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Geographic Information Systems (GIS)in Environmental StudiesENVS 6189 3.0 – Winter 2003Session III

John Sorrell

York Universitysorrell@yorku.ca

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Session PurposeSession Purpose::

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To discuss the various concepts of space, the dominant data types, themes and models used to represent and organize geographic information.

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Cognitive RepresentationCognitive Representationof Spaceof Space::

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Humans have many conceptualization of space. A few include:

• Figural Space• Vista Space• Environmental Space• Geographic Space

Existing GIS is concerned largely with Geographic Space

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The Nature of The Nature of Geographic DataGeographic Data::

For effective use in a computer environment, geographic data entities have the following characteristics:

GIS in Environmental Studies

1) Geographic Position:a location specified in a unique way (where is it).

2) Attributes:non-spatial descriptions of the feature (what is it).

3) Spatial Relationships:selected relationships among features explicitly defined (what’s around it)

4) Time:referring to a point or period in time as defined in real

world or database time-units (when is it).

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Descriptions of Geographic Descriptions of Geographic Data Organization:Data Organization:

Spatial Organization:• Disaggregated Data – Individuals or Single Entities;• Aggregated Data – Mass observations defined by criterion.

Temporal Organization:• Cross-Sectional –data in a single time period;• Longitudinal – one discrete are over a series of observation periods.

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Spatiotemporal Relationship:• Geometric Transformation – spatial change of

location, and/or properties of object (TSA).• Very complex in a database when recorded changes

effect location, attributes and relation to other objects .

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Geographic Data Geographic Data Themes:Themes:

Social-Economic Data:

Information about humans, their activitiesand the spaces/structures used;

Examples: • Land Registry Data, Municipal By-law maps, Demographics, Retail Activity, Transportation Networks.

Sources: Government – Private Database - Field Surveys;

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Considerations/Constraints: Cost, Quality, Format, Time.

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Data Themes Data Themes (cont’d):(cont’d):

Natural/Environmental Data:

Information about the natural or built environment.

Sources: Government – Private Database - Field & Lab Work;

Considerations/Constraints: Cost, Quality, Format, Time.

Characteristics:

- comparatively more static than human data;- mapping unit and scale may smaller scaled;- most effective when merged with human data.

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Modeling the Real Modeling the Real World:World:

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Data Model: A logical construct for organizing data in an information system.

Real World

User view level

Exact Object

Database level

Graphic Mode level

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Spatial Data Spatial Data Models:Models:

Data Structure: A logical and physical mean for digitally encoding geo-spatial data.

A. study area

B. raster representation C. vector representation

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Characteristics of Characteristics of the Raster Data the Raster Data Model:Model:

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Cell value

Spatialresolution

Coordinate Referenceof end of point

Coordinate Referenceof start of point

Different attributesstored in different layers

Pixel

Spatial unit

Column no.Row no.

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Raster Data Model:Raster Data Model:Representation of Data

in Raster FormatData Layerin Map Form Overlay Analysis

Forest Types

Soil Types

Topography

Forest Types

Soil Types

Topography

Analysis ResultsStudy Area

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Vector Data Model:Vector Data Model:(Arc(Arc--Node Topological Node Topological data model)data model)

Topology: a branch of math that defines spatial relationships between features and their properties in elastic space.

Triangulated Irregular Network (TIN)

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The Vector Data Model The Vector Data Model –– Spatial Spatial Representations:Representations:

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Vector Layers

Vector map

Actual terrain

forest

drainage area

drainage lines

drainage point

highway layer

•

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Geographic Data Geographic Data Types:Types:

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Vector (Point, Line Vector (Point, Line Polygon)Polygon)

Raster Raster (Images)(Images)

3D3D

CADCAD

Raster Raster (Surface)(Surface)

TabularTabular

GI Data uses wide variety of data types GI Data uses wide variety of data types and Forms:and Forms:

Geo-referenced data (features):Geo-referenced data forms the locations and shapes of map features such as buildings, streets, or cities. This data intrinsically includes location as a key variable (x,y) .

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“Combined Spatial Layers”

interrelated datapowerful analysis toolseasily understood and presentable co-relationslink data through common geography

Zoning

Topography

AdministrativeBoundaries

Statistical Data

Central Offices

Road Networkand Addresses

ClientsCombined Data ModelsCombined Data Modelsand Thematic Layers:and Thematic Layers:

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ComparisonComparisonof Raster & of Raster & Vector Model:Vector Model:

Advantages:1. It provides a more compact data

structure than the raster model.2. It provides efficient encoding of

topology, and, as a result, more efficient implementation of operations that require topological information, such as network.

3. The vector model is better suited to supporting graphics that closely approximate hand-drawn maps.

Advantages:1. It is a simple data structure.2. Overlay operations are easily and

efficiently implemented;3. High spatial variability is

efficiently more efficient represented in a raster format

4. The raster format is more or less required for efficient manipulation and enhancement of digital images.

Disadvantages:

1. The raster data structure is less compact.

2. Topological relationships are more difficult to implement.

3. The output of graphics is less aesthetically pleasing because boundaries tend to have a block appearance.

RASTER MODEL

Disadvantages:

1. It is a more complex data structure than a simple raster format.

2. Overlay operations are more difficult to implement.

3. The representation of high spatial variability is inefficient.

4. Manipulation and enhancement of digital images cannot be effectively done in a vector domain.

VECTOR MODEL

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