Geography

Global Environmental Change

Module code: 003GS
Level 6
30 credits in spring semester
Teaching method: Practical, Seminar, Fieldwork
Assessment modes: Coursework, Report

Environmental change has become a central global issue with serious implications for the social and natural world. There is a need to monitor the earth's signs of change, especially where ground information is spatially limited, filled with error, or unavailable. Remote sensing datasets are vital in monitoring local, regional and global changes.

In this module, you'll use remote-sensing datasets to answer fundamental questions about our changing planet. This will involve:

  • assessing and monitoring changes in our atmosphere, cryosphere, hydrosphere and biosphere
  • understanding the nature of remote sensing
  • gaining practical knowledge in using and manipulating big datasets
  • linking environmental change to sustainability and policy.

We'll focus on four components of the geosphere:

  • Remote Sensing of the atmosphere monitors weather, detects greenhouse gas and pollution
  • Remote sensing of the cryosphere helps in determining the presence, absence and change of ice cover over the earth's surface
  • Remote sensing of the hydrosphere monitors the oceans, organic and inorganic ocean constituents, sea surface temperatures, el nino events, land water fluxes, and flooding events
  • Remote Sensing of the biosphere monitors the component of the earth that supports life, and is sensitive to changes in climate. This includes:
    • vegetation structure
    • composition
    • land cover types
    • soil moisture
    • leaf chemical components
    • phenology
    • change detection
    • plant stress and photosynthesis
    • transpiration
    • surface temperatures.

Module learning outcomes

  • Understanding differing remote sensing technologies and data characteristics.
  • Understand how remote sensing can be used to answer scientific questions on the environment and climate change.
  • Prepare and analyse digital data using ArcGIS and Matlab.
  • Analyse and evaluate current debates in remote sensing science.