Modelling of Pathways and Movement Networks in Archaeology: An Overview of Current Approaches

Abstract

This chapter presents and discusses current approaches and trends in computer-based modelling of pathways and movement networks in archaeology. After an introduction to the theoretical concepts involved, we present a state of the art of methodologies applied for reconstructing pathways and movement in ancient landscapes and discuss the various difficulties in using these methods as well as the most important technical hurdles involved. The problems of integrating optimal pathfinding algorithms with 'softer' socio-cultural variables are highlighted, as well as the limitations of modelling connections between places using least-cost path techniques. Network analysis reconstruction and analysis approaches are then reviewed as tools to better understand the overall structure of movement and communication in ancient landscapes. It is concluded that, while the potential of current approaches for understanding ancient movement is considerable, improvement is still needed in three main areas: the integration of approaches, sensitivity analysis and validation, and the theoretical underpinning of models of ancient movement.

Developing FAIR Ontological Pathways: Linking Evidence of Movement in Lidar to Models of Human Behaviour

“…The complexity of the evidence observed in lidar data, and the reconsideration of the concepts and models of movement prompted by it, call for a new approach that takes in a broader set of evidence. This approach must go beyond the kind of modelling, essentially based on a cost-benefit hypothesis, which we generally use to simulate invisible or no longer physically extant paths (Verhagen, Nuninger & Groenhuijzen 2019).…”

“…Models of the physical terrain, locations of predefined travel routes or corridors, locations of starting points and destinations, and various models of social and cognitive constraints on and motivations for movement are typical inputs (Bell & Lock 2000;Whitley et al 2010;Murrieta-Flores 2014). Our review of dominant computational models of movement (Verhagen, Nuninger & Groenhuijzen 2019), summarized above, highlights the significant gap between the expected inputs and outputs of these models. These inputs and outputs reflect, on the one hand, data that describe archaeological evidence for movement and, on the other hand, reflect what we expect according to our theoretical models of practices and activities.…”

The Role of Modeling and Synthesis in Creative Mitigation

“…Path proximity and use intensity proved important in predicting the location of resource processing sites and temporary camps that may have been used during travel between springs. In a similar fashion, historical-period transportation routes and route intersections can be useful in predicting historical period site location, as transportation networks often influence the spatial configuration of (Hardesty 1988;Heilen et al 2015;Verhagen et al 2019).…”

Assessing the Impact of Including Traversal across Slope on Least Cost Path Accuracy: A Roman road case study

“…LCP analysis has been implemented in multiple GIS software such as ArcGIS and GRASS (Surface-Evans and White, 2012). Although frequently used for the modelling of past movement (Beyin et al, 2019;Gustas and Supernant, 2017;Kealy et al, 2018;Li et al, 2019;Verhagen and Jeneson, 2012), methodological issues are often ignored and can lead to the model not realistically representing the cost of movement through a landscape (Herzog, 2014a;Surface-Evans and White, 2012;Verhagen et al, 2019). Most notably, the spreading algorithm, which identifies the lowest cost from destination to origin, is implemented differently in different LCP software, resulting in LCP results that may not be comparable (Gietl et al, 2008;Herzog, 2013;Herzog and Posluschny, 2011).…”