ArcheoFOSS 2022
The potential of open lidar datasets for thinking about past mobility

Dimitrij Mlekuž Vrhovnik
Oddelek za arheologijo/Department of Archaeology Filozofska fakulteta/Faculty of Arts Univerza v Ljubljani/University of Ljubljana, Slovenia

Panel: Moving in the past: open solutions for data set design, spatial analysis and (spatial) statistical methods to investigate movement in Antiquity.

With the increased availability of country-wide lidar datasets, a new source to explore past mobility patterns can be employed. Although available under different permissive licences, these datasets provide point cloud data, which allow processing using open source tools and developing digital terrain models for specific purposes.

In the presentation, I explore the potential of open lidar datasets in detecting large-scale mobility patterns across landscapes. Lidar reveals landscapes previously hidden below a woodland canopy in fantastic clarity. One of the most ubiquitous features of the woodland floor is holloways or sunken lanes. I want to explore the potential of large-scale holloway data derived from open lidar datasets for studying past mobility.

In Europe, but also in the Near East, with millennia-old inhabited landscapes that highlight long-term relations between humans, domestic animals and landscapes, holloways are ubiquitous landscape features. They form wide interleaved corridors of paths running on the ridges and avoiding boggy valley floors. They represent traces of long-term human and animal movement as they walk across the landscape.

This movement is not just about individual journeys but about long-term patterns that emerge from routinised travel. These spacetime patterns, especially when viewed over extensive time frames, can be described as flows.

These flows move people, animals, things and substances into new positional and relational contexts with other things and create new material encounters, allowing different flows to emerge.

In this way, the large-scale holloway data derived from lidar datasets can be seen as traces of the past landscape-scale activity systems, stable, multi-scale spatio-temporal patterns formed from intertwined allocation of time among practices in space.

It is interesting to explore such patterns as the situated topologies, which enable and frame performances in a landscape. Movement is a way of orienting in the world and, thus, particular forms of movement have different impacts.

Those patterns enable the study of morphogenesis of complex flow patterns. Studying these patterns is crucial to future mobilities research as it intersects with scientific research into dynamical systems. It also suggests that when we study landscape and movement, we must move beyond predefined, planned network topologies and consider fluid, surprising, emergent forms of large-scale movement.

Open lidar datasets, processed to allow extraction of holloways, are a primary proxy for the past mobility patterns; those data can be used to study, verify and modify available mobility modelling algorithms and approaches in archaeology.


This text is released under CC BY-ND 4.0 International license. Copyright Dimitrij Mlekuž Vrhovnik 2022