Mapping the possible occurrence of archaeological sites by Bayesian inference

Finke, Peter; Meylemans, Erwin; Wauw, Johan Van de

doi:10.1016/j.jas.2008.05.004

Cited by 37 publications

(20 citation statements)

References 21 publications

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“…Evidently, expert knowledge is to some extent based on field data as well, but it may originate from different geographical areas and is usually of a more informal kind.  Mixed approaches are also thinkable (Finke, Meylemans, & Van de Wauw, 2008), e.g. where experts identify the geographic attributes that are of presumed relevance, but the classification of continuous values (e.g.…”

Section: Methods Predictive Modellingmentioning

confidence: 99%

“…Optimally, expectation maps are verified with independent field observations before publication. Depending on the statistical part of the inference, it may be possible to display only those parts of the map that are strongly supported by evidence (Finke, Meylemans, & Van de Wauw, 2008), which may be wise in a politically sensitive context.…”

Section: Methods Predictive Modellingmentioning

confidence: 99%

“…In the case study at hand, we apply a mixed approach to predictive modelling with Bayesian inference to typical combinations of environmental attributes ("strata") as described by Finke, Meylemans & Van de Wauw (2008). This is done for the following reasons: (i) the data configuration is geographically scattered and clustered by surveyed fields.…”

Section: Methods Predictive Modellingmentioning

confidence: 99%

“…An inventory of the collected data (Sergant, Crombé & Perdaen, 2009) shows a geographical and chronological discontinuous site-distribution, possibly implicating an intermittent population and exploitation of the region during prehistory (Crombé & Verbruggen, 2002;Crombé, Perdaen & Sergant, 2008). As stated above, a mixed approach to predictive modelling (Finke, Meylemans, & Van de Wauw, 2008) was used to test if these observed occupational patterns are confirmed, based on predefined biophysical attractors and present data.…”

Section: Predictive Modellingmentioning

confidence: 99%

“…This information was combined with present-day full-cover auxiliary information on various attributes, such as topography, slope, wetness index, wind exposure, visibility, distance to open water, natural drainage class and texture class. For more and detailed information on the different attributes and the production of these predictor grids, we refer to Finke, Meylemans, & Van de Wauw (2008). Fig.…”

Section: Predictive Modellingmentioning

confidence: 99%

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On the use of integrated process models to reconstruct prehistoric occupation, with examples from Sandy Flanders, Belgium

et al. 2010

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A major problem in palaeolandscape reconstruction is that basic data useable for inference are scattered in both the temporal and spatial sense. To improve the understanding of occupational patterns by means of landscape reconstruction methods, we propose the application of different process-models in the soil-water-landscape reconstruction in an interdisciplinary approach. These process-models include a digital elevation model, a hydrological model, a pedogenesis model and a land evaluation model. Due to the multiple disciplines involved, no single model can be used but a model framework is defined in which the various discipline-specific models are integrated. In this paper, each of these models is explained and illustrated for a case-study in Flanders (Belgium) and difficulties occurring when integrating the different models, e.g. grain, extent, coverage, are discussed.

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Section: Methods Predictive Modellingmentioning

confidence: 99%

Section: Methods Predictive Modellingmentioning

confidence: 99%

Section: Methods Predictive Modellingmentioning

confidence: 99%

Section: Predictive Modellingmentioning

confidence: 99%

Section: Predictive Modellingmentioning

confidence: 99%

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On the use of integrated process models to reconstruct prehistoric occupation, with examples from Sandy Flanders, Belgium

et al. 2010

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Reconstruction of a Palaeosurface and Archaeological Site Location in an Anthropogenic Drift Sand Area

Schneider

Hirsch

Wechler

et al. 2017

Archaeological Prospection

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Knowledge of the position of archaeological remains in the surface relief provides important basic information for archaeological survey design and interpretation. Geomorphological processes in (pre)history may have resulted in a modification of the local relief around archaeological sites, especially in areas that are prone to sediment erosion and relocation, such as sheet sand and dune landscapes. In this study, we reconstructed and analysed the palaeorelief of an archaeological excavation site in an inland dune area in southern Brandenburg, Germany. The remains of two Mesolithic sites were documented in the archaeological excavations and found to be associated with a buried soil horizon. To gather information on the relief of the buried soil surface, we used a combination of sedimentological and pedological profile descriptions along archaeological survey trenches and geophysical prospection with ground penetrating radar supplemented with microdrone photography and photogrammetry, global positioning system (GPS) surveys, and analysis of LiDAR‐based elevation models. A digital elevation model of the buried surface was generated and analysed using a geographical information system (GIS). A comparison of the palaeosurface model with the recent surface elevation model shows that sand remobilization resulted in a considerable reshaping of the relief. Further, an analysis of the buried surface model shows that the relief position of the two archaeological sites in the study area was considerably more prominent in relation to the corresponding buried soil surface than in relation to the recent surface morphology. The results affirm the significance of Holocene sediment relocation for the local surface morphology and the importance of considering such relief modifications in archaeological surveys. Copyright © 2017 John Wiley & Sons, Ltd.

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Complex spatial networks in application

Evans

2010

Complexity

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The last five years has seen a considerable growth in the application of graph and network theory to ''realworld'' networks. Many of these networks are ''spatial'' in that their form and dynamics are limited by the distance between nodes in Euclidian space. This paper reviews some of the advances in the analysis of such realworld networks, highlights the continuing difficulties involved, and points to areas that need further work before a network analysis can become a standard field of application for those wishing to understand and predict real-world systems.

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Mapping the possible occurrence of archaeological sites by Bayesian inference

Cited by 37 publications

References 21 publications

On the use of integrated process models to reconstruct prehistoric occupation, with examples from Sandy Flanders, Belgium

On the use of integrated process models to reconstruct prehistoric occupation, with examples from Sandy Flanders, Belgium

Reconstruction of a Palaeosurface and Archaeological Site Location in an Anthropogenic Drift Sand Area

Complex spatial networks in application

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