Evaluation of LiDAR Visualisation Techniques within the National Scenic Area of Orkney

Student thesis: Master's ThesisMaster of Research (awarded by UHI)


This thesis evaluates visualisation techniques in the analysis of Aerial LiDAR Survey (ALS)
derived digital elevation models (DEMs) within the National Scenic Area (NSA) of Orkney
which covers 244 km2 and incorporates the |UNESCO World Heritage Site, The Heart Of
Neolithic Orkney. To date there has been no significant analysis nor interpretation of this
LIDAR data for this region as a whole. Previous research (e.g., Stular et al. 2012) has
demonstrated the potential of visualisation techniques which use diverse analytical
approaches, such as Slope Analysis, Aspect Mapping, PCA, etc. to enhance topographic
mapping and recognition of archaeological features at a variety of scales from the individual
site to the wider landscape. The current focal point of research in this field centres on the
development of better algorithms and filters to enhance the processing of the raw LiDAR
data prior to visualisation (Štular et al 2020, 2021). The primary goal of this study is the
evaluation of the various visualisation techniques themselves not only within a distinct
landscape such as Orkney, but across diverse landforms within that landscape, such as low
lying agricultural land and coastal fringes, hillside pastoral land uncultivated uplands. This
research aims to not only enhance our knowledge of the archaeological features and remains
within the National Scenic Area of Orkney, but will also establish, through the creation of
the digital landscape, a new resource, prospection techniques and methodological
developments for current and future researchers. The development of a specific methodology
for the visualisation of LiDAR data across the diverse landforms of the Orcadian landscape
is one which it is envisioned could have wider applications both within the field of airborne
LiDAR survey data visualisation and analysis and as an aid in the creation of a synthesis of
remote sensing prospection techniques and methodologies utilising LiDAR, geophysical
survey, aerial photography and multi spectrum photography.
Date of Award10 Jan 2023
Original languageEnglish
Awarding Institution
  • University of the Highlands and Islands
SupervisorIngrid Mainland (Supervisor) & James Moore (Supervisor)

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