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 ҕl 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.
