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Masters Dissertation - Presentation
 

Masters Dissertation - Presentation

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  • WelcomeWelcome to my dissertation presentation which will apply GIS techniques to the world of archaeology!Recreation of the Sutton Hoo helmet found in 1939
  • Structure of PresentationBit of background, aims and objectives, methodology used, results, conclusions, finally asking whether I achieved my objectives.
  • BackgroundInspiration came from a project undertaken in 2006 by a guy called John Naylor.Make use of the finds made by metal detector usersThe online database designed to hold the information on their finds now has over 450,000 objects on it. Run by the Portable Antiquities Scheme in conjunction with the British Museum.
  • Aims and ObjectivesInvestigate a complex set of archaeological data using spatial analysis techniques . Reveal patterns in the data that otherwise would be unseenAssess the levels of activity at 22 previously identified sites using spatial analysisMay even be able to pinpoint where the next coin hoard worth £1,000’s may be!
  • Map of Study AreaMap of study area which encompassed the counties of Norfolk and Suffolk in the east of England3500 sq miles rich in Anglo Saxon finds
  • Preparing DataTook ages! Initial searches revealed over 3000 finds for the study areaWhen dealing with data supplied by the general public inconstancies everywhere.I broke down the mass of data into logical object groups Dated everything to an AS period because every item only had a possible date range. Plotted using e + n in the database.
  • Assigning CategoriesEach of the 2617 items were assigned an object group and time periodHere are the 6 categories and 3 time periods and an example of some of the finds placed in each of the object categories.
  • Spatial Analysis Techniques3 different clustering techniques used in the projectAverage Nearest Neighbour – Compare distance between feature locationsGlobal Morans I - Compare the distance between feature valuesGetis Ord G* Hotspot Analysis – shows whether features with high values or features with low values tend to cluster together. Thus forming hot or cold spotsZ Score significance 99% -90%Used to approve or disprove the null hypothesis that all the points were distributed as the result of a random process
  • Average Nearest Neighbour FindingsClustering tended to be less over timepossible reason:Anglo Saxon lifestyles became more rural over time Jewellery was found to cluster the most.Tend to be located togetherSafe storage Commercial and household least clustered.Less care taken over storage and disposal of these items
  • Global Morans I FindingsSlightly different picture, some object groups showed different degrees of clusteringClothing showed the greatest tendency to cluster this timeAgain storage a probable causeClothes and related items tend to be kept in closets or chests Commercial again the least clustered but no confidence level attached this time
  • Hotspot Analysis FindingsNo coldspots were foundAreas of high value clusters moved over time from central – north west of study areaSome object groups clustered in certain areas: Example:Coins in and around the town of Freckenham which was one of the sites identified in 2006Corridors of higher value clusters shown in the coins and commercial object groups can be seen stretching away NE and SE from FreckenhamThis could indicate possible trade or communication routesRoman roads underneathCouple of maps to illustrate this
  • Hotspot Map of all Coin findsMap showing the possible trade route to the NE towards the coast at Great Yarmouth
  • Hotspot Map of late period commercial and household findsMap showing the possible trade route to the SE towards the port at Felixstowe
  • Map showing possible trade routesLines show possible routes of trade or communication
  • VASLE Site AnalysisFinal piece of analysis aimed to evaluate the productivity of 22 sites identified by the 2006 projectUse buffering and intersect techniques to see how many finds fell within a 2.5 mile radius of each siteAs there is no definition of what a productive site is criteria based on the 2006 project were used. Buffer size criteria were unique to this projectProductivity would be based on whether there was an above or below average number of finds falling within an object group or time period.The numbers of object groups and time periods showing above average would indicate whether the site was productive or not
  • Map showing VPS sites and buffersLocations of 22 sites 17 in Norfolk 5 in Suffolk
  • VASLE Site Analysis Results7 out of the 22 sites were deemed to be productive as a result of the buffering processFurther analysis of the finds within each buffer gave an indication of when and how each of the sites developedMost developed as time went on others started strong and weakened over timeHigh quantities of some object groups indicated possible functions of some of the sitesCoins indicated trade or tax collection functions such as in the town of FreckenhamIt also helped assign timings to the possible trade routes
  • Did we achieve our objectives?The project has proved that you can successfully use spatial analysis techniques on complex archaeological datasetsIt’s shown that you can reveal which areas were important and when as well as which towns played a key role The spatial analysis techniques complimented each other helping build a bigger picture for the projectSet the scene for further analysis either through fieldwork or other GIS analysis
  • Thanks for listening any questions?

Masters Dissertation - Presentation Masters Dissertation - Presentation Presentation Transcript

  • Spatial Analysis of East AnglianAnglo Saxon Archaeology
    Edward Kemp
    MSc Applied Geographical Information Systems
    Wednesday 7th September 2011
  • Presentation Structure
    Provide a background to the project.
    Explain the projects aims and objectives.
    Introduce the study area and data.
    Briefly explain the methods used.
    Share some results and conclusions.
    Did we achieve our objectives?
    I mages from: Culture 24 www.culture24.org.uk
  • Background
    Dissertation topic inspired by a project from 2006 by John Naylor at Ashmolean Museum in Oxford
    Uses of an online database of archaeological finds found using metal detectors by members of the public
    Started in 1997 now has over 450,000 unique objects on the searchable database
    Run by the Portable Antiquities Scheme (PAS) in conjunction with the British Museum
  • Aims and Objectives
    Explore archaeological data using spatial analysis techniques
    Explore distributions and patterns in the data with the aim of better understanding the development of Anglo Saxon East Anglia
    Assess the ‘productivity’ (level/type of activity) at previously identified archaeological sites using spatial analysis techniques and the PAS database
    Combine the results highlighting areas that could be investigated further through fieldwork or additional spatial analysis
  • Study Area
  • Preparing PAS Data
    Remove inconstancies in data
    Remove any unclassified or incomplete items
    Object types assigned object groups
    Finds assigned a period in Anglo Saxon history
    Plotted using easting and northing grid references
  • Assigning Categories
    Object groups and time periods were assigned to each item
    One of six object groups were assigned to each item:
    Clothing (buckle, hooked tag, sleeve clasp)
    Coins (single coins, ingots)
    Horse Items (stirrup, strap ends, bridle bit, harness mount)
    Commercial and Household: (spoon, bowl, tweezers, hinge, gaming piece)
    Jewellery (brooch, ring, bracelet, bead, armlet)
    Pins (hair pin, linked pin)
    One of three time periods were also assigned to each item:
    Early: 400 – 600AD
    Middle: 601 – 800AD
    Late: 801 – 1066AD
    Each object group was broken down further by time period
  • Spatial Analysis Techniques
    Average Nearest Neighbour:
    Compare the distance between feature locations
    Global Morans I:
    Compares the distance between feature values
    Are similar or dissimilar values clustering
    Getis – Ord G* Hotspot Analysis:
    Identifies whether features with high values or features with low values tend to cluster together in a study area(forming ‘hot’ or ‘cold’ spots)
    All results were accompanied by a level of significance
    Either 99%, 95% or 90%
    Use to accept or reject the null hypothesis
    Points/ values were located as a result of a random process
  • Average Nearest Neighbour Findings
    Results gave an insight into the distribution of some object groups
    Overall finds showed less tendency to cluster over time
    Jewellery items showed the highest tendency to cluster
    Commercial and household items the least
    Both at a 99% confidence level
  • Global Morans I Findings
    Provided slightly different picture
    Finds again showed less tendency to cluster of time
    Clothing items showed the highest tendency to cluster at a 99% confidence level
    Commercial and household the least but with no confidence level attached
  • Getis –Ord G* Hotspot Analysis Findings
    No statistically significant cold spots were found
    Significant hotspots move around the study area over time
    The central area around the town of Hoxne seems to be important in the early – middle period
    The shift is then to the north and west of Norfolk
    Patterns in two of the maps indicate possible trade or communication routes – aid of underlying OS map
    One running from the VASLE site at Freckenham NE to Great Yarmouth and the other running SE to Felixstowe
  • All
    Coin Finds
  • Commercial
    and Household
    Late Period
    Finds
  • Possible trade
    routes
  • VASLE Productive Site (VPS) Analysis
    Aim to assess the productivity of the 22 VPS using buffering and intersection functions
    No specific definition of what a productive site is so buffer size and criteria were based on the 2006 project:
    2.5 mile buffer chosen because of:
    Dispersed settlement pattern
    Increased distribution through trade as time goes on
    Take into account disposal and accidental loss
    Productivity would be assessed by counting the number of object groups and time periods returning above average numbers of finds from the PAS dataset
    More than 4 out 6 object groups AND 2 out of 3 time periods and the VPS would be deemed productive throughout the Anglo Saxon period
  • 22 VPS
    + 2.5 mile buffers
  • VASLE Productive Site (VPS) Buffer Analysis Results
    7 out of 22 sites were deemed to be productive as a result of the spatial analysis process
    Gave an indication as to when some sites developed
    Gave an indication of each sites primary function
    Pin manufacture, tax and trade.
    Timings for the possible trade routes could be given, northern route earlier, southern route later
  • Conclusions – Did we achieve out objectives?
    Spatial analysis techniques can be successfully used in conjunction with complex archaeological data
    Patterns are revealed that can tell a story about a town or area
    These would not be apparent using purely visual inspection
    Each technique complimented each other
    The project has set the scene for future possible GIS projects
  • THANK YOU
    FOR LISTENING
    ANY QUESTIONS?