The influential landscape: understanding the dynamics of rural castle siting patterns on regional and local scales in the medieval southwest c. 1066-1200

Abstract

This thesis analysed how local and regional landscapes influenced rural castle siting decisions in Norman Devon and Dorset (c. 1066 to 1200), providing the first comparative
regional study of the southwest. It utilised contemporary historical texts and landscape archaeological evidence to establish the local political, social, and economic frameworks of six case studies (Lydford Norman Ringwork, Hembury, Coldridge, Cranborne, East Chelborough, and Shaftesbury). These frameworks allowed this thesis to contextualise each case study’s importance as an individual site within its surrounding landscape and community, thusallowing this thesis to explore why specific locations were selected and how perceptions of the new castle community were understood by local inhabitants and travellers. Additionally,these contexts allowed this thesis to computationally generate and model theoretical environments using GIS and LiDAR. These models allowed me to test and demonstrate the benefits of using Least-Cost Path analyses as a means of supplementing medieval road and routeway data, furthering our understanding of what topographical features encouraged movement to and from castle locations. In generating these models, this thesis drew uponprevious landscape studies to determine and evaluate how movement, accessibility, and visibility within local landscapes influenced castle-siting patterns. Further, these contextual landscape models were compared on local and regional scales and revealed patterns in siting decisions within the southwest of England. These patterns ranged from castle builders deliberately siting within locations that visually controlled local resources, allowing castle builders to generate targeted intervisibility with local inhabitants of rural towns, and allowing castle builders to use the local topography to promote the newly established castle community to various audiences to elicit specific emotions and attitudes.

Date of Award	2024
Original language	English