GIS 2 Census Data Analysis

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GIS 2 Census Data Analysis
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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

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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

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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)

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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.

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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
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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.

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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.

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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.

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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.

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Measurement Type
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Cartographic Representation

• The data measurement type determines the
  classification method used for cartographic
  presentation

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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.

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Summary Statistics
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Census Data Analysis at Smaller Areas
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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.

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Landuse
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Example Landuse, Land Parcel
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Land Parcel
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Example
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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.

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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

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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.

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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.

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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