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Spatial Analysis & Dissemination of Census Data

Learn about spatial analysis techniques and database structures for disseminating census data. Explore examples and tools for querying, buffering, and analyzing spatial relationships.

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Spatial Analysis & Dissemination of Census Data

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  1. Spatial Analysis & Dissemination of Census Data United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  2. Outline • Geographic Database • Spatial Analysis Techniques • Examples United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  3. Geographic Database • Geographical features (Conceptual Model) • Components selection • Attributes • Structure • Spatial Relationships (explicit -Topolgy) United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  4. Spatial relationships United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010 • Logical connections between spatial objects represented by points, lines and polygons • e.g., - point-in-polygon - line-line - polygon-polygon

  5. Spatial Operations United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010 “adjacent to” “connected to” “near to” “intersects with” “within” “overlaps” etc.

  6. Spatial Analysis Techniques • the main use of spatial analysis is for census products and services • Techniques include: queries, distance measurements, buffering, linear interpolation, point pattern analysis, and cartograms, etc. • All offer functionality beyond standard thematic (choropleth) mapping, with many tools now available in both commercial and open-source software programs. United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  7. Spatial Analysis: Query United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010 • select features by their attributes: • “find all districts with literacy rates < 60%” • select features by geographic relationships • “find all family planning clinics within this district” • combined attributes/geographic queries • “find all villages within 10km of a health facility that have high child mortality” Query operations are based on the SQL (Structured Query Language) concept

  8. Examples: What is at…? Features that meet a set of criteria United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  9. “is nearest to” • Point/point • Which family planning clinic is closest to the village? • Point/line • Which road is nearest to the village • Same with other combinations of spatial features United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  10. “is near to”: Buffer Operations • Point buffer • Affected area around a Hospital • Catchment area of a water source United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  11. “is near to”: Buffer Operations • Point buffer • Affected area around a polluting facility • Catchment area of a water source United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  12. Buffer Operations • Line buffer • How many people live near the polluted river? • What is the area impacted by highway noise? United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  13. Buffer Operations • Polygon buffer • Area around a reservoir where development should not be permitted United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  14. Spatial Analysis Techniques • point-in-polygonanalysis • Determines whether a point lies inside or outside a polygon. • Can be used to compare geo-coded village centroids lying inside and outside hazardous areas such as tropical storm tracks or earthquake zones. • Polygon overlayanalysis • Involves comparison between the locations of two different polygonal data layers. • For example, the boundaries of two administrative districts could be compared to troubleshoot errors in the field enumeration process United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  15. “ is within”: point in polygon • Which of the cholera cases are within the containment area United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  16. Solution: “Point-in-Polygon” operation will identify for each point the EA area into which it falls and will attach the census data to the attribute record of that survey point. Problem: We may have a set of point coordinates representing clusters from a demographic survey and we would like to combine the survey information with data from the census that is available by enumeration areas. United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  17. Spatial aggregation United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010 • Example of Spatial aggregation: • fusion of many provinces constituting an economic region

  18. Spatial data transformation: interpolation Example 1: Based on a set of station precipitation surface estimates, we can create a raster surface that shows rainfall in the entire region 13.5 20.1 26.0 27.2 12.7 15.9 24.5 26.1 United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  19. Example of linear interpolation creating contours United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  20. Thiessen polygons illustrated Spatial Analysis Techniques • Thiessen polygons • Have the unique property that each polygon contains only one input point (e.g. settlements), and any location within a polygon is closer to its associated point than to the point of any other polygon. • This method assumes that the values of the unsampled data are equivalent to those of the sampled points. United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  21. Areas of influence • Commuting distances: daily commuters flow United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  22. Modeling/Geoprocessing United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010 • modeling: identify or predict a process that has created or will create a certain spatial pattern • diffusion: how is the epidemic spreading in the province? • interaction: where do people migrate to? • what-if scenarios: if the dam is built, how many people will be displaced?

  23. Modelling: smoothing • Evolution of the population beetwen two censuses United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  24. Spatial Analysis Techniques • Cartograms • sometimes used to display census results • The areas of the original polygons are expanded or contracted based on their attribute values such as population size or voting habits United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  25. Location-allocation problems • Site selection • Optimal allocation • Multicriteria Analysis United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

  26. THANK YOU! United Nations Regional Seminar on Census Data Dissemination and Spatial Analysis Nairobi, Kenya, 14-17 September, 2010

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