Geography 38:376 Intro GIS

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Geography 38376Intro GIS

• Topic 6
• Exploratory Data Analysis
• Chang Chapter 11
• (DeMers Chapters 7 8)

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GIS Data Analysis

• Vast majority of time and invested in
  development of GIS is for data input and mgmt
• In many cases, GIS is not used beyond storage,
  management, and retrieval of spatial data
• Essentially an automated mapping system
• Power of GIS is ability to perform spatial
  analysis

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GIS Data Analysis

• Analytical power of GIS is often supplemented by
  integrating 3rd party tools
• geo-statistical packages
• surface and subsurface modeling
• image analysis software
• hydrological analysis
• etc.

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Exploratory Data Analysis

• GIS is very useful for identifying
• Patterns - arrangement
• Trends - variations in distribution
• Associations - common occurrence
• Relationships - causal occurrence
• . . . between spatially distributed
  phenomena
• First step in spatial analysis is to determine
  WHAT IS WHERE?
• Next step is to determine WHY

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Exploratory Data Analysis

• GIS provide a variety of tools for exploring
  spatial data
• Geographic Visualization
• Descriptive Statistics
• Graphs and Charts
• Query by Attribute
• Query by Location

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Geographic Visualization

• Like maps, GIS facilitate geographic
  visualization
• use of maps for processing spatial data
• identifying spatial relationships
• BUT, GIS also enable us to
• Combine compare hundreds of data layers
• Easily edit the symbolization of features
• Explore various thematic map types
• Adjust the classification scheme used to
  represent data
• 3-D perspective views

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Descriptive Statistics

• Used to explore attributes of geographic features
• Mean
• Median
• Mode
• Range
• Standard Deviation
• Etc.
• . . . which can then be used to symbolize features

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Graphs and Charts

• Pie Charts
• Bar Charts
• Scatter Plots
• Line Charts
• Histograms
• Variograms
• Cumulative Frequency Graphs
• . . . in some cases dynamically linked to the map
  display (and/or in multiple linked views)

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Query (by Attribute or Location)

• Fundamental analytical function, v. powerful
• Based on user-defined criteria
• Defines subset of features
• Selected set can be mapped, graphed, reported, or
  saved as a new data layer
• Queries can be based on
• Aspatial criteria
• Spatial criteria
• or both
• . . . we can follow the string in both
  directions

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Query by Attribute

• Based on the aspatial characteristics of features
  
• E.g. select all host towns with Canad Inn hotels
• Selection by
• Mouse pick records
• Wizard build simple or compound queries
• SQL command type at command prompt
• Used to answer Show me where? questions
• Query the table, follow string to map (where?)

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Query by Attribute

• Query expressions
• Can use relational operators
• gt , ? , lt , ? , , ?
• Boolean logic (connectors for compound queries)
• AND
• OR
• XOR
• NOT
• And wildcards with LIKE
• Parentheses define order of operation

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NOT
OR
AND
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Query by Location

• Based on unique geographic location of features
• E.g. select all host towns adjacent to Hwy 1
• Selection by
• Mouse point and click on features
• Graphic click and drag a box or circle of
  radius
• Spatial relationship within a distance of,
  point in poly, line in poly, etc.
• Used to answer Show me what? questions
• Query map, follow string to table (what?)

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Query by Location

• Mouse
• Tolerance or search radius in pixels

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Query by Location

• Graphics
• Completely within
• Completely or partly within
• Or graphic is completely within

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Query by Location

• Spatial (i.e. topological) relationships
• Select features from one or more layers that
• Intersect
• Are within a distance of
• Completely contain
• Are completely within
• Have their center in
• Share a line segment with
• Touch the boundary of
• Are identical to
• Are crossed by the outline of
• Contain
• Are contained by
• . . . the features of the same or other layers

• Containment
• Intersection
• Proximity/Adjacency

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Query by Attribute or Location

• Queries can be used to
• Create a new selection
• Add to selection
• Remove from selection
• Select from selection (a subset)

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Compound Queries

• Combining multiple query expressions
• Can be performed in a
• Stepwise fashion (narrow down results)
• Using compound expression boolean logic
• E.g. select host town
• with pop65 gt 15 AND
• accommodations gt 350 rooms OR
• Num sheets gt 20

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Raster Data Query

• When we query vector data we select records based
  on one or more attribute values
• Elevation of point feature is an attribute value
• When we query a raster data set we identify
  pixels that meet some criteria
• Elevation of a raster is the cell value

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Raster Data Query

• Use relational operators and boolean logic to
  identify pixels that satisfy expression
• Result is not a selection of records
• Result is output boolean or binary raster
• Cell value 1 yes, criteria satisfied
• Cell value 0 no, criteria not satisfied

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AND
OR
OR
OR
NOT
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