2 results
Introducing the Human Factor in Predictive Modelling: a Work in Progress
- Edited by Graeme Earl, Tim Sly, David Wheatley, Iza Romanowska, Constantinos Papadopoulos, Patricia Murrieta-Flores, Angeliki Chrysanthi
-
- Book:
- Archaeology in the Digital Era
- Published by:
- Amsterdam University Press
- Published online:
- 16 February 2021
- Print publication:
- 01 February 2014, pp 379-388
-
- Chapter
- Export citation
-
Summary
Abstract:
In this paper we present the results of a study aiming at integrating socio-cultural factors into predictive modelling. So far, predictive modelling has largely neglected the social and cultural dimensions of past landscapes. To maintain its value for archaeological research, therefore, it needs new methodologies, concepts and theories. For this study, we have departedfrom the methodology developed in the 1990s during the Archaeomedes Project. In this project, cross-regional comparisons of settlement location factors were made by analyzing the environmental context of Roman settlements in the French Rhone Valley. For the current research, we expanded the set of variables with ‘socio-cultural’factors, in particular accessibility, visibility, and the effect of previous occupation, and created predictive models from this. In this way, we have developed a protocol for predictive modelling using both environmental and socio-cultural factors that can easily be implemented for different regions and time periods.
Keywords:
Predictive Modelling, Socio-Cultural Factors, Regional Comparison, Diachronic Comparison, Roman Period
Introduction
Archaeological predictive modelling has a long history of application, especially in cultural resources management (see Judge and Sebastian 1988; Verhagen 2007; Kamermans et al. 2009). Despite its popularity for archaeological heritage management, it has also been the subject of substantial criticism from academic researchers (van Leusen 1996; Wheatley 2004; van Leusen and Kamermans 2005: Kamermans 2007). The goals of predictive modelling in heritage management are the accurate and cost-effective prediction of the location of archaeological remains within a limited region. However, academic researchers are usually more interested in finding explanations of why archaeological remains are concentrated in particular parts of the landscape. Predictive modelling can be used as a tool for this purpose as well, but should be used with caution. Little attention is paid to the role of socio-cultural factors in prehistoric and historical site location choice (Verhagen et al. 2010). The result is a rather static way of modelling, in which the human factor remains unexplored. Furthermore, issues of temporality have been addressed uncritically or insufficiently. To maintain its value for archaeological research, therefore, predictive modelling needs new methodologies, concepts and theories.
Evaluating Settlement Patterns and Settlement Densities in the Villa Landscapes Between Tongres and Cologne
- Ton Derks, Nico Roymans
-
- Book:
- Villa Landscapes in the Roman North
- Published by:
- Amsterdam University Press
- Published online:
- 19 January 2021
- Print publication:
- 29 December 2011, pp 259-274
-
- Chapter
- Export citation
-
Summary
INTRODUCTION
This article focuses on the Roman settlement landscapes of the fertile loess soils between current-day Tongres (Belgium) and Cologne (Germany). The commonly presented view regarding these landscapes is that in the course of the later 1st century AD they became almost completely dominated by villa-type settlements, characterized by one or more stone-built structures. In the rare instance that a different type of rural settlement is suggested, it is not quantified, which means that there are at present no estimations of the proportion of villas to other types of rural settlement for this region. With regard to settlement density, an average density of one villa per square kilometre seems to be the general consensus for the overall area. This article aims to challenge these perceptions of the composition of the rural settlement landscape and of habitation density. Based on an extensive inventory, and combining archaeological information with spatial dimensions, a new dataset for these landscapes has been compiled which demonstrates both higher settlement densities and a much higher proportion of ‘post-built’ farms than is commonly thought.
This dataset is the result of a landscape-archaeological study that formed part of the research project ‘Roman villa landscapes in the north. Economy, culture, lifestyles.’ The aim of this study was to reconstruct and analyse the Roman landscapes on the loess soils between the Meuse and Rhine, incorporating the results of more than 150 years of archaeological activity. Although both archaeological inventories and synthesizing work have been done for the Roman landscapes in each of the three countries in the study area, reconstructions of the settlement landscape across national borders have been lacking. An all-encompassing inventory of Roman sites in the study area was therefore carried out, including the process of data categorization, to ensure a homogeneous, reliable result. A GIS was used for the registration, mapping and analysis of data. The results of the inventory, the subsequent reconstruction of the settlement landscape, and the settlement density map will be presented and analysed in this paper. I will put forward the argument that particular archaeological practices, rather than any other factor, are responsible for serious biases in current views on the composition and average settlement density of Roman rural landscapes in the northern provinces, and that it is possible, based on the results of recent investigations, to reconstruct different scenarios.