic Elements
Map Frame area which holds the reduced
representation of real world objects, with sets
of symbolized themes as graphics Title a
descriptive title for the entire map Legend
descriptions of the themes with associated
symbology Annotations labels, numbers, text
strings, etc. that are placed in the map to add
descriptive information about themes or features,
or any other added textual information Scale
verbal, representative fraction or graphic scale
that describes the amount of reduction of the
graphic theme(s) contained in the map
frame(s) North Arrow symbol depicting the
geographic north direction for purposes of viewer
orientation -- can represent cardinal points of
the compass Date map production date placed on
the map in order to determine currency of map
data Author map author name, if clarification is
required about sources, methodology, etc.
Typical Map Layout
Two GIS Formats
Raster Grid-based
Vector Object-based
Vector GIS Basics
  • Vector Data map elements
  • Point features
  • Line features
  • Polygon features
  • Nodes
  • Annotations
  • Features are located using X and Y
  • Data Attributes are linked to features by a
    common field, usually the unique identifier of
    the feature
  • Points -- Single X-Y coordinate pair
  • Lines -- String of X-Y coordinate pairs
  • Polygons -- Closed loop of X-Y coordinate
    pairs, where first and last pair are the same

Vector Cartographic Features
A combination of two numbers X-Y or
Lat-Lon that represent locations with zero
dimensions. Eg. Wells, Crime scenes, Cities,
Electric Poles The shortest distance connecting
two points -- lines have a beginning and an
ending point, and therefore a left and right
side. Eg. Roads, Streams, Pipelines,
Shorelines A set of points or vertices
connected by line segments that close back to the
first vertex. By definition, a polygon cannot
contain intersections. In ArcView, vertices for a
polygon are always in clockwise order, with right
sides of segments as the inside of the
polygon. Eg. Lakes, Building Footprints, Census
Vector Coordinate Location

  • All points are defined in a Cartesian
    coordinate system X and Y location
  • Each point feature is identified uniquely

Vector Data Attributes
  • Each Polygon is a single feature with a unique
    identifier Poly_ID
  • Data attributes are attached to the feature
    through this identifier

Raster GIS
  • Areas are quantized into a uniform grid of
  • Each grid cell represents a limited and finite
    amount of the earths surface -- conceptually, a
    grid cell may be assumed to represent a
    particular location
  • Grid cells are usually square and the same size
  • The larger the grid cell, the larger the land
    area represented, the coarser the data set and
    the lower the resolution
  • Groups of grid cells define particular zones
  • Each grid cell has a single attribute -- its
  • Each type of feature is a separate layer
  • Difficult to represent vector like objects,
    such as parcel boundaries, tracts, etc.
  • Raster is useful representing non-constant or
  • vector like features such as NOX
    concentrations, soils,
  • etc.

Raster GIS Conceptual Presentation
Raster Concepts
  • A pixel is a two-dimensional picture element
    that is
  • the smallest indivisible element of an image
  • Pixels are characterized by aspect ratios

  • A grid is a two-dimensional object feature that
  • represents a single element of a continuous
  • surface
  • Grids are used in raster GIS systems to
    represent areas with changing or imprecise
    attributes, such as soil type boundaries, air
    quality or vegetation types

Raster vs. Vector
Good for point and line features Good for map
entities with multiple attributes Good for
thematic mapping of attributes Uses a relational
database structure Overlay operations can be
somewhat complex
Good for continuous features, such as NOX or
soils Good for comparison and overlay
operations Good for modeling proximity Native
format for aerial photography and remote
sensing Difficulty representing linear features
Example of a Raster Dataset Imagery
Integrating Raster and Vector Data
Example of a Raster Dataset GRID
Population Density Grid (Lower Resolution)
Population Density Grid (Higher Resolution)
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