Programme title: GIS (Geographic Information Science) Final award (BSc, MA etc):

Programme title:
GIS (Geographic Information Science)
Final award (BSc, MA etc):
(where stopping off points exist they should be
detailed here and defined later in the document)
UCAS code:
(where applicable)
Cohort(s) to which this programme
specification is applicable:
(e.g. from 2015 intake onwards)
Awarding institution/body:
University College London
Teaching institution:
University College London
Engineering Sciences
Parent Department:
Civil, Environmental & Geomatic Engineering
(the department responsible for the administration of
the programme)
Departmental web page address:
(if applicable)
Method of study:
Criteria for admission to the
Honours degree in relevant/cognate subject, Minimum 2i
Length of the programme:
12 months full time
(please note any periods spent away from UCL, such
as study abroad or placements in industry)
Level on Framework for Higher
Education Qualifications (FHEQ)
(see Guidance notes)
Relevant subject benchmark statement
Level 7
Not applicable
(see Guidance notes)
Brief outline of the structure of the
(see guidance notes)
Board of Examiners:
Students must take 120 credits of taught modules, all of which
are compulsory. These are assessed through a combination of
written examinations and coursework, in the approximate ratio
1:7. The individual dissertation is worth 60 credits and has a
guide length of 10,000 – 12,000 words.
Name of Board of Examiners:
Taught Postgraduate Board for Civil, Environmental & Geomatic
Professional body accreditation
(if applicable):
Date of next scheduled
accreditation visit:
The programme is designed to educate students in the theoretical, scientific and practical aspects of geographic
information science. This covers a range of topics from qualitative and quantitative spatial analytical techniques to
web and mobile mapping, GI system design, spatial database design and management and advanced spatiotemporal data mining. Graduates are given a solid grounding in the scientific principles underpinning spatial
analysis and the computational foundations of GIS, as well as a broader practical understanding of topics such as
analysis of the needs of a GIS user, modern programming environments and database management systems and
their application within Geographical Information Systems.
The programme provides opportunities for students to develop and demonstrate knowledge and understanding,
qualities, skills and other attributes in the following areas:
A: Knowledge and understanding
Knowledge and understanding of:
1. The theoretical and analytical aspects
of Geographic Information Science,
including the geometrical and
coordinate framework in which work
is carried out, and the physical
environment within which
measurements are made, as well as
the techniques for data processing,
manipulation, and analysis.
2. A range of visualisation techniques
for displaying geographic data,
including human factors associated in
design of these displays and
geographic information systems
3. The management, professional, and
legal issues that apply within the
geomatics industry and the
developments that will shape its
4. The principles underlying the
management and analysis of spatial
data and use of basic mathematical,
statistical and computational
processes for analysis of data
5. Programming techniques for
manipulation of existing systems and
for design of custom-made
Teaching/learning methods and strategies:
For each generic area, teaching and learning is through
lecture courses, practical classes, demonstrations and
Management and professional issues are in addition
supported by a series of 14 external speakers from
industry, a GIS-specific careers event which includes
mock interviews and CV reviews and visits to industrial
and government establishments, such as Ordnance
Survey. Students are encouraged to actively participate
in the various GIS activities around London.
Through unseen written examinations, assessed group
and individual coursework. Testing of knowledge is also
through formal presentations.
B: Skills and other attributes
Intellectual (thinking) skills:
1. Explain the generic concepts and
science of GIS – having a good grasp
of theories from Geomatics,
Geography, Computer Science,
Statistics, Environmental Engineering
and related areas.
2. The ability to evaluate and critique
existing data analysis and system
development and design, and
propose alternative avenues where
3. The ability to assess the nature and
impact of economic, environmental,
safety and commercial aspects of a
real-world problem through an
integrated Geographic Information
Science approach
4. The ability to manage, understand
and analyse information and data
5. Creativity and independence of
Teaching/learning methods and strategies:
“Problem” classes and practical exercises. Seminars
and group discussions.
Oral presentations and written submissions of
Also through students’ analysis and questioning of their
colleagues’ work.
C: Skills and other attributes
Practical skills (able to):
1. Competent in the use of commercial
and Free and Open Source GIS
2. Implement typical GIS routines
algorithms (using a high level
language such as Java, Python)
3. Manage data acquisition and digital
mapping projects – including quality
control over the acquisition of spatial
4. Describe the structures used for
spatial data and apply query
languages in relation to database
management systems
5. Undertake user requirement
analyses, understand user interaction
with GI Systems
6. Develop web and mobile Apps that
make use of location as an
underpinning element
7. Perform in-depth analysis on large
spatial and spatio-temporal datasets.
Teaching/learning methods and strategies:
Practical skills are taught alongside specialist
knowledge, using the same range of teaching methods,
such as practical exercises, demonstrations, and
individual and group coursework.
Coursework reports and dissertation projects provide the
opportunity of greater student involvement in the
development of proposals, design of methodological
framework, data acquisition and specialist analysis.
Submitted coursework
Final dissertation
D: Skills and other attributes
Transferable skills (able to):
1. Use a range of techniques for
numerical analysis.
2. Use advanced IT skills, including the
ability to program in at least one
language, e.g. Java and Python (in
addition to enhanced basic IT skills:
use of spreadsheets, word
processing, presentations, etc).
3. The ability to retrieve and analyse
information from a range of sources.
4. The ability to communicate effectively
with co-workers and supervisors, and
to participate effectively in all levels of
project management.
5. The ability to communicate technical
and non-technical information clearly
and effectively, both orally and in
writing, to both specialist and nonspecialist audiences.
6. The ability to present and display a
range of information, both quantitative
and qualitative attractively in reports,
maps, slides and posters.
7. The ability to exercise initiative, selfsufficiency and leadership where
Teaching/learning methods and strategies:
Transferable skills are not taught in separate courses,
but permeate the whole range of teaching and learning
methods used in the department.
Problem-solving classes and tutorials.
Lectures and practical classes.
Submitted coursework and written examinations.
Many course elements in the second term require a
presentation of some sort. The individual MSc project
has a marked element for presentation as a written
report, and an element for an oral/poster presentation.
GIS students additionally carry out an introductory
presentation for their MSc project early in Summer.
The following reference points were used in designing the programme:
 the Framework for Higher Education Qualifications:
 the relevant Subject Benchmark Statements:
 the programme specifications for UCL degree programmes in relevant subjects (where applicable);
 UCL teaching and learning policies;
 staff research.
Please note: This specification provides a concise summary of the main features of the programme and the
learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes
full advantage of the learning opportunities that are provided. More detailed information on the learning outcomes,
content and teaching, learning and assessment methods of each course unit/module can be found in the
departmental course handbook. The accuracy of the information contained in this document is reviewed annually
by UCL and may be checked by the Quality Assurance Agency.
Programme Organiser(s)
Dr Claire Ellul
Date of Production:
Date of Review:
Reviewed 17th November 2015
Date approved by Chair of
Departmental Teaching
Date approved by Faculty
Teaching Committee
January 2016
January 2016