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• To provide an introduction to a variety of Earth and Environmental and geospatial datasets, including remotely-sensed satellite imagery, and to the specialist mathematical and software tools required for their quantitative and computational analysis.
• To provide advanced knowledge of how to use these datasets and tools to tackle cutting-edge and societally-relevant problems relating to the study of the Earths physics and chemistry.

• This module will equip students with the necessary specialist mathematical and software tools to handle, manipulate, visualise and analyse geospatial datasets.
• This will include developing understanding and experience of spatial and geospatial reference systems, geostatistics and Geographical Information Systems software.
• This module will also introduce Earth and Environmental Sciences datasets and cutting-edge problems through a series of detailed topics, each focussed on one or more key data streams or types, including but not limited to geophysical data or model outputs, remotely-sensed satellite data, and Environmental time-series.
• Each topic will feature an introduction to the Earth Sciences context, background, and theory underpinning the key data streams for that topic, an in-depth examination of data collection, handling and processing, and a discussion of unique considerations, limitations and strengths of the individual datasets. Each topic will also highlight a variety of diverse current and societally-relevant problems the data can be used to address.
• Students will have an opportunity to choose one of these topics to investigate further through an independent summative mini-project.
• Class-based teaching in this module is supplemented by a Data Camp; a short field course focussed on acquisition of data in the field from a variety of sources (e.g. individual sensors or drones), followed by processing of these datasets and integration and joint analysis with supplementary datasets across a diverse range of scales (e.g. satellite data, national, international sensor networks).

Subject-specific Knowledge:

• Knowledge and understanding of Earth and Environmental and geospatial datasets, including remotely-sensed satellite data and field data.
• Knowledge and understanding of mathematical and software tools for handling, visualising, analysing and modelling these datasets.
• Knowledge and understanding of select topics of active research in Earth and Environmental Science.

Subject-specific Skills:

• Specialised and advanced computational and mathematical skills for handling, visualisation, analysis and modelling of geospatial and remotely-sensed datasets
• Intellectual and practical skills necessary to synthesise and integrate information/data acquired from a variety of sources and at a variety of scales.
• Intellectual and practical skills necessary to use Earth and Environment data and advanced methodologies for the solution of complex, novel, specialised and unfamiliar problems.
• Intellectual and practical skills necessary to plan, conduct and report on field projects.

Key Skills:

• Presentation skills
• Team working
• Problem solving, written presentation of an argument
• Ability to learn actively and reflectively, to develop intuition, and the ability to tackle unfamiliar and complex new material
• Develop an adaptable and flexible approach to study and work.

• This module will be delivered through a series of flexible 3 hour sessions comprising both lectures and practicals, supported by surgeries.
• The core teaching will also be supplemented by a Data Camp field course.
• The practicals form an important component of the module allowing "hands on" learning and experience.
• Summative assessment is made up of a practical test 20%, a mini-project based on a topic of choice 60% and a group project based on data camp 20%.

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