Topic

Geospatial Data Science

29 January 2024

Our field of Geospatial Data Science develops methodologies to collect, evaluate, model and visualise location-based data and spatial interactions. These techniques are then used by geography, earth sciences, environmental, social, computer and information sciences, remote sensing and imagery sciences, and statistical fields.

HOW TO APPLY

Geospatial Data Science is increasingly important to develop methods that numerous fields use to manage, analyse and interpret the vast quantities of data our society produces. Spatial data is collected from apps on our mobile devices or when we tap our card at a payment terminal. Likewise, vast quantities of satellite and environmental monitoring data are collected faster than they can be analysed. The unprecedented access to high resolution spatial data has revolutionized geospatial knowledge and application domains.

The Geospatial Data Science team at UC works to advance spatial data and methods for Earth, environmental, and social sciences through replicable analysis and modelling. We build scientific knowledge through methodical consideration of critical issues of how space is represented to inform on accuracy, uncertainty, scale and applications. We apply these considerations to spatial data from satellite, airborne, drone, and field collection as well as novel social and environmental data through GPS-enabled devices, mobile phone data, social media sources, and other applications. This work informs policy at national and international levels including the United Nations (UN) Sustainable Development Goals (SDGs).

The School of Earth and Environment | Te Kura Aronukurangi tackles a range of geospatial research questions to model human and other species’ population and movement patterns, physical processes, and human-environment interactions. SEE technical staff support airborne and fieldwork for scientific studies of glaciers and ecosystems, as well as flooding, landslides, and other types of hazard monitoring. SEE draws on geospatial technologies and data science techniques such as remote sensing, cloud-computing, modelling, spatio-temporal analysis, and data integration.

The postgraduate Geospatial Data Science programmes reflect our research by providing teaching and fieldwork experiences in these areas.

Ioannis Delikostidis, Peyman Zawar-Reza

We continually use technology to navigate in our daily lives and increasingly in virtual spaces. Ongoing work investigates human spatial cognition through mobile brain imaging with EEG (Electroencephalogram) in virtual/mixed reality and real-world situations. We aim to understand the neural correlates during various wayfinding tasks and discover methods for improving spatial skills. We assess the usability of navigation systems using immersive virtual environments and user-centred design of mobile navigation systems.

Carolynne Hultquist, Matthew Wilson

We draw on community engagement, earth observations, and physical modelling using data integration and prediction techniques for risk, vulnerability and exposure to hazards to improve decision support for humanitarian, government, and community actors. We develop techniques on flood risk with NIWA and LINZ, earthquakes with GNS Science, as well as, air quality, wildfire, radiation, climatic, and other factors. We develop methods for evaluation of geospatial data quality, representation of uncertainty, and validation as key drivers of our research that feed into policy and impact.

Vanessa Bastos, Lindsey Conrow, Malcolm Campbell, Simon Kingham

We examine human mobility, inequalities, health, and wellness to connect with policy engagement that helps to transform communities to more resilient and accessible systems. We develop and apply novel spatio-temporal methods to extract information from underutilised passively collected geospatial data, e.g., locational data from GPS tracking, smartphone applications and transactional records. We use geospatial insights and mixed methods from human geography to inform on transportation and health challenges locally and in Aotearoa.

Marwan Katurji, Peyman Zawar-Reza

We use geospatial approaches for physical geography to advance understanding of weather processes at the continental, regional, and very local scale. We incorporate observational data from weather stations, satellite, drone-based infrared imagery, and numerical modelling to understand complex dynamical processes in the troposphere. We engage in applied research in wind turbulence for wind energy applications, air pollution dispersion modelling, climate information for environmental conservation, Antarctic meteorology and regional climate dynamics, wild-land fire weather and fire-atmospheric interactions, and applied machine learning.

Disasters: UC hosts a strong contingent of staff with teams supporting disaster related mapping including the Disaster Risk and Resilience group with work on volcanic ash hazard and risk (Tom Wilson and Heather Craig), seismic risk and landslide mapping (Tom Robinson), tsunami risk (James Williams and Kristie-Lee Thomas), and climate changes influencing flood risk (Heather Craig).

Glaciers: Heather Purdie explores, predicts, and manages patterns of glacier behaviour; understanding seasonal snow and ice contributions to downstream water resources.

Antarctica: Gateway Antarctica seeks to improve climatic and ecosystem understanding, management, and solutions on the Southern Ocean within a global context. Wolfgang Rack studies sea ice and snow thickness in the Ross Sea using satellite, airborne, drone, and ground-based radar. Michelle LaRue combines remote sensing techniques with spatial and wildlife ecology to study marine predator populations in the Southern Ocean.

Surveying: The Waterways Centre operates an airborne and mobile mapping lidar facility in partnership with Christchurch Helicopters using a suite of high precision, survey grade lidar, infrared, and topobathymetric sensors. The team work closely with national and regional government partners and industry to support acquisition and modelling including machine learning, extreme weather events (i.e., Cyclone Gabrielle), forest carbon stocks, bathymetric lidar survey design and waveform signal processing, and calibration/validation of surface water retrievals from SWOT (with NASA-JPL). The team acquired dense lidar for over 4000 km2 of New Zealand in a few years and supports operations in Australia.

Directed by Matthew Wilson

GRI promotes interdisciplinary geospatial activities including productive use of geospatial data, technologies and analytics. Recent work includes developing the first national flood map with NIWA, mapping national health and mobility data, and engagement with Māori communities on plant pathogens and urban planning. It aims to grow geospatial capacity and innovation including leadership in indigenous geospatial information towards a just and sustainable society. GRI runs a seminar series of academic, industry, and government speakers with online participation options.