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Improving data capture
Improving data capture
Dissemination of data
Dissemination of data
Improving data capture
Improving data capture
Improving data capture
New data capture – Remote sensing
New data capture – Remote sensing
New data capture – Remote sensing
New data capture – Remote sensing
New data capture – Remote sensing
New data capture –
Terrestrial
New data capture – Close range
New data capture – Hydrological
Spitalfields
Medieval Cemetery
On site data capture
On site data capture
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Derived data capture
Points and attributes
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Alignments and outlines
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Alignments and outlines
Alignments and outlines
Alignments and outlines
Alignments and outlines
Phasing and structure – a view on stratigraphy
Phasing and structure – a view on stratigraphy
Relative meets absolute
Relative meets absolute
• 1920’s toilet centre upper in cemetery• Large basement area on east side of site, • Drainage dividing ditch between main body of cemetery and church in period 17• Civil war ditch leading up to charnel house from south.• Catastrophic burial from later periods
GIS for a truncated landscape
17 1615 14
Quantifying visibility
Quantifying visibility
26.7
45.5
56.854.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0
17 1400-153816 1250-1400 15 1200-125014-1100-1200
%of cemetery truncated by area
Truncation and population extrapolation
Found Est total Period length Cemetery area
Truncated area Visible area
Period 14 1100-1200 900 3000 100 4612 2621 1991
Period 15 1200-1250 2839 5600 50 4701 2538 2163
Period 16 1250-1400 5480 7900 150 5687 2587 3100
Period 17 1400-1538 1009 1350 138 2923 780 2143
Quantifying visibility
Spatial targets, what was happening around these target?
• Charnel house appears in period 1320s • The Pulpit cross – 1390s• Relationships to the south-east end of church period X• Cannon’s infirmary period X• Cemetery changing boundary
Investigating a sacred landscape
Famine disease and distance Catasrophic
burial points
Data as a surface
Boundary proximity & burial type breakdown as %
01020304050607080
A B C
Within 3m of boundaryBackground
Boundary proximity & sex breakdown as %
05
1015202530354045
F M N/U
Within 3m of boundaryBackground
Boundary proximity & agecode breakdown as %
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8
Within 3m of boundaryBackground
Consecrated ground & buffer queries
Age at death period 17 Age at Death P 17
Buffered subsets
0
5
10
15
20
25
30
35
Pre-natal 7-11months
1-5 years 6-11years
12-17years
18-25years
26-35years
36-45years
46 ormore
Within 3m of monuments >3m From monuments
Buffered subsets
•
An articulated version of Rocque
1746 central London map georeferenced
to both OSGB36 and WGS84 CS
•
A point dataset of each combination of Parish, Ward and street/place identifiable on the map.
•
A replicable methodology
MOLA Products
Challenges
•
Accuracy of the map–
Stability of Media used
–
Survey technique used
•
How to minimise the amount of new data entry
•
QA of data sets
•
How to exploit the first accurate mapping of the area
Principles•
Grounding the GIS work in a geographical reality
•
Exploiting / re‐purposing existing resources
•
Creating data sets that required editing rather than re‐building to be appropriate to early or later
mapping
The Old Bailey on line
The Old Bailey on line
Putting the map together
Putting the map together
Putting the map together
Putting the map together
Putting the map in the right place
Putting the map in the right place
Putting the map in the right place
62% churches
Putting the map in the right place
Identifying places on the map
The geographical ‘reality’
Identifying places on the map
1Main thoroughfare ‐
outsized e.g. Holborn, Cheapside typically 20m width. This code is also to be used for
those roads that run around squares and similar entities.
2 Main thoroughfare ‐
standard width (c.15m)
3 Secondary thoroughfare ‐
standard width (c.10m)
4 Tertiary thoroughfare ‐
standard width (c.6m)
5 Alley way ‐
i.e. a narrow route running between two streets or street and place polygon (1‐2m)
6Cul‐de‐sac plus area ‐
i.e. a dead end but one which opens out into a court. The wider area is captured as a
polygon and will be amalgamated with class 6 streets (typically
c.2m but up to 10 for a Mews)
7 Cul‐de‐sac ‐
i.e. a simple dead‐end. (c.2m but up to 10 for a Mews)
Identifying places on the map
Hierarchies of streets
Identifying places on the map
Places and precincts
Identifying places on the map
A Traversable network
Identifying places on the map
Identifying places on the map
A Traversable network
Identifying places on the map
The Holborn viaduct dilemma
The Holborn viaduct dilemma
Identifying places on the map
Line-polygon-buffer
Identifying places on the map
Hierarchical clipping
Identifying places on the map
Identifying places on the map
Naming places
Existing data referenced + cleaned
Generating comprehensive data
Generating comprehensive data
Generating comprehensive data
Generating comprehensive data
Filename Contents Count Type
LL_PL Places 5887 Polygons
LL_PL_POINTS Places 5887 Points
LL_PA Parishes 191 Polygons
LL_PA_POINTS Parishes 191 Points
LL_WA Wards 99 Polygons
LL_WA_POINTS Wards 99 Points
LL_PL_PA 7,121 Polygons
LL_PL_PA_POINTS Places and Parishes 7,016 Points
LL_PL_WA Places and Wards 6,711 Polygons
LL_PL_WA_POINTS Places and Wards 6,711 Points
LL_PL_PA_WA Places and parishes and wards 7,847 Polygons
LL_PL_PA_WA_POINTS Places and parishes and wards 7,847 Points
LL_PA_WA Parishes and wards 555 Polygons
LL_PA_WA_POINTS Parishes and wards 555 Points
LL_STREET_NETWORK Street network Lines
• People are subjective observers• Computers are subjective ‘observers’• Identifying bias and humanization• To be useful they must be understood
Ode to a Spell CheckerI have a spelling checker
I disk covered four my PC. It plane lee marks four my revue Miss steaks aye can knot see.
Eye ran this poem threw it. Your sure real glad two no.
Its very polished in its weigh, My checker tolled me sew
•Defensive ?• On top of steep slopes• Good views of surrounding land?• Invisible interiors ?
Or
Constructing a sense of place?Seeing and being seen?
•Contextualising the act of
interpretation e.g. Video,
diaries•Broadcasting the data, e.g.
hypermedia•Storing multiple
interpretations in parallel•Reactive site investigation
