Disha NEET Physics Guide for classes 11 and 12.pdf
Prospection, Prediction and Management of Archaeological Sites in Alluvial Environments
1. Prospection, Prediction and Management
of Archaeological Sites in Alluvial
Environments
Keith Challis, Mark Kincey and Andy J Howard,
IBM Vista, University of Birmingham
U B
2. Outline
• Study Areas
• Prospection
• Assessing Preservation
• Predictive Management
• Critique
3. Study Areas
Three, c.300km2
study areas
• MTV Derbyshire
• MTV Newark
• LTV Gainsborough
30k ha terrace
35k ha floodplain
144 SAM
11,222 HER records
2254 Aimee (NMR) records
10. Prospection
Airborne Lidar
• 3D record of topography at
very high resolution
• Systematic survey by
Environment Agency
• Upstanding and buried sites
• Assessment of preservation
• Change detection (multi
temporal survey)
14. Assessing Preservation
Airborne Lidar Intensity
• NIR reflectance enhanced
detection of vegetation
and soil properties
• Not a robust indicator
• No systematic collection
• Much work to be done
17. Problem
• Information on heritage assets resides in
expert hands
• Issues of availability / confidentiality
• Discrete, not continuous record
• Articulated need for “red flag” mapping
• How to achieve this without alienation of
some stakeholders
18. Goals
• To provide interpreted
information to non-expert
users
• Models rooted in
knowledge base
• Not to usurp the HER as
a source of data or to
undermine curatorial
prerogative
19. Approach: User-focused
• Understand what users
need, how they think and
work
• Model the knowledge-
based approach of expert
users “topsight” (Gelernter
1992)
• Presentation of results
structured to fit the real-
world and in a user friendly
medium
20. Approach: Simplify
• Inductive (data driven)
rather than deductive
(theory driven)
• Simplify and summarise
(the detail is in the HER)
• Validate through user
feedback (rather than test
and quantify)
21. Approach: Model Objectives
The completed models will provide per parcel scores for:
• The predicted archaeological potential of all land parcels.
• The aggregate bearing potential and value of all land parcels.
• The susceptibility of individual land parcels to field evaluation
techniques.
• The likely physical condition of buried cultural remains.
• The risk of encountering buried waterlogged organic remains.
• The level of impact that different forms of extraction may have on
the archaeological record
• The importance of archaeology in the light of regional priorities.
• The likely mitigation needs in the light of PPG 16 guidance
22. Method: Predictive Models
• Classic predictive
modelling
• Big, empty,
heterogeneous areas
(2500km2 /
21 sites)
• Assess and weigh
environmental factors
• Weights inform model
23. • Such models are
inappropriate for the
TV
• c. 40% of land parcels
contain a record
• Eg. Newark, 1254
parcels out of 5012
Method: Predictive Models
24. Method: Our Data Model
• OS MasterMap® as a
spatial framework
• Raster based GIS
models
• 50m grid (200k cells)
25. Method: Model Building
• Source data is rasterised
• Simplified scores are
applied or extracted
• Models are based on
weighted means of
scores
• Blank areas filled using
landscape classification
and spatial modelling
Terrace: Score = 3
26. Method: Per Parcel Results
• Calculations reclassified
to 5 level scale from low
risk to high
• Aggregated model scores
devolved to level of an
OS MasterMap® TOID
• Built up parcels, water
and parcels less than 1ha
in extent excluded
29. Critique
• “Topsight” is not necessarily the same thing as predictive
modelling or risk mapping
• Modelling period based activity and intensity of activity is
problematic
• It would be possible model individual classes of
monument with clear geographic preferences (eg burnt
mounds)
• Perhaps general models are the most helpful
• The meaning of results is imprecise and open to
misinterpretation
30. Concluding Thoughts
Prospection
• Non-photographic techniques offer huge potential, but uptake issues
(availability, cost, education)
• In fact, in times of limited finances reliance on traditional techniques may
not be cost-effective
Predictive Management
• Need for strategic management of heritage assets is axiomatic
• System adoption requires clear joined-up thinking at high level
• Possible conflict with aggregate resource assessments in England
• Do we need another level of information?