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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.

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Presentation on theme: "GIS & Spatial Analysis in MCH Ravi K. Sharma, PhD Department of Behavioral & Community Health Sciences, Graduate School of Public Health, University of."— Presentation transcript:

1 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

2 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

3 Elements of Spatial Analysis Formulate your question (s). Data requirements based on your question (s) Selection of method (s) Data processing Displaying your results

4 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

5 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

6 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.

7 Data processing using GIS GIS provides the necessary tools for implementing the selected methods.

8 Spatial Public Health/MCH Data Geographic data can be either 1. Discrete 2. Continuous or 3. Aggregated by polygon (area)

9 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

10 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.

11 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.

12 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-discrete spectrum is the ease in defining the feature's boundaries.

13 Representation of Geographic Features Two basic models for representing geographic features are 1) Vector 2) Raster

14 Representing Spatial Elements RASTER VECTOR Real World

15 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)

16 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. Representing Spatial Elements

17 Entity Representations Points - simplest element Lines (arcs) - set of connected points Polygons - set of connected lines We typically represent objects in space as three distinct spatial elements: We use these three spatial elements to represent real world features and attach locational information to them.

18 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!

19 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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21 Properties That Are Distorted Projections tend to distort to the following properties: 1. 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. 2. Distance: A map is equidistant when it portrays distances from the center of the projection to any other place on the map. 3. Direction: A map preserves direction when azimuths (angles from a point on a line to another point) are portrayed correctly in all directions. 4. Scale: Scale is the relationship between a distance portrayed on a map and the same distance on the Earth. 5. 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.

22 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)

23 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.


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