DART Improves Archaeological Detection Science
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The document discusses the DART (Detecting and Recording Archaeological Traces) project, which aims to improve archaeological detection techniques by taking a scientific approach. It involves intensive ground observation and data collection at sites to better understand how archaeological remains generate detectable contrasts and how those contrasts are influenced by environmental factors over time. The data collected includes spectro-radiometry, soil moisture and temperature probes, weather data, and aerial imagery. Preliminary analysis of temperature, moisture, and resistance data show changes seasonally that could help predict optimal times for detection. The open science approach seeks to further archaeological prospection methods.
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DART Improves Archaeological Detection Science
- 1. DART - Improving the science underpinning archaeological detection Anthony (Ant) Beck Twitter: AntArch IC ArchPro Workshop 1 - Airborne Remote Sensing Vienna - 30th November 2011 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
- 4. Archaeological Prospection What is the basis for detection
- 5. Archaeological Prospection What is the basis for detection
- 6. 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
- 7. 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
- 8. 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!).
- 9. 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: • Archaeological sites are physical and chemical phenomena. • There are different kinds of site constituents. • The abundance and spatial distribution of different constituents vary both between sites and within individual sites. • These attributes may be masked or accentuated by a variety of other phenomena. • Importantly from a remote sensing perspective archaeological site do not exhibit consistent spectral signatures
- 10. 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).
- 11. Archaeological Prospection What is the basis for detection
- 12. Archaeological Prospection What is the basis for detection
- 13. Archaeological Prospection What is the basis for detection
- 14. 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
- 16. Why DART? Isn’t everything rosy in the garden?
- 17. 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
- 18. Why DART? Precision agriculture
- 19. Why DART? Precision agriculture
- 20. Why DART? Traditional AP exemplar
- 21. Why DART? Traditional AP exemplar
- 22. 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
- 23. 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
- 24. 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?
- 25. 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
- 26. What do we do about this? Understand the relationship between the sensor and the phenomena
- 27. What do we do about this? Understand the relationship between the sensor and the phenomena
- 28. What do we do about this? Understand the relationship between the sensor and the phenomena determines how finely a system can represent or distinguish differences of intensity is usually expressed as a number of levels or a number of bits • for example 8 bits or 256 levels Higher radiometric resolution means that more subtle differences of intensity or reflectivity can be detected Signal to noise ratios can be a problem
- 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
- 31. 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
- 32. 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
- 33. What do we do about this? Understand the processes better Exacerbated by anthropogenic actions • Cropping • Irrigation • Harrowing
- 34. What do we do about this? Example from multi or hyper spectral imaging
- 35. DART
- 38. 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
- 39. DART: Ground Observation Benchmarking Try to understand the periodicity of change • Require intensive ground observation (spectro-radiometry, soil and crop analysis) at known sites (and their surroundings) in a range of different environments under different environmental conditions
- 40. 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
- 42. DART: Field Measurements Spectro-radiometry • Soil • Vegetation • Every 2 weeks Crop phenology • Height • Growth (tillering) Flash res 64 • Including induced events
- 43. DART: Field Measurements Resistivity Ground penetrating radar Embedded Soil Moisture and Temperature probes • Logging every hour Weather station • Logging every half hour
- 44. DART: Field Measurements Aerial data • Hyperspectral surveys • CASI • EAGLE • HAWK • LiDAR • Traditional Aerial Photographs Low level photography • 1 photo every 30 minutes
- 47. 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
- 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 There appears to be some problems with the recording Useful tool for • Scheduling diurnal thermal inertia flights • Calibrating the TDR readings
- 56. 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
- 57. 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
- 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
- 62. DART: Data so far - Permittivity Conversion to moisture content is also a priority Requires calibration using different mixing models including: • empirical • semi-empirical • physical volumetric • phenomenological models This will help us to link the changes in geophysical responses to the composition of the soil and predict future responses, as well as supporting investigations into crop stress and vigour.
- 63. DART: Data so far – Earth Resistance
- 64. DART: Data so far – Earth Resistance The measured earth resistance of a site will change throughout the year. This is due to many factors which exist in the natural landscape. It is not the broad change of readings we are interested in • Not Quantitative but how the readings within the archaeological feature change compared to the readings of the natural surrounding soil • But Relative
- 65. 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.
- 66. DART: Data so far – Earth Resistance Methodology: • The raw geophysical data is despiked • Specific data points are chosen for examination • Data values are extracted at different probe separations • The percentage difference is calculated
- 67. DART: Data so far – Earth Resistance Probe Separation (m) 0.25 0.5 0.75 1 18.047425 18.885 18.8968 16.794 June 52 45 96 03 19.135177 17.152 17.0816 15.019 July 94 05 13 06 August #N/A #N/A #N/A #N/A 20 8.8411898 14.5124 15.530 Change of Contrast Factors with September 68 13.255 63 69 Seasons Contrast Factor (%) 7.9881288 10.977 12.2170 11.622 15 October 39 14 18 9 Twin Probe 10 Electrode Seperation (m) 0.2 5 5 0.5 June July August September October 0.7 0.25 18.04742 19.13517 8.841189 7.988128 5 0.5 18.88544 17.15204 13.25500 10.97714 0.75 18.89689 17.08161 14.51246 12.21701 1 16.79403 15.01905 15.53069 11.62289
- 68. DART: Data so far – Earth Resistance Z values of Ditch and Natural measurements at CC1011 0.5 SD from mean of dataset 0 -0.5 -1 -1.5 -2 0.25 0.5 0.75 1 Ditch -1.268861893 -1.56669708 -1.640283843 -1.362385321 Natural -0.038363171 0.161952555 0.239082969 0.246559633
- 69. DART: Data so far – Earth Resistance
- 71. 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
- 72. 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
- 77. 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
- 78. 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
- 80. DART: Plant Biology Lab experiments conducted in collaboration with Leeds Plant Biology
- 87. The case for Open Science from Cameron Neylon
- 88. Questions
Notes de l'éditeur
- Image re-used under a creative commons licence: http://www.flickr.com/photos/irenicrhonda/3468242704Landscape features show up at different scalesThe archaeological record SurficialBuried Depending on scale of examination essentially invisble to the human eye
- Traces can be identified through evidence Clusters of artefacts Chemical and physical residues Proxy biological variations Changes in surface relief
- Traces can be identified through evidence Clusters of artefacts Chemical and physical residues Proxy biological variations Changes in surface relief
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/mikkomiettinen/2587623210At 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.
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/arenamontanus/8231697At the large scale: The distribution is far from even, with large areas where archaeological remains are widely and infrequently dispersed. There are other areas where materials and other remains are abundant and clustered. It is these peaks of abundance that are commonly referred to as sites.
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/catikaoe/183454010/We identify contrast Between the expression of the remains and the local 'background' value In most scenarios direct contrast measurements are preferable as these measurements will have less attenuation.Proxy contrast measurements are extremely useful when the residue under study does not produce a directly discernable contrast or it exists in a regime where direct observation is impossible
- Dependant on localised formation and deformation Localised formation and deformation SchifferHarrisPhysical/chemical structure
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/arpentnourricier/2385863532Dependant on localised formation and deformation Environmental conditions Soil moisture Crop Temperature and emmisivity
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/dartproject/6001577156Dependant on localised formation and deformation Land management
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/dartproject/6001577156Dependant on localised formation and deformation Land management
- Satellite approaches should be considered in a multi-sensor environment which includes ground survey and excavationThe point is to learn more about the past
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/southernpixel/3480710493/Not really.We have great techniques but some are in danger of becoming redundant
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/san_drino/1454922072/Environmental processesSensor responses (particularly new sensors)Constraining factors (soil, crops etc.)Bias and spatial variabilityIMPACTS ONDeploymentManagement
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/jimmysmith/720356377/Changes in land management may reduce the appearance of the phenomena we seekUsing science to maximise crop return
- Image re-used under a Creative Commons licence: http://www.flickr.com/photos/tangyauhoong/4502062656/Actual crop returns controlled so they approximate towardsthe 'norm'NEW, i.e. not observed before, archaeology is contained within the tailsThese outlier values are being removed.The outlier is an exceptional year ;-)
- Most successful archaeological detection technique Low level aerial platform Handheld SLR and digital cameras Reliance on oblique photography Optical and Near Infrared wavelengths Used since early 1900s
- Reliant on specific seasonal and environmental conditions Increasingly extreme conditions are required for the detection of ‘new’ sitesLow understanding of the physical processes at play outside the visual wavelengths
- 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
- Image re-used under a creative commons licence: http://www.flickr.com/photos/8203774@N06/2310292882/
- Image re-used under a Creative Commons licence:How does the object generate an observable contrast to it's local matrix?PhysicalChemicalBiologicaletcAre the contrasts permanent or transitory?
- Image re-used under a Creative Commons licence:If transitory why are they occurring?Is it changes in?Soil typeLand managementSoil moistureTemperatureNutrient availabilityCrop typeCrop growth stage
- Image re-used under a Creative Commons licence:
- Image re-used under a Creative Commons licence: DARTSpatial Resolution You need enough to observe the object
- Image re-used under a Creative Commons licence: DARTRadiometric Resolution - You need enough to be able to physically detect the expressed differencesdetermines how finely a system can represent or distinguish differences of intensity is usually expressed as a number of levels or a number of bits for example 8 bits or 256 levels The higher the radiometric resolution, the better subtle differences of intensity or reflectivity can be represented Signal to noise ratios can be a problem Example It is difficult to detect small changes in growth if your ruler only measures to the nearect 10cms You need enough to be able to physically detect the expressed differences
- Image re-used under a Creative Commons licence: DARTYou need to know when to look for the difference
- Spectral Resolution You need to know what part of the spectrum to detect the expressed difference Unsure of the geophysical metaphor for this
- Image re-used under a Creative Commons licence: DARTSo what causes these localised variations?Local conditions structure how any contrast difference is exhibited:Soil typeCrop typeMoistureNutrientsDiurnal temperature variations
- Image re-used under a Creative Commons licence: DARTExpressed contrast differences change over timeSeasonal variationscrop phenology (growth)moisturetemperaturenutrientsDiurnal variationssun angle (topographic features)temperature variations
- Image re-used under a Creative Commons licence: DARTExacerbated by anthropogenic actionsCroppingIrrigationHarrowing
- Image re-used under a Creative Commons licence: DARTBut archaeology doesn't tend to produce spectral signatures Rather: produce localised disruptions to a matrix The nature of these disruptions vary and include: Changes to the soil structure Changes to moisture retention capacity Changes in geochemistry Changes in magnetic or acoustic properties Changes to topography At least one of these disruptions will produce a contrast which is detectable The challenge is What sensor to use The sensitivity of the sensor When to deploy the sensor
- Based upon an understanding of:Nature of the archaeological residuesNature of archaeological material (physical and chemical structure)Nature of the surrounding material with which it contrastsHow proxy material (crop) interacts with archaeology and surrounding matrixSensor characteristicsSpatial, spectral, radiometric and temporalHow these can be applied to detect contrastsEnvironmental characteristicsComplex natural and cultural variables that can change rapidly over time
- Try to understand the periodicity of changeRequire intensive ground observation (spectro-radiometry, soil and crop analysis) at known sites (and their surroundings) in a range of different environments under different environmental conditions
- LocationDiddington, CambridgeshireHarnhill, GloucestershireBoth withcontrasting clay and 'well draining' soilsan identifiable archaeological repertoireunder arable cultivationContrasting Macro environmental characteristics
- Image re-used under a creative commons licence:http://www.flickr.com/photos/soilscience/5104676427Spectro-radiometrySoilVegetationEvery 2 weeksCrop phenologyHeightGrowth (tillering)Flash res 64Including induced events
- ResistivityGround penetrating radarEmbedded Soil Moisture and Temperature probesLogging every hour Weather stationLogging every half hour
- Aerial dataHyperspectral surveysCASIEAGLEHAWKLiDARTraditional Aerial Photographs
- Image reused under a Creative Commons Licence:http://www.flickr.com/photos/kubina/279523019Geotechnical analysesGeochemical analysesPlant Biology
- Image reused under a Creative Commons Licence:http://www.flickr.com/photos/kubina/279523019Geotechnical analysesGeochemical analysesPlant Biology
- Davis Vantage Pro Weather stationCollects a range of technical data e.g.Wind speedWind directionRainfallTemperatureHumiditySolar RadiationBarometric PressureAnd derivativesWind ChillHeat Index
- Image reused under a Creative Commons Licence:http://www.flickr.com/photos/kubina/279523019Geotechnical analysesGeochemical analysesPlant Biology
- There appears to be some problems with the recordingUseful tool forScheduling diurnal thermal inertia flightsCalibrating the TDR readings
- Key aimsInvestigate 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 matrixAttempt 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 workLink the soil properties to local weather and other environmental factors to enable better planning for collection techniques
- TDR - How does it workSends a pulse of EM energyDue 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 traceThe distance between these two reflection points is used to determine the Dielectric permittivity Different soils have different dielectric permittivityThis needs calibrating before soil moisture can be derived from the sensors
- Further analysis of permittivity and conductivity against rainfall Linking the changes to the weather patternsComparisons can be made betweenSoils at different depthsArchaeological and non-archaeological featuresDifferent soil types at the different locations
- Conversion to moisture content is also a priorityRequires calibration using different mixing models including:empiricalsemi-empiricalphysical volumetric phenomenological modelsThis will help us to link the changes in geophysical responses to the composition of the soil and predict future responses, as well as supporting investigations into crop stress and vigour.
- Conversion to moisture content is also a priorityRequires calibration using different mixing models including:empiricalsemi-empiricalphysical volumetric phenomenological modelsThis will help us to link the changes in geophysical responses to the composition of the soil and predict future responses, as well as supporting investigations into crop stress and vigour.
- The measured earth resistance of a site will change throughout the year.This is due to many factors which exist in the natural landscape.It is not the broad change of readings we are interested inNot Quantitativebut how the readings within the archaeological feature change compared to the readings of the natural surrounding soilBut Relative
- methodology similar to that employed by Parkyn et al. (2011)Overviewdata pointslie within the ditch featureover the non-archaeological featurefind an average data value for the feature and the surrounding soilThe 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.
- Conversion to moisture content is also a priorityRequires calibration using different mixing models including:empiricalsemi-empiricalphysical volumetric phenomenological modelsThis will help us to link the changes in geophysical responses to the composition of the soil and predict future responses, as well as supporting investigations into crop stress and vigour.
- Conversion to moisture content is also a priorityRequires calibration using different mixing models including:empiricalsemi-empiricalphysical volumetric phenomenological modelsThis will help us to link the changes in geophysical responses to the composition of the soil and predict future responses, as well as supporting investigations into crop stress and vigour.
- The graph below shows the calculated z-values from the selected points inside the ditch and from the chosen ‘background’ response when compared to the entire dataset. This is a useful analysis of how the chosen ditch and background samples compare to all the collected points and shows that the ditch is always over 1.25 standard deviations below the mean of the dataset as a whole.
- Sampling zones – setting up a spatial proxy