horizon dtc integrator event
DESCRIPTION
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.TRANSCRIPT
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Horizon DTC Integrator Day:The Geospatial Industry
Jeremy Morley,Steven Feldman
2nd December 2009
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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?
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Programme
2 – 3pm Isn’t there geo in everything?
3 – 3.15pm Break3.15 – 3.50pm Spatial is special3.50 – 4pm Break4 – 4:40pm Geofutures
(& why spatial isn’t special)
4.40 – 5pm Wrap-up
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Your words
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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?”
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Geocommons – screen-scraping university locations to a map
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mgr = new MarkerManager(map);var lat = parseFloat(57.1650804282195);var lng = 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:[email protected]">[email protected]</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.
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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\n ","\"" name "\"", lat, lng }}
Unix ‘awk’ script to extract and format the text
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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
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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
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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
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Your words
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Reporting
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Break!
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Spatial is special
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“How to lie with maps”
1 – change the map units
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Political context
Gerrymandering: adjusting political units to favour particular party
See: http://www.redistrictinggame.org
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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.
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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
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“How to lie with maps”
2 – extensive versus intensive
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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
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Example – total population
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Example – population density
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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
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“How to lie with maps”
3 – change the colouring
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Equal intervals
Quantile
Choice of classification is critical
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Example (from ESRI) – where are the kids?
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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)
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Break!
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Geofutures
Geo in 2015
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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?
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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/
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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?
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Wrap-up
• What have you learnt?• Feedback: has this helped?
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Further Examples – zoning effects"How to Lie with Maps" by Mark Monmonier
(see Chapter 9 (first edition))
1000 100 50 100 50 100 50
200 100 200 100 200 100 200
100 200 100 4000 100 200 100
200 400 200 400 200 400 3000
Number of televisions
2000 200 100 200 100 200 100
200 100 200 100 200 100 200
100 200 100 4000 100 200 100
100 200 100 200 100 200 1500Number of households
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Televisions per household
0.5 0.5 0.5 0.5 0.5 0.5 0.5
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
2.0 2.0 2.0 2.0 2.0 2.0 2.0
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AggregationNumber of TVs
Number of h'holds
TVs per h'hold
1450
5900
4800
2900
5900
2400
0.5
1.0
2.0
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Aggregation (2)
2300 5700 4150
0.74 1.04 1.60
3100 5500 2600
Number of TVs
Number of h'holds
TVs per h'hold
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Aggregation (3)Number of TVs
Number of h'holds
TVs per h'hold
11003550
4100
340022003200
4100
17000.51.11
1.0
2.0
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Further examples – ecological fallacy
2300 5700 4150
0.74 1.04 1.60
3100 5500 2600
Number of TVs
Number of h'holds
TVs per h'hold
What’s the pattern in the original cells?
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A consistent disaggregation
Number of TVs
Number of h'holds
190 285 200 350 350 210 890
455 450 1085 960 895 520 1260
355 315 525 480 595 360 700
130 120 80 100 80 110 100
100 150 100 200 100 50 100
350 300 700 600 500 200 300
500 450 700 600 700 400 500
650 600 400 500 400 550 500
2300 5700 4150
3100 5500 2600
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Ecological FallacyNumber of TVs
Number of h'holds
190 285 200 350 350 210 890
455 450 1085 960 895 520 1260
355 315 525 480 595 360 700
130 120 80 100 80 110 100
100 150 100 200 100 50 100
350 300 700 600 500 200 300
500 450 700 600 700 400 500
650 600 400 500 400 550 500
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Ecological FallacyNumber of TVs
Number of h'holds
TVs per h'hold
190 285 200 350 350 210 890
455 450 1085 960 895 520 1260
355 315 525 480 595 360 700
130 120 80 100 80 110 100
1.90 1.90 2.00 1.75 3.50 4.20 8.90
1.30 1.50 1.55 1.60 1.79 2.60 4.20
0.71 0.70 0.75 0.80 0.85 0.90 1.40
0.20 0.20 0.20 0.20 0.20 0.20 0.20
100 150 100 200 100 50 100
350 300 700 600 500 200 300
500 450 700 600 700 400 500
650 600 400 500 400 550 500
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Ecological Fallacy
1.90 1.90 2.00 1.75 3.50 4.20 8.90
1.30 1.50 1.55 1.60 1.79 2.60 4.20
0.71 0.70 0.75 0.80 0.85 0.90 1.40
0.20 0.20 0.20 0.20 0.20 0.20 0.20
0.5 0.5 0.5 0.5 0.5 0.5 0.5
1.0 1.0 1.0 1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0 1.0 1.0 1.0
2.0 2.0 2.0 2.0 2.0 2.0 2.0
0.74 1.04 1.60Same aggregated trend from different fine-scale detail.