KE5017 - Earth Observation and GIS

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What will I learn on this module?

This module is designed to teach you the concepts and techniques of spatial data handling and analysis using the techniques of remote sensing and image processing and Geographical Information Systems (GIS). Adding to the cartographic skills and basic spatial analysis that you have learnt from level 4 (first year) you will be taught to carry out spatial analysis from a wider range of sources and types of social and scientific geographical data. You will learn basic theoretical principles underpinning the use and application of digital datasets followed by more advanced techniques of image classification and spatial analysis. You will be taught how to use industry standard computer software applied in research and the workplace that will allow you to manipulate and analyse those data. In particular you will learn:
• the key components of remote sensing acquisition and analysis/display, including different platforms, sensors, image wavebands, and temporal and spatial resolution of imagery, and the fundamental processing techniques required in order to interpret remotely sensed imagery;
• theoretical background of datasets that can be generated and used to interpret change over space and time (e.g. loss of crops to disease, impact of changes in climate on food productivity and earths biomass); and
• the techniques used to classify and analyse datasets; explore spectral signatures, apply different classification models to produce land cover maps as a basis for resource management.
• key critical theoretical concepts associated with the types and associated use of digital data, implications of scale on analysis, error (what is it, why it matters and what can be done about it) geographical co-ordinate systems and georeferencing;
• about the GIS tool box and different methods of spatial analysis available to you including the third dimension – 3D analysis using digital elevation models; and
• the practical skills you need to interrogate and analyse data in order to answer spatial queries – geographical decision making for policy and practice.

How will I learn on this module?

In this module, you will learn through lectures and IT workshops. In addition to timetabled sessions, your independent study will be guided and supported through your engagement with a range of interactive learning resources accessible on-line via the module eLP site, including electronic reading lists.

Lectures will be used to introduce and develop key issues, concepts and theoretical principles across the range of topics covered on the module, thus acting as a framework to support your learning and understanding of the practical application of skills taught in IT workshops. In semester one you will develop your practical and technical skills using workbooks with guided exercises and directed learning to support you in completing a portfolio of tasks associated with each exercise. The IT workshops are supervised but you will be expected to finish the portfolio tasks in your own time whilst exploring in more detail key theoretical principles provided in lectures. In semester two the IT workshops are designed to support your engagement with the project based application of image analysis and spatial analysis where you will design and implement a spatial modelling technique in order to address a set of objectives. The IT workshops enable you to analyse and interpret a wide of range of digital datasets and are designed to improve your ability to solve complex problems applying the latest techniques using industry-standard software. In addition you will be given directed reading and reference to online resources that you will need to explore for examples of the techniques you are learning implemented in research or in the public and private sector.

You will be assessed through: (i) a portfolio based on practical exercises delivered in Semester 1 (up to 1000 words, 40% weighting); and (ii) a written project report combining the use of image processing and spatial analysis practical skills (and associated theoretical principles) to design and implement a spatial modelling technique carried out in semester 2 (up to 2000 words, 60% weighting). You will receive formative feedback in practical classes and summative feedback on submitted coursework.

How will I be supported academically on this module?

Module content and guidance will be made available by your module tutor in lectures as well as via the module eLP site. During IT sessions, you will interact closely with teaching staff who will provide formative support (demonstrations are often provided at the start of the class) and feedback on activities leading up to the assessment tasks, you will also benefit from interaction and problem solving with your fellow students in working through the workbooks. An interactive reading list with on-line access to a number of key articles is available to you, some of which will be linked to the weekly lecture programme. Teaching staff operate an ‘open door’ policy for students meaning you can approach them anytime during normal office hours, or via email, to answer questions, receive feedback and support your learning on the module.

What will I be expected to read on this module?

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:
(Reading List service online guide for academic staff this containing contact details for the Reading List team –

What will I be expected to achieve?

Knowledge & Understanding:
• MLO 1: Evaluate appropriate techniques of image processing in order to carry out land cover mapping and classification.
• MLO 2: Evaluate the fundamental capabilities and limitations of digital data and GIS methods for spatial analysis.
• MLO 3: Discuss the key role of remote sensing techniques and GIS spatial analysis for resource management and geographical decision making in policy and practice.

Intellectual / Professional skills & abilities:
• MLO 4: From a choice of different methods and techniques be able to generate and describe different types of digital data and their purpose.
• MLO 5: Select and apply appropriate techniques in image processing/ landcover classification and GIS spatial analysis in order to generate and/or combine data for interpretation in order to answer set aims and objectives.
• MLO 6: Critically review the use of digital data from a variety of sources and identify, quantify and manage error at a variety of geographical scales.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):

How will I be assessed?

Summative Assessment:

Individual Portfolio - maximum 1000 words
Weighted 40% of module mark.
Your portfolio submission is linked to IT practicals and associated exercises. The portfolio tasks require you to integrate theoretical and practical aspects of data generation and the use of software and associated tools in order to develop your understanding of how digital data is generated and applied for image processing, land cover mapping and classification and spatial analysis.
MLOs 1, 2 3 and 4

Individual Project report - 2000
Weighted 60% of module mark
The second assignment requires you to design and implement a spatial modelling technique in order to address a set of objectives. Knowledge and practical skills gained from the first assignment are expanded upon and added to in the following IT workshops. Formative feedback is provided by staff when you are working on the datasets and designing a method.
MLOs 3, 4, 5 and 6

You will receive formative feedback on work to be submitted for your portfolio and report during practical classes. This will provide guidance on the expected style and standard of work, and engender confidence and engagement. Annotated feedback, together with the mark awarded, will enable students to feed forward key aspects into assessments for this module and in other modules at both levels 5 and 6. The practical and project/enquiry-based nature of the assessments will also support students in thinking ahead towards their final year dissertation.





Module abstract

Developing practical skills in analysing digital datasets and understanding the implications and benefits of doing so is an emerging key skill set used in practice to answer key questions on resource management and in environmental decision making, leading to development and implementation of policy in the public and private sector. You will be learning how to use industrial standard software and in understanding the tools and techniques available, applying them to design a methodology, problem solve and explore the strengths and weakness of your results relative to objectives being set in your assignments on this module, an essential skill in the workplace. All the skills that you are taught on this module are transferable to a wide range of practices: town planning, population dynamics, hazard/risk assessment, food sustainability, environmental protection, pollution monitoring and control, and understanding of physical processes in the environment (soil erosion, landslides, glaciation).

Course info

UCAS Code L700

Credits 20

Level of Study Undergraduate

Mode of Study 3 years full-time or 4 years with a placement (sandwich)/study abroad

Department Geography and Environmental Sciences

Location Ellison Building, Newcastle City Campus

City Newcastle

Start September 2019 or September 2020

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