KL7028 - Applied Space Observation

You will learn through a combination of research-led lectures and extensive hands-on computer-based workshops. Lectures introduce the key concepts and techniques of space observation, delivered by experts actively involved in space research. The majority of your contact time is dedicated to practical workshops where you will work with real space observation data using Python programming, developing your technical skills in data processing, analysis, and visualisation. You will also engage with the wider context of space observations through a literature-based discussion session on space weather impacts and through a group-based interactive disaster scenario exercise. Beyond scheduled sessions, your independent study will be supported through comprehensive online resources accessible via the module eLP site, including mission data archives, analysis software documentation, and relevant research publications.

You will be taught by world-leading experts in the field of space observations. Your learning will be enhanced by guest lectures from organisations such as the UK Met Office Space Weather Operations Centre and industry partners such as Lockheed Martin. Course materials will be supported by curated online resources including mission handbooks and recent publications. Staff maintain an open-door policy and provide responsive email support. The module benefits from access to state-of-the-art facilities including the Northumbria Space Technology Laboratory and connections to the North East Space Skills and Technology (NESST) Centre.

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

Knowledge & Understanding:
MLO1: Understand the key remote sensing and in-situ methodologies used to observe the space environment.
MLO2: Critically evaluate how different space observation techniques contribute to our understanding of space weather processes and their impacts on critical national infrastructure.

Intellectual / Professional Skills & Abilities:
MLO3: Demonstrate proficiency in processing, analysing, and visualising space observation data using Python-based tools through computer-based practical exercises.
MLO4: Develop advanced analytical, problem-solving, and scientific communication skills for presenting complex space observation findings to both specialist and non-specialist audiences.

Personal Values Attributes (Global / Cultural Awareness, Ethics, Curiosity) (PVA):
MLO5: Demonstrate intellectual curiosity and collaborative problem-solving in applying space observation techniques to address space weather challenges, recognising the global significance of space weather for society and technology.

Summative assessment: you will be assessed in a summative manner through two pieces of assessment:

Technical Portfolio (40%)
This assessment requires you to compile a technical portfolio (equivalent to 1,500 words) documenting your practical work from the module workshops. You will demonstrate your ability to process and analyse space observation data using Python, presenting your methods, results, and visualisations in a clear and professional format. The portfolio should cover a selection of the workshop exercises, demonstrating technical competency across different observation techniques covered in the module.
Addresses MLOs 1, 3 and 4.

Individual Space Observation Project Report (60%)
You will deliver a project report (up to 2,500 words) on a space observation topic aligned with the module themes. This may draw on the space weather disaster scenario exercise or on an independent investigation of a specific observation technique or dataset. You will critically review relevant literature, present original data analysis and visualisations, and communicate your findings effectively to a mixed audience.
Addresses MLOs 1, 2, 3, 4 and 5.

Formative assessment: You will receive formative feedback throughout the module via the weekly workshops, where staff will provide guidance on your data analysis techniques and scientific interpretation. You will also have the opportunity to discuss your project ideas and receive feedback on your analytical approach before the final presentation. Detailed written feedback will be provided on summative submissions.

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How do we observe the visible and invisible forces shaping the space environment around us? This module introduces the diverse techniques used to study the Sun, Earth's magnetosphere, and the wider space environment – from remote sensing by space telescopes and ground-based observatories to in-situ measurements by satellite constellations. Through extensive hands-on workshops using Python and real mission data, you will develop practical skills in space data analysis and visualisation that are directly transferable to careers in the space sector. A highlight of the module is an interactive space weather disaster scenario, where you will apply your knowledge to assess the impacts of extreme space weather on critical national infrastructure. Taught by internationally recognised researchers with direct involvement in ESA, NASA, and UK Space Agency missions, and enriched by guest contributions from external organisations (such as the UK Met Office and Lockheed Martin), this module connects you to cutting-edge research and the rapidly growing space industry.