Postgraduate Diploma, Master of Science
Faculty of Life and Health Sciences
School of Geography and Environmental Sciences
This course is taught online so you can study where you want, when you want.
An engaging course specialising in improving remote sensing and GIS employability and professional skills.
This online course delivers contemporary content on remote sensing and GIS integrating theoretical and practical learning activities encompassing acquisition, analysis and interpretation of geospatial data. Course participants will develop skills in a range of areas including:
We are an established provider of online distance learning postgraduate courses. With 25 years' experience of teaching GIS, and nearly 20 years via online distance learning, we have a long and successful track record in GIS education. We enjoy imparting knowledge, skills and confidence that enhance employment prospects with our innovative and career-focused modules and research.
Ask yourself these simple questions: Are you a fresh graduate desiring to enter remote sensing/GIS-related employment for the first time, or add remote sensing and GIS to your skillset to enhance employability, qualification or change career? Are you a professional already in remote sensing/GIS-related employment and want to broaden and deepen your remote sensing and GIS knowledge and skills with a view to making better use of spatial technologies, or want to enhance your career and promotion prospects, or even just qualification?
If you answered yes to any of these, then good news – this course is for you!
Our remote sensing and GIS programme offer flexible learning through part-time education – while each module has coursework deadlines, you study at a time and pace that suits you.
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The demand for remote sensing and GIS professionals has been steadily increasing within government, business, education and voluntary sectors, whereas rapid growth in availability of spatial data, mainly via remote sensing satellites and other big data sources provide a huge potential to map, monitor and understand systems and change in terrestrial and marine environments. Skills in remote sensing and GIS enables analysis across global or local scales on a rapid basis in vast application areas spanning both physical and human geography – climate change, agriculture, forestry, natural resource management, marine planning, sustainable urban development, epidemiology and crime analysis are to name a few. This course aims to provide training in capturing, storing, analysing and interpreting big earth data.
Modules are taught online via Blackboard Virtual Learning Environment that provides access to lectures, practical exercises, reading and additional study materials. Communication tools (discussion boards, video-conferencing and email) are integrated within Blackboard and all modules are supported by experienced lecturers and tutors. Progress is assessed entirely online – there are no formal sit-in examinations.
This course is fully online and part-time. You do not need to visit Ulster at any stage to successfully complete this course. You have greater control over your learning journey when you study part-time - balance work and other commitments and study at a pace that suits you.
You can choose your own hours of study; however, you should expect to dedicate an average of 17-20 hours to the course per week.
This course is delivered through a teaching platform (Virtual Learning Environment, VLE), called Blackboard, through which we provide teaching materials, assignment instructions, links to electronic library resources and other reading materials, as well as discussion boards and other communication tools. Teaching materials consist mainly of lectures in various formats (e.g. as illustrated documents or podcasts) and practical exercises (written instructions with screenshots or screencasts), which may be supplemented by additional reading or video content, tutorial exercises, quizzes, etc. The format of delivery provides you with the flexibility to study at your own pace, any place and at any time, and you are not required to attend the campus at any stage during the course.
Learning is supported by lecturers and e-tutors via discussion forums, email, phone or video-conferencing tools. Discussion forums encourage participation from the whole class and offer opportunities for you to learn about issues and problems from different perspectives as well as getting to know your fellow students.
Assessment involves a mixture of methods including practical reports, problem analysis, research projects, presentations, blogs, online tests and group work. The Master’s element of the course takes the form of a substantial independent research project, written up in the form of an academic paper, which may subsequently be considered for submission to a scientific journal. You will be assessed by coursework only and there are no sessional examinations.
Once registered, you will be able to use the University's extensive online library resources of electronic journals, e-books and databases. In addition, you will also gain access to different remote sensing, GIS and statistics software packages.
The content for each course is summarised on the relevant course page, along with an overview of the modules that make up the course.
Each course is approved by the University and meets the expectations of:
As part of your course induction, you will be provided with details of the organisation and management of the course, including attendance and assessment requirements - usually in the form of a timetable. For full-time courses, the precise timetable for each semester is not confirmed until near the start date and may be subject to change in the early weeks as all courses settle into their planned patterns. For part-time courses which require attendance on particular days and times, an expectation of the days of attendance will often be included in the letter of offer. A course handbook is also made available.
Courses comprise modules for which the notional effort involved is indicated by its credit rating. Each credit point represents 10 hours of student effort. Undergraduate courses typically contain 10- or 20-credit modules and postgraduate course typically 15- or 30-credit modules.
The normal study load expectation for an undergraduate full-time course of study in the standard academic year is 120 credit points. This amounts to around 36-42 hours of expected teaching and learning per week, inclusive of attendance requirements for lectures, seminars, tutorials, practical work, fieldwork or other scheduled classes, private study, and assessment. Part-time study load is the same as full-time pro-rata, with each credit point representing 10 hours of student effort.
Postgraduate Masters courses typically comprise 180 credits, taken in three semesters when studied full-time. A Postgraduate Certificate (PGCert) comprises 60 credits and can usually be completed on a part-time basis in one year. A 120-credit Postgraduate Diploma (PGDip) can usually be completed on a part-time basis in two years.
Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures you can expect at least 3 contact hours per week (lectures/seminars/tutorials). Laboratory classes often require a greater intensity of attendance in blocks. Some modules may combine lecture and laboratory. The precise model will depend on the course you apply for and may be subject to change from year to year for quality or enhancement reasons. Prospective students will be consulted about any significant changes.
Assessment methods vary and are defined explicitly in each module. Assessment can be via one method or a combination e.g. examination and coursework . Assessment is designed to assess your achievement of the module’s stated learning outcomes. You can expect to receive timely feedback on all coursework assessment. The precise assessment will depend on the module and may be subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.
Coursework can take many forms, for example: essay, report, seminar paper, test, presentation, dissertation, design, artefacts, portfolio, journal, group work. The precise form and combination of assessment will depend on the course you apply for and the module. Details will be made available in advance through induction, the course handbook, the module specification and the assessment timetable. The details are subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.
Normally, a module will have four learning outcomes, and no more than two items of assessment. An item of assessment can comprise more than one task. The notional workload and the equivalence across types of assessment is standardised.
The class of Honours awarded in Bachelor’s degrees is usually determined by calculation of an aggregate mark based on performance across the modules at Levels 5 and 6 (which correspond to the second and third year of full-time attendance).
Level 6 modules contribute 70% of the aggregate mark and Level 5 contributes 30% to the calculation of the class of the award. Classification of integrated Masters degrees with Honours include a Level 7 component. The calculation in this case is: 50% Level 7, 30% Level 6, 20% Level 5. At least half the Level 5 modules must be studied at the University for Level 5 to be included in the calculation of the class.
All other qualifications have an overall grade determined by results in modules from the final level of study. In Masters degrees of more than 200 credit points the final 120 points usually determine the overall grading.
Figures correct for academic year 2019-2020.
Main teaching staff:
Learning is also supported by several experienced e-tutors.
The University employs over 1,000 suitably qualified and experienced academic staff - 59% have PhDs in their subject field and many have professional body recognition.
Courses are taught by staff who are Professors (25%), Readers, Senior Lecturers (20%) or Lecturers (55%).
We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic staff (81%) are accredited fellows of the Higher Education Academy (HEA) by Advanced HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.
The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise. The precise staffing for a course will depend on the department(s) involved and the availability and management of staff. This is subject to change annually and is confirmed in the timetable issued at the start of the course.
Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.
Figures correct for academic year 2021-2022.
Here is a guide to the subjects studied on this course.
Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.
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This module covers advanced topics in visible remote sensing and image analysis, including photogrammetry and digital elevation models, image processing and manipulation, advanced classification techniques such as object-based image analysis (OBIA), and time series analysis using Google Earth Engine. It builds on the topics covered in EGM713, complements the topics covered in EGM722, and provides a foundation for further study in remote sensing.
This module introduces the theory and practice of Geographic Information Systems, and is intended to provide an understanding of the breadth of potential GIS applications and to equip students with key concepts and skills relating to the input, management, manipulation, analysis and output of spatial data. Lecture-based teaching of key concepts is reinforced by linked practical exercises which allow students to develop competence in ESRI's ArcGIS package. The module assumes no prior knowledge or experience of GIS.
This postgraduate module offers students the opportunity to study the principles and applications of remote sensing and image analysis and to explore links between remote sensing and GIS. Students will become familiar with theoretical foundations of remote sensing and will develop technical skills through a series of software-based practical exercises and assignments using ERDAS Imagine.
This module develops programming skills using the python programming language. The module seeks to provide students with key skills in the development of repeatable, automated analyses of GIS applications. The module also aims to develop academic writing skills in preparation for the MSc degree.
This module covers advanced topics in active and passive remote sensing, including the highly sought-after topics of hyperspectral and microwave remote sensing, covering both active and passive microwave applications. It also covers thermal and below-surface (i.e., ground-penetrating radar) remote sensing techniques. It builds on the topics introduced in EGM713 and provides a framework for more detailed modules covered later in the course, as well as the (optional) research topic.
This module builds on the knowledge and practical skills gained in EGM711 to provide students with further experience in the acquisition, manipulation and analysis of spatial data. Methods for generating and collecting digital spatial data from primary and secondary sources are considered, and data processing, selection, integration and analysis extensively practiced. Lecture and practical sessions include digitising, geo-registration, GPS, accessing and using secondary sources, spatial join and overlay, network analysis and 3D modelling, and incorporate experience of a variety of large and small scale vector and raster datasets. The module also incorporates practice in statistical analysis and interpretation. Development of GIS software skills focuses on ArcGIS and extensions.
This module is optional
This module first introduces the underlying concepts of marine remote sensing and its applications within the framework of ocean properties and seafloor characteristics. It introduces students to different datasets and spatial data management tools for ocean remote sensing and aim to help them develop an appreciation of mapping scales, data resolution and density. Lastly the module focuses on the effective integration of relevant datasets in the context of specific users' and stakeholders' requirements. The module is a combination of theoretical and practical based sessions using both commercial and open source software. Guest lectures and contributions from world-leading experts in the field will form an integral component of the module.
This module is optional
This module examines the role of programming within the GI industry. It aims to enable students to appreciate the need for programming skills that can be used to customise and develop applications. A range of programming skills is introduced which equip the student with knowledge of the potential and scope of programming within various applications.
This module is optional
This module builds on the introductory material of EGM711 and EGM712, covering advanced concepts of spatial data analysis and modelling, and providing extensive practical experience of ESDA and spatial analysis and modelling within a GIS environment.
This module is optional
This optional module examines the application of GIS to environmental management, modelling and impact assessment. It aims to enable students to appreciate the need for properly researched information to support strategic and operational environmental management decisions, and to be aware of the means by which such information can be obtained and evaluated.
This module provides students with the opportunity to undertake a substantial piece of research in an area of particular interest to the student. The student will be assessed on their project proposal and two progress reports, together with the final research paper.
We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.
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As a normal requirement, applicants must hold an Honours degree (2:2 or above) with a substantial component of geography, environmental science, computing or other numerate discipline. Applicants with other equivalent and relevant qualifications or experience can also be considered on an individual basis.
English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.
Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.
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Remote sensing, GIS and geospatial technologies underpin a rapidly growing, multi-billion-dollar industry, and are becoming increasingly mainstream within both the public and private sectors, resulting in a need for graduates who have a combination of theoretical knowledge and practical skills. Participants and graduates of this course could seek employment in a variety of remote sensing/ GIS-related roles such as analysts, scientists, consultants, project managers, surveyors, data specialists, technicians, mapping officers, development, sales and marketing, customer support, GIS training, lecturing and research (including funded PhD projects). The breadth of potential uses of remote sensing and GIS ensures a great diversity of job opportunities; for example, our GIS graduates have found employment with mapping agencies, GIS and SatNav companies, environmental consultancies, ecological and marine resource management and environmental agencies, renewable energy companies, forestry, fisheries, town planning departments, heritage agencies, health and emergency services, housing authorities, local government, aid agencies, countryside recreation, rural development, retail analysis, utilities and infrastructure, Further and Higher Education, mining and mineral exploitation and the oil industry, among others. Knowledge and understanding of geospatial data are also increasingly required in a variety of jobs outside of the GI profession, making remote sensing and GIS qualifications valuable for enhancing employability in a range of fields.
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A prize - 'GES Academic Excellence Award for Remote Sensing and GIS research' - will be awarded to an outstanding piece of research.
This course has very few additional mandatory costs and the majority of reading material is available free of charge via the University's electronic library resources. Our libraries are a valuable resource with an extensive collection of online books and journals but you will be expected to purchase a small number of textbooks during the course. However, costs are kept as low as possible and are not likely to exceed £150 in total.
The latest version of Microsoft Office is available to download for current students, free of charge. You can run Office on up to five desktop Mac or Windows. You can also run Office Mobile on up to 5 mobile devices (on supported mobile operating systems). Other software programs required for this course are either freely available (open source), or provided free of charge under academic licence (e.g. ESRI's ArcGIS Pro, the remote sensing package Erdas Imagine and SPSS for statistical analysis).
You will need a PC or laptop with a minimum of 4 GB RAM (preferably higher) and a CPU speed of at least 2.2 GHz. As ArcGIS Pro and Erdas Imagine only run on Windows, a Windows-based PC or laptop (rather than Mac) is required.
Please contact the course team in case you need more information.
It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition feesWhere a course has additional mandatory expenses (in addition to tuition fees) we make every effort to highlight them. These may include residential visits, field trips, materials (e.g. art, design, engineering)vaccinations , security checks, computer equipment, uniforms, professional memberships etc.
We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals as well as first-class facilities and IT equipment. Computer suites and free wifi are also available on each of the campuses.
There will be some additional costs which cannot be itemised and these will be different for each student. You may choose to purchase your own textbooks and course materials or prefer your own computer and software. Printing and binding may also be required. There are additional fees for graduation ceremonies, examination resits and library fines. Additional costs vary from course to course.
Students choosing a period of paid work placement or study abroad as part of their course should be aware that there may be additional travel and living costs as well as tuition fees.
Please contact the course team for more information.
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Please contact Ulster University with any queries or questions you might have about:
For any queries regarding course entry requirements or getting help with your application, please select Admissions in the drop down below.
For queries related to course content, including modules and placements, please select Course specific information.
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