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Summary of DART Electromagnetic Methodology 100111
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Summary of DART Electromagnetic Methodology 100111

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A summary of the proposed Electromagnetic methodology to be used on the DART project. Presented at the academic and stakeholder meetings (10th and 11th January 2011 respectively) by David Stott (Leeds ...

A summary of the proposed Electromagnetic methodology to be used on the DART project. Presented at the academic and stakeholder meetings (10th and 11th January 2011 respectively) by David Stott (Leeds University).

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    Summary of DART Electromagnetic Methodology 100111 Summary of DART Electromagnetic Methodology 100111 Presentation Transcript

    • On the surface: Optical aerial remote sensing methodology David Stott
    • Introduction What am I doing? Determining contrast parameters for detecting archaeological deposits in optical aerial remote sensing data using passive sensors These sensors operate across the electromagnetic spectrum We will be using Field spectro-radiometry Aerial hyper-spectral imaging
    • Introduction Why? To produce a model that will allow us to: Predict optimal data acquisition times for archaeological deposits on different geologies Evaluate contrast in existing archival data based on time of acquisition and context This will improve practice and help to get better value from our datasets
    • Background Deposits are identified by contrasts either: Directly (bare soil) By proxy (change in vegetation) Image redacted
    • Background
    • Source: Beck 2010 Source: Wikimedia commons
    • Change
    • Soil Soil moisture Apparent in absorption bands at 1400nm, 1900nm and 2700nm More visible in clay soils than sandy soils Soil texture Little impact on spectral reflectance other than moisture retention Organic matter Visible wavelengths Iron oxide Absorption bands at 560nm and 830nm indicate ferrous or reduced iron Surface roughness affects spectral response
    • Vegetation Vegetation stress and vigour: Greatest contrasts result from Soil Moisture Deficit (SMD) Potential SMDs calculated by subtracting estimated transpiration and evaporation from rainfall Severity varies according to crop type and over phenological cycle Stress and vigour may be further detectable using photosynthetic fluorescence Radiation emitted at longer wavelengths as a by-product of photosynthetic reactions Indicates health of photosynthetic machinery Used in precision agriculture to determine water and nutrient stress
    • Methodology: Introduction Mostly ground based: Isolation of different parameters Temporal change Producing comparable data Spatially restricted Airborne Data : Spatially extensive Temporally restricted (4 flights during 2011) CASI from Environment Agency Possibly Eagle and Hawk
    • Methodology: Features Image courtesy of Stefano Campana
    • Harnhill location http://maps.google.co.uk/maps?f=q&source=s_q&hl=en&geocode=&q=Cirencester&sll=52.276677,-0.25899&sspn=0.061128,0.110378&g=diddington&ie=UTF8&hq=&hnear=Cirencester,+United+Kingdom&ll=51.705438,-1.90424&spn=0.007739,0.021973&t=h&z=16
    • Measuring Spectra ASD Fieldspec Pro: Spectral Range 350-2500 nm Sampling Interval 1.4 nm, 350-1000 nm 2 nm, 1000-2500 nm Two approaches: Field based reflectance measurements Contact measurements
    • Spectro-Radiometry: Reflectance Requires calibration with a reference panel Data dependant on viewing position More generalised sampling (combined reflectance) dependant on field of view (IFOV) Optimal usage 2-3 hours before and after solar noon (4+ hour window) Can’t be used in the rain 235 rain days on average annually in Cirencester* 196 rain days on average annually in Diddington* * Source www.myweather2.com
    • Spectral Radiometry: Contact probe Uses an artificial light source on a small area (c.10mm) Very specific Fewer calibrations required Can be used off-site on samples Fewer temporal restrictions Not weather dependant But How to get vegetation samples measured before they die? (ice?) How to get un-disturbed soil-surface samples? (Kubiena tins?)
    • Spectro-radiometry: Envisaged methodology Contact probe is used to take measurements of separate soil and vegetation samples. Taken from randomly determined locations in each metre square Can be processed on site (in vehicle) or taken in-situ where possible Soil surface samples can also be used for further analysis Surface properties in each metre square to be recorded Used to predict mixed pixels Where possible (weather dependant) the 25deg FOV sensor to be used to measure reflectance for each metre square to test prediction
    • Sampling strategy Understanding transition between sterile and archaeological areas of archaeological potential is vital Important to catch ‘halo’ around feature Sample squares extending >5m on either side of feature
    • Quantifying coverage as viewed from above How to do this quickly? Quadrat survey? Close-range photogrammetry? IR adapted camera?
    • Further issues How many samples per m 2 are enough to understand heterogeneity? Observer effect How to measure these parameters without influencing the results Surface compaction / poaching Trampling vegetation Wind damage in mature crop caused by access corridors
    • References Beck, A. R., Archaeological site detection: the importance of contrast. In Proceedings of the 2007 Annual Conference of the Remote Sensing and Photogrammetry Society, Newcastle University, Sept. 11-14, 2007 McCoy, R.M. 2005. Field methods in Remote sensing. Guilford Press NY Scollar, I. 1990. Archaeological prospecting and Remote Sensing . Cambridge University Press, Cambridge