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Horizon DTC Integrator Event

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My part of the slide deck from the Integrator Event for the DTC PhD students, 2 Dec 2009. This includes the additional slides I mentioned on the Modifiable Areal Unit Problem.

My part of the slide deck from the Integrator Event for the DTC PhD students, 2 Dec 2009. This includes the additional slides I mentioned on the Modifiable Areal Unit Problem.

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Transcript

  • 1. Horizon DTC Integrator Day:The Geospatial Industry
    Jeremy Morley,Steven Feldman
    2nd December 2009
  • 2. Purpose
    Scope of the geospatial industry
    Exciting opportunities at the bleeding edge
    Most projects have some geo
    What’s the geography, be it explicit or implicit, in your projects?
  • 3. Programme
    2 – 3pm Isn’t there geo in everything?
    3 – 3.15pm Break
    3.15 – 3.50pm Spatial is special
    3.50 – 4pm Break
    4 – 4:40pm Geofutures (& why spatial isn’t special)
    4.40 – 5pm Wrap-up
  • 4. Your words
  • 5. Geo in 2010(1 hour)
    The industry now
    Geospatial without the degree
    My maps
    GeoCommons
    Google Earth
    Breakout: “where’s the geo in our projects?”
  • 6.
  • 7. Geocommons – screen-scraping university locations to a map
  • 8.
  • 9. mgr = new MarkerManager(map);
    var lat = parseFloat(57.1650804282195);
    varlng = parseFloat(-2.09906504822913);
    var point = new GLatLng(lat,lng);
    array_points[1] = [];
    array_points[1]['point'] = point;
    var html = '<div style="width: 260px; padding-right: 10px"><h3>The University of Aberdeen (A20)</h3>'+
    'University Office<br />' +
    'King's College<br />' +
    'Aberdeen<br />' +
    'AB24 3FX<br />' +
    't: +44 (0) 1224 273504<br />' +
    'e: <a href="mailto:sras@abdn.ac.uk">sras@abdn.ac.uk</a><br />' +
    'w: <a href="http://www.abdn.ac.uk/sras" target="_blank">www.abdn.ac.uk/sras</a><br /><br />' +
    '<a href="/students/choosingcourses/choosinguni/instguide/a/a20">further details</a>';
    array_points[1]['description'] = html;
    array_points[1]['region'] = '11';
    array_points[1]['name'] = 'The University of Aberdeen';
    array_points[1]['code'] = 'A20’;
    Javascript source for map, showing one university’s record. We can use the fixed structure to extract the information we want.
  • 10. BEGIN {
    print "name, latitude, longitude” }
    match($0,"lat =") {
    i = match($0 , "[)]" )
    lat = substr($0,22,i-22); }
    match($0,"lng =") {
    i = match($0 , "[)]" )
    lng = substr($0,22,i-22); }
    {
    i = match($0,"/H3>") + match($0,"</h3>")
    if( i > 0 ) {
    j = match($0,"<H3>") + match($0,"<h3>")
    name = substr($0,j+4,i-(j+4))
    gsub(",","-",name)
    printf "%s, %s, %s ",""" name """, lat, lng
    }
    }
    Unix ‘awk’ script to extract and format the text
  • 11. name, latitude, longitude
    "The University of Aberdeen (A20)", 57.1650804282195, -2.09906504822913
    "University of Abertay Dundee (A30)", 56.4634, -2.9726
    "Aberystwyth University (A40)", 52.4147760680295, -4.08403520146778
    "ALRA (The Academy of Live and Recorded Arts) (A42)", 51.4551, -0.1730
    "Accrington & Rossendale College (A44)", 53.7549, -2.3714
    "The College of Agriculture- Food and Rural Enterprise (A45)", 54.6986, -6.2152
    "American InterContinental University - London (A50)", 51.5188, -0.1516
    "Anglia Ruskin University (A60)", 51.7412476988799, 0.474334439742583
    "Anglo European College of Chiropractic (A65)", 50.7262, -1.8243
    "Askham Bryan College (A70)", 53.9110, -1.1053
    "Aston University- Birmingham (A80)", 52.4860, -1.8895
    Comma-separated variables file, ready for import into Geocommons
  • 12. Breakout session –“Where’s the geo in our projects?”
    Four groups
    15mins to work as a group to find geographic dependencies, and analysis, in your projects
    20mins: each group has 5mins to give examples of their geographic content
  • 13. Your words
    Marketing Communications
    recontextualized
    social networks and virtual worlds
    web 2.0 technologies for public engagement and activism
    ways people divide up and structure information
    interactive handheld guide
    innovative solutions in the transport sector
    spatial cognition
    learning with technology
    environmental sensors and location-aware technology
  • 14. Your words
  • 15. Reporting
  • 16. Break!
  • 17. Spatial is special
  • 18. “How to lie with maps”
    1 – change the map units
  • 19. Political context
    Gerrymandering: adjusting political units to favour particular party
    See: http://www.redistrictinggame.org
  • 20. The Modifiable Areal Unit Problem
    'the areal units (zonal objects) used in many geographical studies are arbitrary, modifiable, and subject to the whims and fancies of whoever is doing, or did, the aggregating."(Openshaw, 1984 p.3)
    Openshaw and Taylor's (1979):The results of statistical analysis of data for spatial zones can be varied at will by changing the zonal boundaries.
  • 21. Types of MAUP
    Scale effect
    The variation in numerical results that occurs due to the number of zones used in analysis.
    E.g. tendency towards smoother statistics with larger aggregation areas
    Zoning effect (Gerrymandering)
    The variation induced by the choice of units in which to collect data, or to aggregate to.
    Ecological Fallacy
    The error in thinking that the results of an aggregated area can be uniquely distributed to constituent parts
  • 22. “How to lie with maps”
    2 – extensive versus intensive
  • 23. Examples
    Some examples here - taken from the work of Dr. Jason Dykes and Prof. David Unwin.
    Part of Project Argus
    Using data from the 1991 Population Census for Leicestershire, UK
    187 wards of varying size and character
    http://www.agocg.ac.uk/sosci/casestudies/dykes/dykes.pdf
  • 24. Example – total population
  • 25. Example – population density
  • 26. Types of values
    We can divide polygon attributes into two types:
    Spatially intensive
    True possibly for any part of the area (if the area is homogeneous), e.g. densities, rates, proportions
    A field value, averaged over the area
    Spatially extensive
    True only for the entire area, e.g. total population
    Integration (summation) of the field over the area
    Usually misleading – convert to intensive/normalised
  • 27. “How to lie with maps”
    3 – change the colouring
  • 28. Choice of classification is critical
    Equal intervals
    Quantile
  • 29. Example (from ESRI) – where are the kids?
  • 30. Spatial is special
    Be careful with spatial reasoning
    Be careful with map presentation
    Spatial also special in data structure
    Spatial representations:
    Points / lines /polygons (e.g. road map)
    Topological relationships (e.g. adjacency)
    Continuous fields (e.g. temperature)
  • 31. Break!
  • 32. Geofutures
    Geo in 2015
  • 33.
  • 34. Generating ideas
    Some thinking time (20 mins)
    What’s the geo problem I’d like solved?, or
    How does this stuff change my research focus?
    Or, what’s the geo data I need and don’t have?
    Reporting:
    How does this fit my research direction?
    Could this be part of my feasibility project?
    Or, what outside interest might incorporate geo ?
    ACTION: what do I need to do next?
  • 35. GeoVation Awards Program
    £21,000 to promote and support innovation for social, economic and environmental benefit through the use of geography
    https://challenge.geovation.org.uk/
  • 36. Purpose
    Scope of the geospatial industry
    Exciting opportunities at the bleeding edge
    Most projects have some geo
    What’s the geography, be it explicit or implicit, in your projects?
  • 37. Wrap-up
    What have you learnt?
    Feedback: has this helped?
  • 38. Further Examples – zoning effects
    "How to Lie with Maps" by Mark Monmonier(see Chapter 9 (first edition))
    Number of televisions
    Number of households
  • 39. Televisions per household
  • 40. Aggregation
    Number of TVs
    Number of h'holds
    TVs per h'hold
  • 41. Aggregation (2)
    Number of TVs
    Number of h'holds
    TVs per h'hold
  • 42. Aggregation (3)
    Number of TVs
    Number of h'holds
    TVs per h'hold
  • 43. Further examples – ecological fallacy
    Number of TVs
    Number of h'holds
    TVs per h'hold
    What’s the pattern in the original cells?
  • 44. A consistent disaggregation
    Number of TVs
    Number of h'holds
  • 45. Ecological Fallacy
    Number of TVs
    Number of h'holds
  • 46. Ecological Fallacy
    Number of TVs
    Number of h'holds
    TVs per h'hold
  • 47. Ecological Fallacy
    Same aggregated trend from different fine-scale detail.