Detecting Associations between Archaeological Site Distributions and Landscape Features: A Monte Carlo Simulation Approach for the R Environment
2. Research Background: Understanding Archaeological Site Distributions
2.2. Monte Carlo Simulation
3. Materials and Methods
3.1. Study Area
3.2. Study Aims
- The location of the Palaeolithic finds is, in many cases, uncertain.
- Many quarries are small—the fairly low precision of the recording of findspots means that finds might not coincide with the mapped location of the quarry from which they probably came.
- Not all quarrying activities are recorded on the maps.
- The fourth edition map was only partially available in digital form at the time the digitizing work was undertaken. Many tiles and areas of this map were missing from the dataset used, so later quarries are likely to have been omitted.
- Not all Palaeolithic sites are directly derived from quarries. Some have arrived in the hands of collectors as a result of natural processes, such as erosion.
- Quarries have been digitised without consideration for their depth or purpose, as determining this information would have been unreasonably time-consuming. Consequently, the dataset includes a number of quarries which do not impact any Pleistocene deposits (e.g., hilltop chalk quarries).
3.3.1. Georeferencing and Digitising of Quarries
3.3.2. Adding Buffers to Account for Uncertainty
3.3.3. Random Sites Generation
3.3.4. Overlay and Frequency Determination
3.3.5. Script Programming
5. Concluding Discussions
Conflicts of Interest
Appendix A. Technical Description of the MCSites Tool
Appendix A.1. Data Import and Analysis Preparation in R
Appendix A.2. Generation of Random Points Inside Study Area
Appendix A.3. Buffering Sites and Random Points to Account for Uncertainty
Appendix A.4. Overlay Features Layer with Sites and Random (Simulated) Sites
Appendix A.5. Run Monte Carlo Simulation
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|Run Number||Number of Simulations||Mean Frequency||Median||Mode||Min||Max||Recorded Sites||Uncertainty (m)|
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Hewitt, R.J.; Wenban-Smith, F.F.; Bates, M.R. Detecting Associations between Archaeological Site Distributions and Landscape Features: A Monte Carlo Simulation Approach for the R Environment. Geosciences 2020, 10, 326. https://doi.org/10.3390/geosciences10090326
Hewitt RJ, Wenban-Smith FF, Bates MR. Detecting Associations between Archaeological Site Distributions and Landscape Features: A Monte Carlo Simulation Approach for the R Environment. Geosciences. 2020; 10(9):326. https://doi.org/10.3390/geosciences10090326Chicago/Turabian Style
Hewitt, Richard J., Francis F. Wenban-Smith, and Martin R. Bates. 2020. "Detecting Associations between Archaeological Site Distributions and Landscape Features: A Monte Carlo Simulation Approach for the R Environment" Geosciences 10, no. 9: 326. https://doi.org/10.3390/geosciences10090326