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GIS 2 Census Data Analysis

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Title: GIS 2 Census Data Analysis


1
GIS 2 Census Data Analysis
2
Census Data
  • Nationally collected census data provides an
    extensive list of social indicators that can
    provide valuable information. Some examples of
    social data that could be brought into a GIS are
  • Population age breakdowns
  • Minimum education levels
  • Education levels
  • Percent indigenous population
  • Percent separated/divorced families
  • Dependency ratio
  • Percent public housing
  • Percent households suffering financial stress

3
Economic Data
  • Economic variables and activities are important
    considerations for the planning process, and are
    usually given undue priority over environmental
    and social considerations. Some examples of
    economic data that could be brought into a GIS
    are
  • Occupational characteristics
  • Industry employment characteristics
  • Workforce participation rates
  • Unemployment rates
  • Percent of labourers and related workers
  • Income distribution rates
  • Office/retail floor space

4
Examples of Environmental Datasets
  • Forests, national parks, and timber reserves
  • Geology
  • Terrain topography
  • Soils
  • Lakes, rivers, and creeks
  • Water catchments
  • Marine parks
  • Wildlife and fish habitat areas
  • Vegetation
  • Climate data (rainfall)

5
Census Data
  • Like social data, economic data can be collected
    through national censuses. The data is then
    linked to aggregated spatial units (for example,
    collector districts or local government authority
    boundaries) and used to produce thematic maps
  • ABS Census is a comprehensive database (32
    themes) to meet variety of requirements. Some
    understanding of social practices/customs is
    required to make best use of data.

6
Example - Family Types
Families
One parentfamily
Couple onlyfamilies
Two parent families
Other families
Parent and dependent children
Couple and dependent children
Parent and non- dependent children
Couple and non-dependent children
Parent, dependent and non- dependent children
Couple and dependent and non- dependent
children
7
Example - Housing Types
  • Separate houses are self-contained dwellings with
    access on all sides (at least one half metre).
    They include houses that have an attached flat.
  • Semi-detached, row or terrace houses, or
    townhouses are dwellings with their own private
    grounds and no dwelling above or below. They are
    attached in some structural way to, or separated
    by less than one half metre from, one or more
    neighbouring dwellings.
  • Flats, units or apartments include all
    self-contained dwellings in blocks of flats,
    units or apartments that usually share a common
    entrance. They include houses converted into
    flats and flats attached to houses.

8
Classifying Data
  • Often, it is useful to group, or classify, data
    by some attribute to show relationships and
    represent how phenomena are distributed over a
    geographic area. For example
  • Private dwelling occupancy, and unemployment data
    to show their distribution across geographic
    regions (collector districts).
  • Once data is classified, you can create thematic
    maps that show relationships between data and
    geography.
  • The method you use to classify data depends on
    how the data is measured.
  • Measurement types relate to real-world
    quantities. They are the basis for statistical
    analysis and the cartographic symbolization of
    planning data.
  • In general, four empirical scales of measurement
    are used.

9
Method of Classification
  • The method used to classify data depends on how
    the data is measured.
  • Measurement types relate to real-world
    quantities.
  • They are the basis for analysis and the
    cartographic symbolization of data.

10
Qualitative and Quantitative data
  • Qualitative data can be considered nominal or
    ordinal.
  • Nominal data is descriptive (nominal is derived
    from "name") and has no natural order. Nominal
    data maintains an individual set membership.
  • Ordinal data has an associated alphanumeric value
    that allows the data to be ranked or placed in an
    ordered sequence (e.g., first, second, third,
    etc.).
  • Quantitative or numeric, planning data is
    interval or ratio and is related to a real value
    scale. You can subtract values to see how
    different they are numerically.

11
Measurement Type
12
Cartographic Representation
  • The data measurement type determines the
    classification method used for cartographic
    presentation

13
Summarizing Data
  • Summarizing data is an efficient way to learn
    more about it. For example, summarizing
    socio-economic datasets gives you a better
    understanding of the inherent relationships that
    exist between different variables. Summarizing
    data is also useful when working with larger
    geographic areas.
  • For example, if you had a dataset of regional
    boundaries that extended outside the boundaries
    of particular states for which you had population
    attributes, you could use the summarize function
    to find the average population in each region.
  • When you summarize data, you can have ArcGIS
    calculate a number of statistical variables. You
    can then create thematic maps of the data using
    the calculated statistics.

14
Summary Statistics
15
Census Data Analysis at Smaller Areas
16
Land Use, Land Parcel
  • Land use refers to the existing or current use of
    a particular geographical area. Land use can be
    influenced by economic, cultural, political,
    historical, and land tenure factors. Examples of
    land uses are residential development, commercial
    development, parkland, and vacant land etc.
  • For planning purposes, the most common unit used
    to spatially represent a particular land use is
    the land parcel.
  • Each individual land parcel maintains a unique
    identifier called a parcel identification number
    (PID). By accessing a land parcel's PID, the land
    use attributes can be accessed for display and
    analysis purposes.

17
Landuse
18
Example Landuse, Land Parcel
19
Land Parcel
20
Example
21
Landuse
  • Land use has multiple dimensions, including
  • Activities occurring in specific locations
  • Structures housing those activities
  • Characteristics of the land itself
  • For example, a description of the dimensions of a
    particular land parcel currently used as park
    would include both passive and active
    recreational activities that occur there.
    Structures housing these activities might include
    playground equipment, soccer goals, and a grand
    stand. Finally, the characteristics of the land
    could be described as flat grassland surrounded
    by numerous trees, shrubs, and flowerbeds.

22
What is zoning?
  • Each zone is defined within the city plan and
    schematically depicted within the planning
    scheme. Some examples of planning zones that
    could be included in a city planning scheme are
  • Urban Residential
  • Park Residential
  • Non-Urban
  • Active Open Space
  • Environmental Open Space

23
What is zoning?
  • Zoning is a practice usually undertaken to
    designate preferred land use for a particular
    town or city. Each zone (suburb for example)
    comprises a number of land parcels designated as
    having the same future urban land use.
  • These land parcels may or may not have existing
    structures and associated activities. Vacant land
    parcels within the zones are considered
    potentially developable.
  • Zones that divide a city into different areas of
    preferred development constitute the city
    planning scheme, an important component of any
    city's governing planning document.

24
How do land use and zoning relate to each other?
  • Land use focuses on the current activities and
    structures found on a land parcel, while zoning
    focuses on the preferred future use of land.
  • Each land parcel can be assigned particular land
    use and zoning attributes. With this attribute
    data, GIS can be used to compare and contrast the
    existing and preferred future use of land within
    an urban area. The results of such analyses can
    be displayed as maps or tables.
  • Land parcels with different land uses may in fact
    be zoned the same.

25
Exam Questions
  • Describe qualitative and quantitative data types
    and the methods of measuring these data types?
    Give examples of qualitative and quantitative
    data you have used in this course.
  • Describe different types of classification
    methods used for cartographic presentation
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