BEGIN seminar – Dr David McArthur

Date: 18 February 2020
Time: 15:00-16:00
Venue: School VI

Understanding and promoting cycling using crowdsourced data

Cycling is increasingly seen as a way of dealing with a variety of social problems: from dealing with the climate emergency to improving public health. Unfortunately, in the UK cycling is not a common mode choice. Governments have made money available to encourage more people to get on their bikes. A large portion of this money has been spent on new infrastructure. However, it hasn’t always been easy to evaluate whether this is effective due to a lack of appropriate data. In recent years, the proliferation of smartphones and activity-tracking apps such as Strava has made new, detailed mobility data available to researchers. In this talk, I will present some of the ways we have been making use of this data at the Urban Big Data Centre (UBDC).


David McArthur is Senior Lecturer in Transport Studies and Associate Director of the Urban Big Data Centre at the University of Glasgow. An economist by training, his current work looks at how new and emerging forms of data can be used to better understand cities; with a particular focus on the promotion of walking and cycling as modes of transport.



BEGIN seminar – Vanessa Brum-Bastos

Date: 21 January 20120
Time: 15:00-16:00
Venue: School VI

Movement analytics: using geospatial temporal data to understand behavior

Movement analytics has been boosted in the recent years by the ubiquitous availability and quality of spatio-temporal data on people and wildlife. Movement ecology and human mobility are the two main application areas of movement analytics, the first one aims to understand wildlife behavior for conservation purposes mostly, whilst the second one looks at human movement to improve transportation and urban planning, particularly in the context of smart cities. Location-based services and GPS trackers are constantly creating massive data-sets on individuals’ locations at specific timestamps. These data-sets can be analyzed to extract movement patterns, which in conjunction with contextual data can lead to a further understanding of behavior.  In this seminar, Dr Brum-Bastos will present her work on the influence of the weather on human movement in Scotland – UK, bicycling ridership patterns in San Francisco – US and the impact of e-scooters in Tempe – US.


Vanessa Brum-Bastos is a Research Fellow at the School of Geography and Sustainable Development at the University of St Andrews. Currently, she works with Dr Urska Demsar on the project Uncovering the Mechanisms of Migratory Bird Navigation with Big Data Analytics funded by the Leverhulme Trust. Dr Bastos research focuses on the development and implementation of Context-Aware Movement Analysis (CAMA) to further understand behavior from movement data. More specifically, she is interested in combining movement data with environmental and socio-economic variables to understand how different factors can influence human mobility and wildlife behavior. This knowledge is critical for planning equalitarian sustainable transportation systems, as well as designing biodiversity conservation plans.



BEGIN seminar – Theoni Photopoulou

Date: 17 December 2019
Time: 15:00-16:00
Venue: School VI

Using time series models to make biological inferences from animal tracking data

Animal location data can be thought of as time series of individual animal behaviour. This type of animal movement data can be effectively analysed using statistical models for time series to help understand what the animal is “doing”. One class of time series models that has become popular for analysing animal tracking data are hidden Markov models (HMMs). These models fall under the umbrella of state-space models, where we assume that the time series of observations is generated by an underlying “hidden” time series of system states, and that the observations and underlying states are linked in some way. The dependence structure between the observations and underlying, unobserved states allows us to make inferences about the unobserved time series, from the observed one. I will show examples of what we can learn about animal movement data using HMMs, based on two case studies from marine systems: acoustic detections of great white sharks and satellite locations of Weddell seals.


Theoni Photopoulou is a Newton International Fellow in the School of Biology. She has a background in marine ecology and statistics and splits her time between the Scottish Oceans Institute and the Centre for Research into Ecological and Environmental Modelling.



GIS Day 11/11/19

GIS Day @ St Andrews
When: Mon. Nov 11, 2019
13:00 – 15:00
Where: SMC:T201 – Lecture Room 1, St Mary’s College, South Street


GIS in the energy industry (Joe Marple, Graduate
Environmental Consultant, Xodus Group, Aberdeen)

Mapping a PhD in bird navigation (Beate Zein, PhD
Candidate, School of Geography & SD, St Andrews)

From paper‐sheet to field data collection – ArcGIS for
Developers (Fernando Benitez, Postdoctoral Researcher,
School of Geography & SD, St Andrews)y

Geospatial data in the wild: how small companies with big
data approach GIS (Carson Farmer, Open Source
Developer,, Victoria, Canada)

See also:

GIS Day Poster 2019

BEGIN seminar – Christina Fell

Date: 19 November 2019
Time: 15:00-16:00
Venue: School VI

Automatic detection of animals from aerial photography

Aerial photography is increasing available to ecological researchers from a variety of platforms such as drones, light aircraft and satellites. This generates large amounts of data which is usually examined manually by researchers to detect and locate the animals. This is a time consuming process and often a bottleneck in the pipeline that prevents these data sources being used more widely. Modern computer vision techniques hold out the hope that this could now be automated. I will discuss a dataset that I have created to test algorithms for detection of animals in aerial imagery. I have applied classical computer vision and machine learning techniques to the dataset as well as convolutional neural net approaches. The results of these techniques on the dataset will be presented. The results are now approaching human accuracy for recall, now the focus is on reducing the number of false positives. The location of the animals detected can then be used to model the spatial distribution of the animals over large areas of land.


Christina Fell is in the final year of her PhD in the School of Mathematics and Statistics at St Andrews. She is jointly supervised by Monique Mackenzie from the School of Mathematics and Statistics and David Harris-Birtill from the school of Computer Science.



BEGIN seminar – Miguel Nacenta

Date: 15 October 2019
Time: 15:00-16:00
Venue: School VI

Maps, Space and the 2D Plane from the Data and User Interface Perspective

The 2D plane underpins most displays of information and therefore most of the ways in which interface designers and data analysts can dynamically represent information. As a user interface and information visualization designer/researcher I encounter the 2D plane often as a necessity and sometimes as an opportunity to enhance human cognitive processes. Maps, who are the original example of use of the 2D plane to represent information serve often as inspiration.

In this talk, I will discuss some of my most exciting encounters with the 2D plane and maps, and reflect on their deeper affordances to support thinking and understanding. I hope also to engage in conversation with you in the audience about what maps and the 2D plane mean for you and how you use them.


Miguel Nacenta is a Senior Lecturer at the School of Computer Science, University of St Andrews, and a co-founder of SACHI, the St Andrews Human-Computer Interaction group. His work has appeared, among other, in, Fast Co.Design, the MIT Technology review, and the New Scientist. He is generally interested in making everyone able to think better and gain a better understanding of the world through new types of interactive media that allow people to leverage collaboration with computers.

BEGIN seminar – Dr Jan Kropáček

Date: 2 July 2019
Time: 15:00-16:00
Venue: Forbes room, Irvine Building

Title: Remote sensing of environmental change in mountain areas


The changes in temperature and precipitation patterns and human intervention of different types are changing the face of mountains at an unprecedented speed. Remote sensing provides us with periodic, unbiased information on a global scale with steadily improving quality.

On the Tibetan Plateau changes in glacier balance, oscillation of lake levels, floods and landslides are a consequence of such development. Relying on remote sensing, down-wasting of Tibetan glaciers could be estimated by satellite altimetry on a regional scale. An analysis of snow cover dynamics by optical medium resolution data from MODIS resulted in new knowledge about lake effect and biennial behaviour of snow cover in the drainage basin of sacred Nam Co lake one of the largest lakes in Tibet. Furthermore, a recurrent glacier lake outburst flood in Limi Valley was analyzed and better understood.

In the Ethiopian Highlands, slopes formed by rift development, volcanic activity, and fast river incision are heavily shaped by landsliding. Valuable information about their dynamics can be derived from aerial photographs from multiple aerial surveys which were initiated already in 1936 during the Italian occupation of the country. Investigation of two remarkable sites of landsliding in Ethiopia by various remote sensing techniques will be presented. The first site Debre Sina landslide is located in the vicinity of the trunk road connecting Addis Ababa with Eritrea and it is the largest recent landslide in Ethiopia.  In Dessie, several large landslides are just next to its centre. Surprisingly, their timing and triggers remained unknown.


Jan Kropáček ( is a geographer specialized on remote sensing with special focus on the mountain environment. He received his Ph.D. degree from the Faculty of Sciences of Charles University in Prague. After the accession of his country to the EU, he started to work at the Joint Research Centre of the European Commission in Ispra, Italy. His research was focused on mapping of biomass in tropical Africa and wetland detection in boreal forests of Eurasia. During his postdoc stays at the universities of Tubingen and Dresden in Germany, he took part in three projects studying cryosphere and hydrological cycle on the Tibetan Plateau. His further research interests are monitoring of slope instabilities in the Ethiopian Highlands and assessment of gully erosion in semi-arid regions. Since 2016 he continues his research and teaching at the Faculty of Environmental Sciences of the Czech University of Life Sciences Prague. During his free time, he travels and climbs on sandstone towers in Bohemian Paradise and elsewhere.

BEGIN seminar – Dr Thiago Silva

Date: 14 May 2019
Time: 15:00-16:00
Venue: Forbes room, Irvine Building

Title: Embracing variability: using remote sensing and spatial data to understand ecosystem function in seasonal ecosystems

Abstract: Highly seasonal environments are often characterized by a strong coupling between environmental variation and ecosystem responses, including organism adaptations, plant phenology and productivity, and biogeochemical cycling. This tight coupling can help us quantify and forecast changes in ecosystem function caused by changes in climatic and environmental factors, as long as we can understand and quantify the responses and uncertainties associated with seasonal variability. In his talk, Dr. Thiago Silva will show some examples of his previous and current work using direct and indirect remote sensing methods and spatial variables to capture, quantify and forecast the effects of environmental variation on vegetation dynamics, ecosystem function and biogeochemical cycling, from local to regional scales, focusing on Brazilian ecosystems.


Dr. Thiago Silva has recently joined University of Stiling after being an assistant professor for 5 years at São Paulo State University (UNESP, Brazil). He started his career as an ecosystem ecologist with a strong focus on remote sensing of Amazon floodplain wetlands. Since then, his research has expanded to encompass several aspects of global change biology, including plant community ecology, plant functional ecology and biogeography/macroecology. He is particularly interested in environmental regulation of community assembly and ecosystem function, and on developing quantitative approaches that explicitly incorporate the spatial and temporal dynamics of the biosphere at multiple scales. His research often combines in-situ ecological methods with modern remote sensing, GIS and data science, leading to collaborations with landscape, community and ecosystem ecologists, phylogeographers, and applied ecologists, as well as climatologists, hydrologists, geologists and computer scientists.

BEGIN seminar – Dr Paul Holloway

Date: 11 June 2019
Time: 15:00-16:00
Venue: Forbes room, Irvine Building

From static to dynamic: Aggregating the conceptualisation of movement data better captures real world and simulated animal-environment relationships.

Habitat selection analysis is a widely applied statistical framework used in spatial ecology. Many of the methods used to generate movement and couple it with the environment are strongly integrated within GIScience. The choice of movement conceptualisation and environmental space can potentially have long-lasting implications on the spatial statistics used to infer movement-environment relationships. This study explores how systematically altering the conceptualisation of movement, environmental space, and temporal resolution affects the results of habitat selection analyses using real-world case studies and a virtual ecologist approach. Model performance and coefficient estimates were explored between conceptualisations of movement, with substantial differences found for the more aggregated representations (e.g., segment and area). Key findings from the virtual ecologist approach identified that altering the temporal resolution identified inversions in the movement-environment relationship for vectors and moves, while systematically increasing resistance to linear features (e.g., roads) was not identified for individual aggregations. These results suggest that spatial statistics employed to investigate movement-environment relationships should advance beyond conceptualising movement as the (relatively) static conceptualisation of vectors and moves and replace these with (more) dynamic aggregations of longer-lasting movement processes such as segments and areal representations.

Bio: Paul Holloway is a lecturer in Geographic Information Science and Systems in the Department of Geography and a Principal Investigator in the Environmental Research Institute at University College Cork. His research and teaching interests include using GIScience and spatial analysis to address a suite of ecological, environmental, and geographic issues. His research addresses the long-standing issue of how to incorporate movement at different spatial and temporal extents into species distribution models, how the use of volunteered geographic information and machine learning can improve spatial predictions, and how movement data and geographic context are used to understand movement processes.