GIS

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GIS Spatial Analysis in MCH

• Ravi K. Sharma, PhD
• Department of Behavioral Community Health
  Sciences,
• Graduate School of Public Health,
• University of Pittsburgh,
• Pittsburgh, Pa 15261

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What is Spatial Analysis?

• Various methods of looking geographic patterns in
  your data and the relationship between features
• The actual methods used can simple (such as
  making a map) or complex (such as creating a
  spatial data model combining multiple data layers

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Elements of Spatial Analysis

• Formulate your question (s).
• Data requirements based on your question (s)
• Selection of method (s)
• Data processing
• Displaying your results

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Formulate your question (s).

• Start your analysis by asking what you need to
  know? Be specific. This could be question such
  as How many women of childbearing age live
  within two mile radius of a TRI site? Is there a
  childhood leukemia cluster in my county? What
  neighborhood (s) in my county has significantly
  higher death rate from breast cancer? What do
  you know about levels of exposure in relation to
  distance from the TRI site?
• Specificity? analysis ? Methods ?Presentation

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Data requirements based on your question (s)

• Type of data feature ? Methods selected
• Type of feature and attribute data available or
  that you can get or create
• Data creation refers to calculation of new values
  based on existed data or obtaining new layers

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Selection of method (s)

• Decision will be guided by the (1) question for
  which you seek answer (2) availability depth of
  data (3) processing time effort (4) precision
  of results (5) how the results are going to be
  applied?
• E.G. If you are looking at patterns of mortality
  you might decide to simply map the mortality
  rates on the other hand if a particular
  industrial plant in being charged with causing a
  particular disease in a community, you might need
  more precise and detailed data.

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Data processing using GIS

• GIS provides the necessary tools for implementing
  the selected methods.

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Spatial Public Health/MCH Data

• Geographic data can be either
• Discrete
• Continuous or
• Aggregated by polygon (area)

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Discrete features

• Discrete data are geographic features for which
  actual locations can be specified. A feature is
  either present or absent at any given spot. A
  discrete object has known and definable
  boundaries. It is easy to define precisely where
  the object begins and ends

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Continuous features

• Continuous data, or a continuous surface,
  represents phenomena where each location on the
  surface is a measure of the concentration level
  or its relationship from a fixed point in space
  or from an emitting source.
• Continuous data is also referred to as field,
  nondiscrete, or surface data.
• One type of continuous surface data is derived
  from a series of sample points such as ozone
  concentrations measurement from air pollution
  monitoring stations at fixed locations.
• The second type (Progressively varying continuous
  data) of continuous surface data includes
  phenomena that progressively vary as they move
  across a surface from a source.
• One type of movement is through diffusion or any
  other locomotion where the phenomena moves from
  areas with high concentration to areas with less
  concentration until the concentration level evens
  out, such as a oil spill.
• Another type of movement is governed by inherent
  characteristics of the moving item or by the mode
  of locomotion.

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Spatially aggregated features

• Public health/MCH data is usually available as
  summary data for various geographic levels. For
  example counts of immunized children, low births
  weights babies, childhood leukemia case etc by
  census tracts or counties.

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Is your Data Discrete or continuous?

• When representing and modeling many public health
  features, the boundaries are not clearly
  continuous or discrete. If we conceptualized
  consisting of a continuum is created with pure
  discrete at one end and pure continuous features
  at the other end, most features fall somewhere
  between the extremes. The decisive factor for
  where a feature falls on the continuous-to-discret
  e spectrum is the ease in defining the feature's
  boundaries.

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Representation of Geographic Features

• Two basic models for representing geographic
  features are
• Vector
• Raster

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Representing Spatial Elements

• RASTER
• VECTOR
• Real World

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Representing Spatial Elements
Raster
Stores images as rows and columns of numbers with
a Digital Value/Number (DN) for each cell. Units
are usually represented as square grid cells that
are uniform in size.
Data is classified as continuous (such as in an
image), or thematic (where each cell denotes a
feature type. Numerous data formats (TIFF, GIF,
ERDAS.img etc)
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Representing Spatial Elements
Vector
Allows user to specify specific spatial locations
and assumes that geographic space is continuous,
not broken up into discrete grid squares We store
features as sets of X,Y coordinate pairs.
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Entity Representations
We typically represent objects in space as three
distinct spatial elements
Points - simplest element Lines (arcs) - set of
connected points Polygons - set of connected lines
We use these three spatial elements to represent
real world features and attach locational
information to them.
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Two Major Categories of Maps

• Choropleth maps (Greek choros place, plethos
  magnitude)
• Classifies areas into categories based values on
  one or more variables
• Most common method of mapping health data
• Isopleth maps (Greek isos equal)
• Interpolates lines of equal value across the
  spatial surface, independent of administrative
  boundaries
• Examples include weather maps, topographic maps
• Not common in public health . . . But they should
  be!

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Map Projections Coordinate System

• Map projections are attempts to represent the
  surface of the earth or a portion of the earth on
  a flat surface
• Since the earth is a spheroid any attempt to
  flattened it to a plane any attempt to
  represents the earth's surface in two dimensions
  causes distortion in the shape, area, distance,
  or direction of the data.

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Properties That Are Distorted

• Projections tend to distort to the following
  properties
• Conformality Conformal projections preserve
  local shape When the scale of a map at any point
  on the map is the same in any direction, the
  projection is conformal. Meridians (lines of
  longitude) and parallels (lines of latitude)
  intersect at right angles.
• Distance A map is equidistant when it portrays
  distances from the center of the projection to
  any other place on the map.
• Direction A map preserves direction when
  azimuths (angles from a point on a line to
  another point) are portrayed correctly in all
  directions.
• Scale Scale is the relationship between a
  distance portrayed on a map and the same distance
  on the Earth.
• Area When a map portrays areas over the entire
  map so that all mapped areas have the same
  proportional relationship to the areas on the
  Earth that they represent, the map is an
  equal-area map.

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Geographic Coordinate Systems

• A geographic coordinate system is a reference
  system that uses a three-dimensional spherical
  surface to determine locations on the earth.
• A point is referenced by its longitude and
  latitude values.
• Longitude and latitude are angles measured from
  the earth's center to a point on the earth's
  surface. The angles often are measured in degrees
  (or in grads)

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A Geographic Coordinate System
This figures shows a geographic coordinate system
where a location is represented by the
coordinates longitude 80 degree East and latitude
55 degree North.