A GIS open source application for cost distance modelling for site catchment analysis of prehistoric sites
Year: 2023
Type: conference-paper
Abstract: Archaeological research employing least-cost analysis and Geographic Information Systems (GIS) has increased over the past decade. In the Portuguese archaeological research, several approaches were applied to estimating the cost-distance, describing the relationship between travel distances and their associated costs. Archaeologically, Site Catchment Analysis (SCA) consists of a territorial analysis of the area surrounding a site that its inhabitants can exploit in terms of natural resources. There are a few generic least-cost path plugins available in QGIS software, but none of them incorporates an archaeology-specific methodology, as many GIS users combine QGIS algorithms with ArcGIS tools to achieve the desired results. This work’s objective is to automate the cost-distance modelling for SCA at archaeological sites by creating a QGIS open-source application. Tobler's hiking function and a set of geographic information – slope, aspect, rivers - were implemented in the application, allowing the evaluation of archaeological hypotheses in a specific research study area. The application was tested for Northwest Portugal in a region comprised of the districts of Porto, Braga, and Viana do Castelo, where an inventory of archaeological sites from the second millennium BC until 500 BC was compiled. The creation of SCA maps for archaeological sites enabled the detection of a few differences in the composition of one hour walking territories. This suggests the existence of a set of similarities between these territories, despite their different topographic histories. For archaeologists, the application has benefits for automating the creation of specific maps and streamlining the process of making these models.
DOI: 10.1117/12.2678993
Authors: Lia Duarte, Sofia Godinho, Alberto Gomes, Sérgio Rodrigues, Ana Cláudia M. Teodoro
Language: English
Subfield: Archeology
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4387770959