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School of ComputingFaculty of Engineering
DART – Archaeological detection
Anthony (Ant) Beck
Twitter: AntArch
Potential of satellite images and hyper/multi-spectral recording in archaeology
Poznan – 31st June 2012
Overview
• How do we detect stuff
• Why DART
• Going back to first principles
• DART overview
• Platforms
• Knowledge base – impact on deployment
Archaeological ProspectionWhat 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).
Archaeological ProspectionThese attributes may be masked or accentuated by a variety of other phenomena
http://www.youtube.com/v/UfOi_7Os7kA
Archaeological ProspectionWhat 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 meNow you dont
Archaeological ProspectionWhat is the basis for detection
Archaeological ProspectionWhat is the basis for detection
Archaeological ProspectionSummary
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
A multi-sensor environment:which includes ground survey and excavation
Why DART? Isn’t everything rosy in the garden?
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
Why DART? Precision agriculture Using science to maximise crop return
Why DART? Precision agricultureOutlier values are being controlled
Why DART? Traditional AP exemplar
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
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
What do we want to achieve with this?
Increased understanding which could lead to:• Improved detection in marginal
conditions
• Increasing the windows of opportunity for detection
• Being able to detect a broader range of features
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?
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
What do we do about this? Understand the relationship between the sensor and the phenomena
What do we do about this? Understand the relationship between the sensor and the phenomena
Spatial Resolution
What do we do about this? Understand the relationship between the sensor and the phenomena
Radiometric resolution
determines how finely a system can represent or distinguish differences of intensity
Radiometric Resolution
What do we do about this? Understand the relationship between the sensor and the phenomena
Temporal Resolution
What do we do about this? Understand the relationship between the sensor and the phenomena
http://www.youtube.com/v/Nh-ZB5bxPhc
Spectral(?) Resolution
What do we do about this? Understand the processes better
So what causes these localised variations?• Local conditions structure how any
contrast difference is exhibited:
• Soil type
• Crop type
• Moisture
• Nutrients
• Diurnal temperature variations
What do we do about this? Understand the processes better
Expressed contrast differences change over time• Seasonal variations
• crop phenology (growth)
• moisture
• temperature
• nutrients
• Diurnal variations
• sun angle (topographic features)
• temperature variations
What do we do about this? Understand the processes better
Exacerbated by anthropogenic actions• Cropping
• Irrigation
• Harrowing
What do we do about this? Example from multi or hyper spectral imaging
DART
DART - Collaborators
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
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
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
http://prezi.com/_tntxlrctptg/dart-sites/
DART: Probe Arrays
DART: Probe Arrays
DART: Field Measurements
Spectro-radiometry• Soil
• Vegetation
• Every 2 weeks
Crop phenology• Height
• Growth (tillering)
Flash res 64• Including induced events
DART: Field Measurements
Resistivity
Weather station• Logging every half hour
DART: Probe Arrays
DART: Field Measurements
Aerial data• Hyperspectral surveys
• CASI
• EAGLE
• HAWK
• LiDAR
• Traditional Aerial Photographs
DART: Laboratory Measurements
Geotechnical analyses
Particle size
Sheer strength
etc.
Geochemical analyses
Plant Biology
DART: Laboratory Measurements
Plant Biology• Rate of germination
(emergence)
• Growth analysis
• Number of Leaves
• Number of Tillers
• Stem length
• Total plant height
• Drought experiment
• A - Ci Curve
• Chlorophyll a fluorescence
• Soil and leaf water content
• Root studies
• Root length and density.
• Root – Shoot biomass ratio.
• Total plant biomass
• Biochemical analysis: Protein and chlorophyll analysis.
• Broad spectrum analysis of soil (Nutrient content) and C-N ratios of leaf.
DART
ERT
B’ham TDR
Imco TDR
Spectro-radiometry transect
DitchRob Fry
DART
ERT
B’ham TDR
Imco TDR
Spectro-radiometry transect
DitchRob Fry
DART – exemplars
Hyperspectral (400-2500nm)
High resolution Vertical
ERT
B’ham TDR
Imco TDR
Spectro-radiometry transect
DitchRob Fry
DART – exemplars
Airborne Laser Scanning
Discrete Echo and Full Waveform ERT
DitchRob Fry
DART – exemplars
Obliques
UAV
ERT
B’ham TDR
DitchRob Fry
DART: Data so far - Temperature
DART: Data so far - Temperature
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
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
DART: Data so far – Earth Resistance
R
DART: Data so far – Earth ResistanceProbe Separation (m)
0.25 0.5 0.75 1
June 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
September 8.841189868 13.255 14.512463 15.53069
October 7.988128839 10.97714 12.217018 11.6229
June July August September October
0.25 18.0474255247753
19.1351779351603
0 8.84118986817586
7.98812883944877
0.5 18.8854489164087
17.1520465259726
0 13.2550009710624
10.9771430226832
0.75 18.8968963893818
17.0816126928928
0 14.5124626121635
12.2170179547229
1 16.7940349425365
15.0190573579995
0 15.5306917565003
11.6228978543617
7.5
12.5
17.5
Change of Contrast Factors with Seasons
0.250.50.75
Twin Probe Electrode
Seperation (m)
Co
ntr
ast
Facto
r (%
)
Difference in magnitude
DART: Data so far – Earth Resistance
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
http://prezi.com/-oaoksqr09gx/dart-hyperspectral-the-driest-spring/
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
http://prezi.com/v5kahvg2zmyz/dart-plant-biology/
DART: Knowledge Base
http://prezi.com/ef_aud--i00t/dart-knowledge-base
DART: Communication
http://prezi.com/yo-pijkatt0a/dart-communication-infrastructure/
http://dartproject.info/WPBlog/
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 ETC.
Why are we doing this – spreading the love
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
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
Why are we doing this – innovation
Reducing barriers to data and knowledge can improve innovation
Why are we doing this – education
To provide baseline exemplar data for teaching and learning
Why are we doing this – building our network
Find new ways to exploit our data
Develop contacts
Write more grant applications
Discussion
SFM
Pushbroom
High resolution frame
Oblique and UAV
Topographic
From SFM
Full Waveform LiDAR
Detection
Hyperspectral (including thermal)
Spectral Analysis
Visualization
ERT and tomography
Complex data!
Plant Biology
Phenology
Differential growth parameters
Data mining (process from measurements)
Environmental
Soils
Temperature
Questions
Overview
There is no need to take notes:
Slides – http://goo.gl/ZHYaB
Text – http://goo.gl/osQZi or http://goo.gl/M5Eu1
There is every need to ask questions
The slides and text are release under a Creative Commons by attribution licence.