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Digital Geography

Overview

  • Credit value: 30 credits at Level 5
  • Convenor: Dr Shino Shiode
  • Assessment: a 20-minute class presentation (40%) and 3000-word project (60%)

Module description

In this module we will introduce the concepts, technologies and applications that underpin the rapidly evolving field of digital geography and geospatial innovations. Specifically, we explore how digital geographical data are collected, managed, analysed and communicated through contemporary digital geospatial tools and platforms, including GIS, web mapping and mobile mapping. You will learn about the diverse forms of digital spatial data generated through social media, crowdsourcing and volunteered geographic information, while also pursuing the growing role of artificial intelligence and GeoAI to interpret spatial patterns and processes and tackle real-world challenges. By engaging with current and emerging digital geographical methods, you will develop critical awareness of how digital technologies are reshaping our geographical understanding and decision-making, as well as wider socioeconomic activities, including those embedded in our everyday life.

You will also develop practical and analytical skills for working with geospatial data in a range of applied contexts. You will gain experience in collecting, integrating, visualising and interpreting digital geographical information using open-source geospatial tools and introductory geospatial programming techniques in Python. By combining technical training with critical geographical perspectives, you are encouraged to work both independently and collaboratively to undertake digital geography investigations, communicate findings effectively through digital and cartographic outputs, and engage with future developments in geospatial technologies and innovation.

Indicative syllabus

  • Nature of data in digital geography
  • Collecting geographical data from various data sources in different formats
  • Understanding our world using digital geography methods
  • Web mapping, mobile mapping and interactive cartography
  • Crowdsourced geographic data and volunteered geographic information
  • Social media and geotagged data handling
  • Use of AI in analysing and modelling geographical data
  • Geospatial programming with Python
  • Geospatial data quality, accuracy and uncertainty
  • Future trends in digital geography and geospatial innovation

Learning objectives

By the end of this module, you will be able to:

  • explain key concepts, technologies and emerging trends in digital geography and geospatial innovation
  • collect, manage and integrate geo-referenced data from multiple digital sources and formats
  • use web mapping and mobile mapping to visualise and communicate geographical information effectively
  • assess issues relating to geospatial data quality, accuracy, uncertainty, ethics, privacy and representation
  • critically interpret digital geographical evidence and communicate findings using appropriate digital and cartographic outputs
  • use and apply GeoAI methods and platforms to improve understanding of real-world phenomena and problems
  • demonstrate introductory geospatial programming skills (in Python programming language) for handling and processing geo-referenced data
  • work both independently and collaboratively to design and undertake digital geography investigations using open-source geospatial tools and platforms.