A presentation given by Anthony Beck to the Department of Archaeology at University College Dublin on the 21st February 2012

1. DART - Improving the science
underpinning archaeological detection
Anthony (Ant) Beck
Twitter: AntArch
Dublin– 23rd February 2012
School of Computing
Faculty of Engineering

2. Overview
•How do we detect stuff
•Why DART
•Going back to first principles
•DART overview
•Data so far
•Open Science

3. Overview
There is no need to take notes:
Slides –
Text –
http://dl.dropbox.com/u/393477/MindMaps/Events/Conference
sAndWorkshops.html
There is every need to ask questions
The slides and text are release under a Creative Commons by
attribution licence.

4. Archaeological Prospection
What is the basis for detection

5. Archaeological Prospection
What is the basis for detection
At the small scale:
• The archaeological record can be
considered as a more or less
continuous spatial distribution of
artefacts, structures, organic
remains, chemical residues,
topographic variations and other
less obvious modifications

6. Archaeological Prospection
What is the basis for detection
At the large scale:
• The distribution is far from even, with
large areas where archaeological
remains are widely and infrequently
dispersed. There are other areas,
however, where materials and other
remains are abundant and clustered.
It is these peaks of abundance that
are commonly referred to as sites,
features, anomalies (whatever!).

7. Archaeological Prospection
What is the basis for detection
Discovery requires the detection of one or more site
constituents.
The important points for archaeological detection are:

8. Archaeological Prospection
Archaeological sites are physical and chemical phenomena

9. Archaeological Prospection
There are different kinds of site constituents

10. Archaeological Prospection
The abundance and spatial distribution of different
constituents vary both between and within individual sites

11. Archaeological Prospection
These attributes may be masked or accentuated by a variety
of other phenomena

12. Archaeological Prospection
Importantly from a remote sensing perspective archaeological
site do not exhibit consistent spectral signatures

13. Archaeological Prospection
What is the basis for detection
We detect Contrast:
• Between the expression of the remains
and the local 'background' value
Direct Contrast:
• where a measurement, which exhibits a
detectable contrast with its surroundings,
is taken directly from an archaeological
residue.
Proxy Contrast:
• where a measurement, which exhibits a
detectable contrast with its surroundings,
is taken indirectly from an archaeological
residue (for example from a crop mark).

14. Archaeological Prospection
What is the basis for detection

15. Archaeological Prospection
What is the basis for detection

16. Archaeological Prospection
Summary
The sensor must have:
• The spatial resolution to resolve the feature
• The spectral resolution to resolve the contrast
• The radiometric resolution to identify the change
• The temporal sensitivity to record the feature when the contrast is
exhibited
The image must be captured at the right time:
• Different features exhibit contrast characteristics at different times

18. Archaeological Prospection
What is the basis for detection

19. Archaeological Prospection
What is the basis for detection
Micro-Topographic variations
Soil Marks
• variation in mineralogy and
moisture properties
Differential Crop Marks
• constraint on root depth and
moisture availability changing
crop stress/vigour
Proxy Thaw Marks
• Exploitation of different thermal
capacities of objects expressed
in the visual component as
thaw marks
Now you see me
dont

20. Why DART? Isn’t everything rosy in the garden?

21. Why DART? ‘Things’ are not well understood
Environmental processes
Sensor responses (particularly new
sensors)
Constraining factors (soil, crops etc.)
Bias and spatial variability
Techniques are scaling!
• Geophysics!
IMPACTS ON
• Deployment
• Management

22. Why DART? Precision agriculture

23. Why DART? Precision agriculture

24. Why DART? Traditional AP exemplar

25. Why DART? Traditional AP exemplar
Significant bias in its application
• in the environmental areas where it is
productive (for example clay
environments tend not to be
responsive)
• Surveys don’t tend to be systematic
• Interpretation tends to be more art
than science

26. What do we do about this?
Go back to first principles:
• Understand the phenomena
• Understand the sensor
characteristics
• Understand the relationship
between the sensor and the
phenomena
• Understand the processes better
• Understand when to apply
techniques

27. What do we do about this? Understand the
phenomena
How does the object generate an
observable contrast to it's local
matrix?
• Physical
• Chemical
• Biological
• etc
Are the contrasts permanent or
transitory?

28. What do we do about this? Understand the
phenomena
If transitory why are they
occurring?
• Is it changes in?
• Soil type
• Land management
• Soil moisture
• Temperature
• Nutrient availability
• Crop type
• Crop growth stage

29. What do we do about this? Understand the
relationship between the sensor and the phenomena

30. What do we do about this? Understand the
relationship between the sensor and the phenomena
Spatial Resolution

31. What do we do about this? Understand the
relationship between the sensor and the phenomena
Radiometric Resolution
Radiometric resolution
determines how finely a system can
represent or distinguish differences of
intensity

32. What do we do about this? Understand the
relationship between the sensor and the phenomena
Temporal Resolution

33. What do we do about this? Understand the
relationship between the sensor and the phenomena
Spectral(?) Resolution

34. What do we do about this? Example from multi or
hyper spectral imaging

35. DART

36. DART - Collaborators

37. DART: Ground Observation Benchmarking
Based upon an understanding of:
• Nature of the archaeological residues
• Nature of archaeological material (physical and chemical structure)
• Nature of the surrounding material with which it contrasts
• How proxy material (crop) interacts with archaeology and surrounding
matrix
• Sensor characteristics
• Spatial, spectral, radiometric and temporal
• How these can be applied to detect contrasts
• Environmental characteristics
• Complex natural and cultural variables that can change rapidly over
time

38. DART: Ground Observation Benchmarking
Try to understand the periodicity of change
• Requires
• intensive ground observation
• at known sites (and their surroundings)
• In different environmental settings
• under different environmental conditions

39. DART: Sites
Location
• Diddington, Cambridgeshire
• Harnhill, Gloucestershire
Both with
• contrasting clay and 'well draining'
soils
• an identifiable archaeological
repertoire
• under arable cultivation
Contrasting Macro environmental
characteristics

41. DART: Field Measurements
Spectro-radiometry
• Soil
• Vegetation
• Every 2 weeks
Crop phenology
• Height
• Growth (tillering)
Flash res 64
• Including induced events

42. DART: Field Measurements
Resistivity
Ground penetrating radar
Embedded Soil Moisture and
Temperature probes
• Logging every hour
Weather station
• Logging every half hour

43. DART: Field Measurements
Aerial data
• Hyperspectral surveys
• CASI
• EAGLE
• HAWK
• LiDAR
• Traditional Aerial Photographs
Low level photography
• 1 photo every 30 minutes

44. DART: Probe Arrays

45. DART: Probe Arrays

46. DART: Weather Station
Davis Vantage Pro Weather station
• Collects a range of technical data e.g.
• Wind speed
• Wind direction
• Rainfall
• Temperature
• Humidity
• Solar Radiation
• Barometric Pressure
• And derivatives
• Wind Chill
• Heat Index

47. DART
ERT
Ditch
Rob Fry
B’ham TDR
Imco TDR
Spectro-radiometry transect

48. DART
ERT
Ditch
Rob Fry
B’ham TDR
Imco TDR
Spectro-radiometry transect

49. DART: Laboratory Measurements
Geotechnical analyses
Geochemical analyses
Plant Biology

50. DART: Data so far - Temperature

51. DART: Data so far - Temperature

52. DART: Data so far - Temperature

53. DART: Data so far - Temperature

54. DART: Data so far - Temperature

55. DART: Data so far - Temperature
Useful tool for
• Scheduling diurnal thermal inertia flights
• Calibrating the TDR readings

56. DART: Data so far - Permittivity
TDR - How does it work
• Sends a pulse of EM energy
• Due to changes in impedance, at the start and at the end of the probe,
the pulse is reflected back and the reflections can be identified on the
waveform trace
• The distance between these two reflection points is used to determine
the Dielectric permittivity
• Different soils have different dielectric permittivity
• This needs calibrating before soil moisture can be derived from the
sensors

57. DART: Data so far - Permittivity
Key aims
• Investigate the propagation of EM radiation in different soil conditions
(e.g. temperature, magnetic permeability, moisture content, density) and
identify the difference between archaeological residue and the
surrounding soil matrix
• Attempt to use geotechnical properties (e.g. particle size distribution,
moisture content) to predict the geophysical responses of the different
EM sensors used in aerial and geophysical work
• Link the soil properties to local weather and other environmental factors
to enable better planning for collection techniques

58. DART: Data so far - Permittivity

59. DART: Data so far - Permittivity

60. DART: Data so far - Permittivity

61. DART: Data so far - Permittivity
Further analysis of permittivity and conductivity against rainfall
Linking the changes to the weather patterns
Comparisons can be made between
• Soils at different depths
• Archaeological and non-archaeological features
• Different soil types at the different locations
Conversion to moisture content is also a priority

62. DART: Data so far – Earth Resistance

63. DART: Data so far – Earth Resistance
methodology similar to that employed by Parkyn et al. (2011)
Overview
• data points
• lie within the ditch feature
• over the non-archaeological feature
• find an average data value for the feature and the surrounding soil
The percentage difference between these two figures can
then be considered the amount of contrast within the test
area.
The higher the percentage, the better the feature is able to be
defined.

64. DART: Data so far – Earth Resistance
Probe Separation (m)
0.25 0.5 0.75 1
June
R 18.04742552 18.88545 18.896896 16.79403
July 19.13517794 17.15205 17.081613 15.01906
August #N/A #N/A #N/A #N/A Difference in magnitude
September 8.841189868 13.255 14.512463 15.53069
Change of Contrast Factors with
October 7.988128839 10.97714 12.217018 11.6229
20 Seasons
Contrast Factor (%)
15
Twin Probe
Electrode
Seperation (m)
10 0.2
5
0.5
0.7
5 5
Septemb
June July August October
er
0.25 18.047426 19.135178 8.8411899 7.9881288
0.5 18.885449 17.152047 13.255001 10.977143
0.75 18.896896 17.081613 14.512463 12.217018
1 16.794035 15.019057 15.530692 11.622898

65. Spectro-radiometry: Methodology
• Recorded monthly
• Twice monthly at Diddington during the growing season
• Transects across linear features
• Taken in the field where weather conditions permit
• Surface coverage evaluated using near-vertical photography
• Vegetation properties recorded along transect
• Chlorophyll (SPAD)
• Height

66. Spectro-radiometry: Methodology
• Lab-based, background methodology
• Soils
• Soil samples taken along transect
• Reflectance measured with varying moisture content
• Vegetation
• Vegetation samples taken during each field visit
• Measured under artificial light under controlled conditions

71. Diddington transect 1: Spectroradiometry June 2011
0.12
R
e
l 0.1
a
t
i
v 0.08
e
r
0.06
e
f
l
e 0.04
c
t
a
n 0.02
c
e
0
400 500 600 700
Wavelength (nm)
27/06/2011 Archaeology 27/6/2011 Outside archaeology 14/06/2011 Archaeology
14/06/2011 Outside archaeology 08/06/2011 Archaeology 08/06/2011 Outside archaeology

72. Diddington transect 1: Spectroradiometry June 2011
0.4
R
0.35
e
l
a
0.3
t
i
v
0.25
e
r
0.2
e
f
l
0.15
e
c
t
0.1
a
n
c 0.05
e
0
350 450 550 650 750 850 950 1050 1150 1250 1350 1450 1550 1650 1750 1850 1950 2050 2150 2250 2350 2450
Wavelength (nm)
27/06/2011 Archaeology 27/6/2011 Outside archaeology 14/06/2011 Archaeology
14/06/2011 Outside archaeology 08/06/2011 Archaeolgy 08/06/2011 Outside archaeology

74. DART: Plant Biology
Lab experiments conducted in collaboration with Leeds Plant
Biology in 2011 and repeated in 2012
From soils at Quarry Field
Soil structure appears to be the major component influencing
root penetration and plant health

75. DART: Knowledge Base

76. DART: Communication

77. The case for Open Science from Cameron Neylon

78. Open Data: Server (in the near future)
The full project archive will be available from the server
Raw Data
Processed Data
Web Services
Will also include
TDR data
Weather data
Subsurface temperature data
Soil analyses
spectro-radiometry transects
Crop analyses
Excavation data
In-situ photos

79. Open Data: Server (in the near future)
Also:
Hyperspectral data
Thermal imaging
Full Waveform LiDAR
UAV data collection
Formats
Standard interoperable formats
Licences
These are not complete
Most data will be made available under an open re-use licence (see server)
Creative Commons
GPL

80. Why are we doing this – spreading the love

81. Why are we doing this – it’s the right thing to do
DART is a publically funded project
Publically funded data should provide benefit to the public

82. Why are we doing this – IMPACT/unlocking potential
More people use the data then there is improved impact
Better financial and intellectual return for the investors

83. Why are we doing this – innovation
Reducing barriers to data and knowledge can improve
innovation

84. Why are we doing this – education
To provide baseline exemplar data for teaching and learning

85. Why are we doing this – building our network
Find new ways to exploit our data
Develop contacts
Write more grant applications

86. Questions