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Spatial Prediction: Reconstructing the “Spatiality” of Social Activities at the Intra-Site Scale

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Abstract

Predictive modelling has proved its effectiveness for landscape analysis at inter-site scales, searching for the hidden rules guiding the most probable placement of settlements. In this paper, we suggest using similar spatial models at smaller intra-site scales, to discover apparent rules in the placement of activity areas within a settlement. In so doing, the most probable placement of social activities can be predicted in terms of the statistical properties of the precise locations where artefacts and ecofacts have been observed. As predictive tools in an intra-site scale, we advocate in this paper the use of spatial interpolation techniques. Through their application to a concrete case study from Bronze Age Central Italy, the advantages and limitations of this approach are also discussed.

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Notes

  1. One hundred fifty-eight belong to macro-faunal category (Bos taurus (cattle) and Cervus elaphus (red deer) and 53 to mesofauna (Ovis vel capra sp. (caprovines) and Sus sp. (pig and wild boar).

References

  • Achino, K. F. (2016). From micro to macro spatial dynamics in the Villaggio delle Macine between XIX-XVI century BC. Unpublished PhD dissertation, Universitat Autónoma de Barcelona, Prehistory Department.

  • Achino, K. F., & Capuzzo, G. (2015). The quantification of spatio-temporal distributions of archaeological data: from counts to frequencies. Archeologia e calcolatori, 26, 59–75.

    Google Scholar 

  • Achino, K. F., Angle, M., & Barceló, J. A. (2016). Predicting the accumulative consequences of abandonment processes. Intra-site analysis of lakeside settlements. In S. Campana, R. Scopigno, G. Carpentiero, & M. Cirillo (Eds.), CAA2015. Keep the revolution going (pp. 723–731). Oxford: Archaeopress.

    Google Scholar 

  • Angle, M. (2007). Comune di Castel Gandolfo. Villaggio delle Macine. In C. Belardelli (Ed.), Repertorio dei siti protostorici del Lazio. Province di Roma, Viterbo e Frosinone (pp. 173–181). All’Insegna del Giglio: Firenze.

    Google Scholar 

  • Angle, M., Lugli, F., & Zarattini, A. (2002). Lago Albano: il “Villaggio delle Macine”. In S. Rizzo (Ed.), Roma Città del Lazio (pp. 52–56). Roma: De Luca.

    Google Scholar 

  • Angle, M., Cerino, P., Granata, G., Mancini, D., Malinconico, R., & Tomei, N. (2014). Il sito su impalcato ligneo del Villaggio delle Macine a Castel Gandolfo. In E. Calandra, G. Ghini, & Z. Mari (Eds.), Atti del Convegno “Decimo Incontro di Studi sul Lazio e Sabina” Roma, 4–6 giugno 2013 (pp. 315–318). Roma: Lavori e Studi della Soprintendenza per i Beni Archeologici del Lazio.

    Google Scholar 

  • Bailey, G. (2007). Time perspectives, palimpsests and the archaeology of time. Journal of Anthropological Archaeology, 26(2), 198–223.

    Article  Google Scholar 

  • Balakrishnan, N., & Lai, C. (2009). Continuous bivariate distributions. Berlin: Springer.

    Google Scholar 

  • Barceló, J. A., & Mameli, L. (2010). Frequency seriation and temporal order. A Zooarchaeological study. In F. Nicolucci & S. Hermon (Eds.), Beyond the artefact. Digital interpretation of the past (pp. 451–457). Archaeolingua: Budapest.

    Google Scholar 

  • Barceló, J. A., & Maximiano, A. (2012). The mathematics of domestic spaces. In M. Madella, G. Kovács, B. Berzsényi, & I. Briz (Eds.), The archaeology of household (pp. 6–22). Oxford: Oxbow.

    Google Scholar 

  • Barceló, J. A., Achino, K. F., Bogdanovic, I., Capuzzo, G., Del Castillo, F., Moitinho De Almeida, V., & Negre, J. (2015). Measuring, counting and explaining: an introduction to mathematics in archaeology. In J. A. Barceló & I. Bogdanovic (Eds.), Mathematics and archaeology (pp. 3–64). Boca Raton: CRC Press.

    Chapter  Google Scholar 

  • Barnett, V., & Lewis, T. (1994). Outliers in statistical data (3rd ed.). Chichester: John Wiley & Sons.

    Google Scholar 

  • Barton, C. M., Bernabeu, J., Aura, J. E., Garcia, O., Schmich, S., & Molina, L. (2004). Long-term socioecology and contingent landscapes. Journal of Archaeological Method and Theory, 11(3), 253–295.

    Article  Google Scholar 

  • Binford, L. R. (1978). Dimensional analysis of behavior and site structure: learning from an Eskimo hunting stand. American Antiquity, 43(03), 330–361.

    Article  Google Scholar 

  • Binford, L. R. (1981). Behavioral archaeology and the “Pompeii premise”. Journal of Anthropological Research, 37(3), 195–208.

    Article  Google Scholar 

  • Blankholm, H. P. (1991). Intra-site spatial analysis in theory and practice. Aarhus: Aarhus University Press.

    Google Scholar 

  • Brain, C. K. (1980). Some criteria for the recognition of bone-collecting agencies in African caves. In A. K. Behrensmeyer & A. P. Hill (Eds.), Fossils in the making: vertebrate taphonomy and paleoecology (pp. 108–130). Chicago: University of Chicago Press.

    Google Scholar 

  • Buonaccorsi, J. P., Elkinton, J. S., Evans, S. R., & Liebhold, A. M. (2001). Measuring and testing for spatial synchrony. Ecology, 82(6), 1668–1679.

    Article  Google Scholar 

  • Carleton, W. C., Conolly, J., & Ianonne, G. (2012). A locally-adaptive model of archaeological potential (LAMAP). Journal of Archaeological Science, 39(11), 3371–3385.

    Article  Google Scholar 

  • Carr, C. (1984). The nature of organization of intrasite archaeological records and spatial analytic approaches to their investigation. In M. B. Schiffer (Ed.), Advances in archaeological method and theory (Vol. 7, pp. 103–222). Orlando: Academic Press.

    Chapter  Google Scholar 

  • Chiarucci, P. (1985). Materiali dell’età del Bronzo nelle acque del Lago Albano. Archeologia Laziale, 7, 34–39.

    Google Scholar 

  • Chiarucci, P. (1986–88). Il “Villaggio delle Macine” nel Lago Albano. Annali Benacensi, 9, 407-419.

  • Chiarucci, P. (1995–6). Il Villaggio delle Macine sommerso nelle acque del Lago Albano. Bollettino di Archeologia Subacquea, 2-3, 176-183.

  • Chilès, J., & Delfiner, P. (1999). Geostatistics: modeling spatial uncertainty. New York: John Wiley & Sons.

    Book  Google Scholar 

  • Crema, E. R. (2015). Time and probabilistic reasoning in settlement analysis. In J. A. Barceló & I. Bogdanovic (Eds.), Mathematics and archaeology (pp. 314–334). Boca Raton: CRC Press.

    Chapter  Google Scholar 

  • Crema, E. R., Bevan, A., & Lake, M. W. (2010). A probabilistic framework for assessing spatio-temporal point patterns in the archaeological record. Journal of Archaeological Science, 37(5), 1118–1130.

    Article  Google Scholar 

  • Cressie, N. (1990). The origins of kriging. Mathematical Geology, 22(3), 239–252.

    Article  Google Scholar 

  • D’Ambrosio, E., Giaccio, B., Lombardi, L., Marra, F., Rolfo, M. F., & Sposato, A. (2009). L’attività recente del centro eruttivo di Albano tra scienza e mito: un’analisi critica del rapporto tra il Vulcano Laziale e la storia dell’Area Albana. In G. Ghini & Z. Mari (Eds.), Atti del Convegno “Quinto Incontro di Studi sul Lazio e Sabina”, Roma, 4–6 marzo 2009 (pp. 125–136). Roma: L’Erma di Bretschneider.

    Google Scholar 

  • De Smith, M., Goodchild, M. F., & Longley, P. A. (2015). Geospatial analysis. A comprehensive guide to principles, techniques and software tools (5th ed.). Leicester: The Winchelsea Press.

    Google Scholar 

  • Deravignone, L., Blankholm, H. P., & Pizziolo, G. (2015). Predictive modeling and artificial neural networks: from model to survey. In J. A. Barceló & I. Bogdanovic (Eds.), Mathematics and archaeology (pp. 335–351). Boca Raton: CRC Press.

    Chapter  Google Scholar 

  • Djindjian, F. (1988). Improvements in intrasite spatial analysis techniques. In S. P. Q. Rahtz (Ed.), Computer and quantitative methods in archaeology (pp. 95–106). Oxford: British Archaeological Reports.

    Google Scholar 

  • Dye, T. S., & Buck, C. E. (2015). Archaeological sequence diagrams and Bayesian chronological models. Journal of Archaeological Science, 63, 84–93.

    Article  Google Scholar 

  • Hassan, F. A. (1987). Re-forming archaeology: a foreword to natural formation processes and the archaeological record. In I. D. T. Nash & M. D. Petraglia (Eds.), Natural formation processes and the archaeological record (pp. 1–9). Oxford: British archaeological Series S352.

    Google Scholar 

  • Hietala, H. (1984). Intrasite spatial analysis in archaeology. Cambridge: Cambridge University Press.

    Google Scholar 

  • Hilton, M. R. (2003). Quantifying post-depositional redistribution of the archaeological record produced by freeze–thaw and other mechanisms: an experimental approach. Journal of Archaeological Method and Theory, 10(3), 165–202.

    Article  Google Scholar 

  • Hodder, I., & Orton, C. (1976). Spatial analysis in archaeology. Cambridge: Cambridge University Press.

    Google Scholar 

  • Isaaks, E. H., & Srivastava, R. M. (1989). An introduction to applied geostatistics. New York: Oxford University Press.

    Google Scholar 

  • Judge, J. W., & Sebastian, L. (1988). Quantifying the present and predicting the past: theory, method and application of archaeological predictive modeling. Denver: U.S. Department of the Interior, Bureau of Land Management.

    Google Scholar 

  • Kelly, R. L., & Thomas, D. H. (2013). Archaeology: down to earth (6th ed.). Wadsworth: Cengage Learning.

    Google Scholar 

  • Kohler, T. A., & Parker, S. C. (1986). Predictive models for archaeological resource location. In M. B. Schiffer (Ed.), Advances in archaeological method and theory (Vol. 9, pp. 397–452). New York: New York Academic.

    Chapter  Google Scholar 

  • Kvamme, K. L. (1990). The fundamental principles and practice of predictive archaeological modelling. In A. Voorrips (Ed.), Mathematics and information science in archaeology: a flexible framework (pp. 257–295). Bonn: Holos Verlag.

    Google Scholar 

  • Lancelotti, C., Negre Pérez, J., Alcaina-Mateos, J., & Carrer, F. (2017). Intra-site spatial analysis in ethnoarchaeology. Environmental Archaeology, 1–11.

  • Lindsey, J. (1995). Modelling frequency and count data. Oxford: Oxford University Press.

    Google Scholar 

  • Llobera, M. (2012). Life on a pixel: challenges in the development of digital methods within an “interpretive” landscape archaeology framework. Journal of Archaeological Method and Theory, 19(4), 495–509.

    Article  Google Scholar 

  • Lloyd, C. D., & Atkinson, P. M. (2004). Archaeology and geostatistics. Journal of Archaeological Science, 31(2), 151–165.

    Article  Google Scholar 

  • Lock, G., & Molyneaux, B. L. (2006). Confronting scale in archaeology. New York: Springer.

    Book  Google Scholar 

  • Lucas, G. (2008). Time and archaeological event. Cambridge Archaeological Journal, 18(1), 59–65.

    Article  Google Scholar 

  • Lucas, G. (2012). Understanding the archaeological record. Cambridge: Cambridge University Press.

    Google Scholar 

  • Mameli, L., Barcelò, J. A., & Estevez, J. (2002). The statistics of archaeological deformation processes. An archaeological experiment. In G. Burenhult, J. Arvidssen, & J. (Eds.), Archaeology at the interface (pp. 221–232). Oxford: Archeopress.

    Google Scholar 

  • March, J. G., & Olsen, J. P. (1986). Garbage can models of decision making in organizations. Ambiguity and Command, 10, 11–35.

    Google Scholar 

  • Maximiano, A. (2007). Teoría Geoestadística aplicada al análisis de la variabilidad espacial arqueológica intra-site. Unpublished Doctoral dissertation, Tesis doctoral, Universidat Autónoma de Barcelona, Department of Prehistory.

  • Mehrer, M., & Westcott, K. (2006). GIS and archaeological predictive modelling: large-scale approaches to establish a baseline for site location models. London: Taylor and Francis.

    Google Scholar 

  • Nobles, G. (2016). Dwelling on the edge of the Neolithic: investigating human behaviour through the spatial analysis of Corded Ware settlement material in the Dutch coastal wetlands (2900–2300 cal BC). PhD thesis. University of Groningen.

  • Oliver, M. A., & Webster, R. (1990). Kriging: a method of interpolation for geographical information systems. International Journal of Geographical Information System, 4(3), 313–332.

    Article  Google Scholar 

  • Orton, C. (2004). Point pattern analysis revisited. Archaeologia e Calcolatori, 15, 299–315.

    Google Scholar 

  • Peeters, A., Zude, M., Käthner, J., Ünlü, M., Kanber, R., Hetzroni, A., & Ben-Gal, A. (2015). Getis–Ord’s hot-and cold-spot statistics as a basis for multivariate spatial clustering of orchard tree data. Computers and Electronics in Agriculture, 111, 140–150.

    Article  Google Scholar 

  • Pielou, E. C. (1977). Mathematical ecology. New York: Wiley.

    Google Scholar 

  • Pizziolo, G., & Sarti, L. (2015). Predicting prehistory: predictive models and field research methods for detecting prehistoric contexts. Siena: Museo e Istituto Fiorentino di Preistoria “Paolo Graziosi”.

    Google Scholar 

  • Rathje, W. L., & Murphy, C. (2001). Rubbish!: the archaeology of garbage. New York: University of Arizona Press.

    Google Scholar 

  • Reno, J. (2015). Waste and waste management. Annual Review of Anthropology, 44(1), 557–572.

    Article  Google Scholar 

  • Riris, P. (2017). Towards an artefact’s-eye view: non-site analysis of discard patterns and lithic technology in Neotropical settings with a case from Misiones province, Argentina. Journal of Archaeological Science: Reports, 11, 626–638.

    Article  Google Scholar 

  • Scanlan, J. (2005). On garbage. Chicago: Reaktion Books.

    Google Scholar 

  • Schiffer, M. B. (1976). Behavioral archaeology. New York: Academic Press.

    Google Scholar 

  • Schiffer, M. B. (1987). Formation processes of the archaeological record. Albuquerque: University of New Mexico Press.

    Google Scholar 

  • Setianto, A., & Triandini, T. (2013). Comparison of kriging and inverse distance weighted (IDW) interpolation methods in lineament extraction and analysis. Journal of Applied Geology, 5(1), 21–29.

    Google Scholar 

  • Stein, M. L. (2012). Interpolation of spatial data: some theory for kriging. New York: Springer.

    Google Scholar 

  • Surovell, T. A. (2012). Toward a behavioral ecology of lithic technology: cases from Paleoindian archaeology. Arizona: University of Arizona Press.

    Google Scholar 

  • Ullah, I. I., Duffy, P. R., & Banning, E. B. (2015). Modernizing spatial micro-refuse analysis: new methods for collecting, analyzing, and interpreting the spatial patterning of micro-refuse from house-floor contexts. Journal of Archaeological Method and Theory, 22(4), 1238–1262.

    Article  Google Scholar 

  • van Leusen, M., & Kamermans, H. (2005). Predictive modelling for archaeological heritage management: a research agenda. Amersfoort: Rijksdienst voor het Oudheidkundig Bodemonderzoek.

    Google Scholar 

  • van Leusen, M., Pizziolo, G., & Sarti, L. (2011). Hidden landscapes of Mediterranean Europe. Cultural and methodological biases in pre- and protohistoric landscape studies. Proceedings International Meeting, Siena 2007. BAR International Series 2320. Oxford: Archaeopress.

  • Varien, M. D., & Ortman, S. G. (2005). Accumulations research in the Southwest United States: middle-range theory for big-picture problems. World Archaeology, 37(1), 132–155.

    Article  Google Scholar 

  • Verhagen, P. (2006). Quantifying the qualified: the use of multicriteria methods and Bayesian statistics for the development of archaeological predictive models. In M. W. Mehrer & K. L. Wescott (Eds.), GIS and archaeological site location modeling (pp. 191–216). Boca Raton: CRC Press.

    Google Scholar 

  • Verhagen, P. (2007). Case studies in archaeological predictive modeling. Leiden: Leiden University Press.

    Book  Google Scholar 

  • Verhagen, P., & Whitley, T. G. (2012). Integrating archaeological theory and predictive modeling: a live report from the scene. Journal of Archaeological Method and Theory, 19(1), 49–100.

    Article  Google Scholar 

  • Wandsnider, L. (1996). Describing and comparing archaeological spatial structures. Journal of Archaeological Method and Theory, 3(4), 319–384.

    Article  Google Scholar 

  • Whitley, T. G. (2003). GIS as an interpretative tool for addressing risk management and cognitive spatial dynamics in a slave society. In Doerr, M., &Sarris, A. (Eds.), CAA 2002. The digital heritage of archaeology. Computer applications and quantitative methods in archaeology. Proceedings of the 30th Conference, Heraklion, Crete, April 2002, archive of monuments and publications (pp. 209–215). Heraklion: Hellenic Ministry of Culture.

  • Williams, C. K. (1998). Prediction with Gaussian processes: from linear regression to linear prediction and beyond. In M. I. Jordan (Ed.), Learning in graphical models (pp. 599–621). Cambridge: MIT Press.

    Chapter  Google Scholar 

  • Zarattini, A. (2003). Il Villaggio delle Macine: indagini nel lago di Albano (Castel Gandolfo, RM). In A. Benini & M. Giacobelli (Eds.), Atti del II Convegno di archeologia subacquea. Castiglioncello, 7-9 settembre 2001. Bari: Edipuglia.

    Google Scholar 

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Acknowledgments

We are grateful to Soprintendenza per i Beni Archeologici del Lazio e dell’Etruria Meridionale, represented in this case by Micaela Angle, who allowed to study the surface layers of the archaeological context analysed in this paper. Furthermore, we are grateful to Beatriz Pino Úria and Antonio Tagliacozzo (Soprintendenza al Museo Nazionale Preistorico Etnografico “L. Pigorini”, Sezione Paleontologia del Quaternario e Archeozoologia), that firstly analysed and subdivided the archeozoological remains. We thank three anonymous reviewers who made relevant suggestions to improve the paper. Any remaining errors or misunderstandings are responsibility of the authors.

Funding

This work was supported by both the Departament d’Universitats, Recerca i Societat de la Informació of the Generalitat de Catalunya and the Spanish Ministry of Science and Innovation, through the Grant No. HAR2012-31036 and HAR2016-76534-C2-1-R. The first author also acknowledges for her grant from the Program of Formation of Investigators F.I. 2013, managed by AGAUR (Generalitat de Catalunya).

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Achino, K.F., Barceló, J.A. Spatial Prediction: Reconstructing the “Spatiality” of Social Activities at the Intra-Site Scale. J Archaeol Method Theory 26, 112–134 (2019). https://doi.org/10.1007/s10816-018-9367-1

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