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.

One semester focuses principally on remote sensing where you will learn in relation to image processing:
• 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 landcover maps as a basis for resource management.

The other semester focuses on spatial analysis using GIS by:
• teaching you about key theoretical concepts associated with the types and associated use of digital data: what you can and can’t do to digital data in GIS, 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;
• teaching you 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
• teaching you 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 principles across the range of topics covered on the module, thus acting as a framework to support your learning. You will develop your practical and technical skills using workbooks with guided exercises and directed learning to complete before the next class. The IT workshops enable you to explore, analyse and interpret a wide of range of digital datasets, applying the latest techniques using industry-standard software. The exercises are designed to improve your ability to solve complex problems. The IT workshops are supervised but you will be expected to finish the project work in your own time whilst exploring in more detail, in the literature and using online resources, examples of the techniques you are learning implemented in research or in the public and private sector. In the workbooks you are also set tasks that you can work on in your own time to support your engagement with the project based application image analysis and spatial analysis linked to your assignments on this module.

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 virtual learning platform, Blackboard. 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. Your workbooks also contain tasks for you to work on in your own time. 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: 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)

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:

1 hour online test
Weighted 35% of module mark
The two remote sensing assignments in one semester are project based and are linked to a workbook that contains weekly tasks, using the same data that build and contribute to the associated assessment. The first assignment is an online test that will enable 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 and landcover classification
MLOs 1 and 4

2,500 word Project
Weighted 35% of module mark
Knowledge and skills gained from the first assignment are expanded upon in the following IT workshops and formative feedback is provided by staff when you are working on the datasets and designing a method in order to answer the objectives of the project assignment.
MLOs 1, 3, 5 and 6

500 word short answer GIS methods
Weighted 15% of module mark
IT practicals for the GIS element of this module are also provided in a workbook but adopt a different approach where you will work on different datasets each week. In order to answer a set of questions (short answer assignment) you will need to apply a problem solving approach using the GIS skills and theory taught to you in the first half of the the module, in order to generate a Hazard Index using the GIS techniques you have been taught.
MLOs 2 and 4

2,500 word Project 1 hour exam
Weighted 35% of module mark
This assignment will test build upon and add to the suite of GIS skills provided in IT workshops the second assignment requires you to design and implement a GIS spatial modelling technique in order to answer a set of objectives
MLOs 2, 3, 5 and 6

Formative assessment/support processes and feedback
The results of the online test are provided the same day and if you get it wrong the answers are provided to you in a group feedback session as part of a lecture. For all three written assessments, 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.

Pre-requisite(s)

KE4005

Co-requisite(s)

None

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).

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.

Course info

UCAS Code L7T6

Credits 20

Level of Study Undergraduate

Mode of Study 4 years full-time or 5 years with a placement (sandwich)/study abroad

Department Geography and Environmental Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2019 or September 2020

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