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GEOL50130: Earth and Environmental Sciences

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 5
Credits 30
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Earth Sciences

Prerequisites

  • None

Corequisites

  • None

Excluded Combinations of Modules

  • None

Aims

  • 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.

Content

  • 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).

Learning Outcomes

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.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • 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%.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures/Practicals16Weekly3 Hours48Yes
Surgeries8Bi-weekly1 Hour8 
Fieldwork3Days721Yes
Self-Study and Reading223 
Total300 

Summative Assessment

Component: Continual AssessmentComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
In-class Test2 Hours20
Mini-project based on topic of choice60
Group project based on data camp20

Formative Assessment

More information

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