Become a highly skilled and sought-after professional in geospatial data science

Sustainable use or conservation of the earth's resources requires the organisation, utilisation and integration of technologies such as database management, image processing and digital cartography, to ensure provision of high quality, reliable and up-to-date information. The Advanced GIS and Remote Sensing master’s (previously known as Geographical Information Management) is a unique and innovative course that has been developed in direct collaboration with industry and in response to the increased global demand for multi-disciplinary managers, advisors and consultants in resource management. Taught by leading academic experts, this course is unique in providing balanced coverage of the key GIS technologies to prepare you for a successful career in the rapidly growing geospatial sector.


  • Start dateFull-time: October, part-time: October
  • DurationOne year full-time, two-three years part-time
  • DeliveryTaught modules 40%, group project (dissertation for part-time students) 20%, individual project 40%
  • QualificationMSc, PgDip, PgCert
  • Study typeFull-time / Part-time
  • CampusCranfield campus

Who is it for?

We welcome students from a variety of backgrounds who have a passion for technology and data. We bring together students who want to understand their role in sustainability and the new global economy, to solve real-world problems and make a positive global impact. You will gain experience of world-class spatial problem solving, as well as developing a range of personal and leadership skills to set you on the path for a rewarding career in any one of the growing range of industrial and research sectors that now routinely make use of geospatial information to solve global challenges.

Your career

Successful students develop diverse and rewarding careers in the spatial information industry, national and local government, consultancies, utilities, and research organisations. The international nature of this course means that career opportunities are not restricted to the UK. Cranfield graduates develop global careers and this course is internationally recognised by employers across the scientific, industrial and educational communities. Our practical and industry-led education makes our graduates some of the most desirable in the world for global employers to recruit.

The course is designed in direct collaboration with industry to provide you with the knowledge and practical skills to prepare you for a successful career across the full range of global sectors, including:

Environmental management, Natural resource management, Urban planning, Transportation planning, Emergency management, Science, Government and Business intelligence.

Our successful graduates who are highly skilled and sought-after professionals have pursued or enhanced their careers in a variety of key roles such as:

Data Scientist, Academic Researcher, GIS Technician, Geospatial Analyst, GIS officer, Project Development Officer and Remote Sensing Scientist, at organisations such as Airbus and Cambridgeshire Acre.


Cranfield Careers and Employability Service

Cranfield’s Career Service is dedicated to helping you meet your career aspirations. You will have access to career coaching and advice, CV development, interview practice, access to hundreds of available jobs via our Symplicity platform and opportunities to meet recruiting employers at our careers fairs. Our strong reputation and links with potential employers provide you with outstanding opportunities to secure interesting jobs and develop successful careers. Support continues after graduation and as a Cranfield alumnus, you have free life-long access to a range of career resources to help you continue your education and enhance your career.

Cranfield supports international students to work in the UK after graduation

I chose Cranfield because of the academic excellence in my course – it's highly regarded in and around the UK and so are its links with industries.
My time at Cranfield prepared me for my current job in a variety of ways. Directly, group projects and working within a team of people who challenge your ideas and viewpoints is infinitely applicable in the work place. Indirectly, the heavy workload prepared me for balancing various projects in the workplace, developing my time management and communication skills.
There are students that are coming up with ideas that I would never have thought of and I know that businesses who we collaborate with would never have thought of. So it’s really important to get idea generation, to get motivations and to get people engaged in what businesses need today.
The assignments have good challenges for each student so we gain more knowledge and information. My group project is tracking precision nutrient management and using different kinds of GIS technology - that case study was in Kenya.

Why this course?

Advanced GIS and Remote Sensing is an exciting and rapidly growing branch of information technology (IT), incorporating and integrating satellite remote sensing, aerial photography and other spatial data, such as soil survey information, to derive reliable and up-to-date information which is essential for the sustainable use or conservation of the earth’s resources. This course will equip you with the skills and knowledge to develop an exciting career helping to address global issues in the geospatial sector.

Benefit from a practical approach to learning, gaining skills in geographical information systems, spatial analysis, machine learning, coding, image processing, remote sensing, data visualisation and cartography, and data science for a successful career in the rapidly expanding geospatial field.

You will also:

  • Gain experience in the collection and processing of a wide range of geospatial data from satellite, manned and unmanned aircraft, and field survey, including processing of high-volume data in the cloud.
  • Focus on identifying problems and creating resilient and sustainable solutions through the selection and integration of appropriate technologies.
  • Learn via a varied combination of lectures, tutorials, real-world case studies and practical sessions led by Cranfield staff.
  • You will gain practical, real-world experience through consultancy led individual and group projects, often supported by industry sponsors and focused on your personal interests and career aspirations.
  • Apply the knowledge and skills that you learn on this course to issues such as climate change, improving farming yields, tropical deforestation, transportation, smart navigation systems, disaster response management, recreation, property management and telecommunications.

This master’s course is supported by our team of professional thought leaders, who have industry backgrounds and provide real-life learning challenges. Our teaching team are heavily involved in industrially funded research and development in digital environment, environmental monitoring, and resource survey. Our world leading research leads the course content and aligns it with the latest sector thinking. Our dedicated teaching team includes Professor Ronald Corstanje and Professor Stephen Hallett who are influential in the field of Environment and an integral part of this MSc. Our high student to staff ratio aims to deliver an excellent student experience and maximise your employability opportunities.

Informed by industry

The Advanced GIS and Remote Sensing MSc is designed to meet the relevant needs of global employers and benefits from a strong input from industry experts. This gives our students the confidence to know the course content aligns with the latest sector thinking and is beneficial to building a rewarding career.

  • The applied GIS and related research our staff undertake is fed back into our GIS teaching programmes, ensuring all students who complete this MSc are equipped with cutting-edge expertise and skills.
  • Double accreditation by The Royal Institution of Chartered Surveyors (RICS) and The Chartered Institution of Civil Engineering Surveyors (CICES) ensures that the course has been independently assessed as meeting current professional standards.
  • Employers and partners ensuring that the MSc meets current industry demands for GI specialists include:
  • ERM
  • GIGL
  • WRG
  • WRc PLC
  • Enviros
  • Golder
  • Unilever
  • Neales Waste
  • Natural England
  • National Trust
  • Trucost
  • SLR Consulting
  • FWAG
  • Adas
  • RSPB
  • PA Consulting
  • Joint Research Centre, Ispra
  • Airbus
  • Cresswell Associates
  • Chartered Institute of Waste Management
  • Geospatial Insight
  • Oakdene Hollins
  • Chartered Institute of Water and Environment Management
  • Health Protection Agency
  • Highview Power Storage
  • Nomura Code Securities
  • Astrium Geo-information Services
  • Environment Agency
  • Landscape Science Consultancy

Course details

This course comprises eight modules, a group project and an individual project. Courses are not isolated from the real world and many are supported by research groups working on cutting-edge programmes.  


Course delivery

Taught modules 40%, group project (dissertation for part-time students) 20%, individual project 40%

Group project

The group project experience during the course is highly valued by both students and prospective employers. It provides you with the opportunity to take responsibility for a consultancy-type project while working under academic supervision. It also enables you to start building essential industry links and knowledge whilst studying.

The project involves the application and integration of component technologies:

  • GIS
  • GPS and remote sensing
  • Field methods, and statistical analysis to produce quality-assured innovative solutions

Recent group projects include:

Individual project

The individual project is either industrially or University driven. You will be able to select the individual project in consultation with the course team and it will provide the opportunity to demonstrate independent research ability, the ability to think and work in an original way, contribute to knowledge, and overcome genuine challenges in relation to the management of the earth's resources. It also offers you the opportunity to work and build links with the types of organisation you will be seeking employment with on successful completion of the course.


Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.

Course modules

Compulsory modules
All the modules in the following list need to be taken as part of this course.

GIS and Spatial Data Management

Module Leader
  • Dr Joanna Zawadzka
    Geographical information is increasingly prevalent in our daily life, affecting personal leisure activities as much as business services and the workplace. Geographical information represents a key theme in environmental management and it has been estimated that some 80% of the data used for environmental, business and policy-oriented decision-making is geographical in nature. Such spatial data requires a structured approach in its management if the maximum benefit is to be derived from analysis and dissemination. This module provides a solid introduction to the issues concerning the management of spatial information and the tools to do so, with a predominant focus on ESRI’s software solutions. 

    Spatial data models and database structures – vectors, rasters, topology, ordered and indexed lists, hierarchical, network, relational, object oriented, hybrid, metadata.
    Mapping fundamentals – geodesy, projections, cartography, abstraction of the real world into map form.
    Analysis approaches – database manipulation, reclassification, overlay, spatial modelling.
    Data specification and standards – use cases, interoperability, INSPIRE.
    Data visualisation.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Define the functional components of a GIS, projections, data and modelling processes for managing spatial data,
  • Organise and integrate, using appropriate data structures, spatial and aspatial data within a GIS,
  • Analyse, evaluate and prepare data within appropriate spatial databases structures for information dissemination,
  • Examine the role of the INSPIRE Directive and FAIR data principles for enabling interoperability between spatial data infrastructures,
  • Perform and disseminate the results of analysis and data manipulation via maps, tables and other appropriate media.

Scientific Python

Module Leader
  • Dr Daniel Simms
    Writing code opens-up new approaches to creative problem solving and allows us to move beyond the limitations of any particular software. This module aims to develop your skills and confidence to write your own code in the Python programming language and access a broad ecosystem of packages and tools that comprise the foundations of Data Science.

    Fundamentals of programming:
    Python syntax, types, calculations, variables, strings, and object-oriented programming concepts.
    Branching, iteration, and recursion.
    Abstraction, functions, and classes. 
    Files, packages, and imports.
    Testing, debugging, and exceptions.
    Version control.
    Writing efficient code.
    Python scientific packages for data analysis and visualisation.
    Geospatial data.
    Jupyter Notebooks and Colaboratory.
    Statistics for Data Science.

Intended learning outcomes On successful completion of this module you should be able to:
Explain how computer code is used in science and engineering.
Create Python code for solving set problems and develop confidence in writing code for your own projects.
Analyse data using Python libraries and visualise results as graphs, maps and interactive figures.

Aerial Photography and Digital Photogrammetry

Module Leader
  • Dr Daniel Simms

    Deriving digital elevation models and ortho imagery is an important application of remote sensing data for many areas of spatial work. This module introduces techniques for the extraction of topographic information from remotely sensed data using digital photogrammetry techniques. Image interpretation is also a vital skill required in many image based mapping projects. The concepts and techniques of image interpretation will be introduced and practised.


  • Topographic maps and remote sensing images: map scale and content, image sources and interpretation methods, accuracy issues. 
  • Aerial imagery in the context of other remote sensing systems. Physics of light: principles of recording the image. Stereoscopy and parallax. Geometry: scale variation, relief displacement, tilts.
  • Geometry of vertical aerial imagery: geometry, co-ordinate axes, scale, measurement. 
  • Digital photogrammetry.  Digital elevation models.  Structure from Motion.
  • Satellite photogrammetry.
  • Aerial imagery mosaics and orthophotos.
  • Interpretation: principles and factors.  Applied interpretation: geology, geomorphology, vegetation, soils, urban structures.  Flight planning.  API project management and implementation.
  • Recent developments - UAV imagery, digital aerial cameras.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Explain the geometry and spectral properties of vertical aerial imagery.
  • Explain the basic principles of digital photogrammetry.
  • Interpret aerial imagery to analyse the physical and human environments.
  • Extract elevation data from stereo imagery in a digital photogrammetric environment
  • Derive orthophotography from standard frame aerial photography.

Applied Earth Observation

Module Leader
  • Dr Abdou Khouakhi
    The appropriate application of remote sensing to the monitoring of earth resources requires an understanding of basic physics and imaging technology. This subject introduces the basic radiometric concepts and physical relations and then gives you the practical tools to extract physical measurements from information from digital image data stored in the cloud. 

    Physical principles:

    Electromagnetic radiation: radiometric units and terms, radiation laws, radiation sources optical, thermal and microwave.
    Atmospheric interactions and correction.
    Surface interactions and interpretation of spectral response patterns.
    Plant, soil and water spectral properties.
    Image formation: passive systems (detectors, opto-mechanical line scanners, waveband separation, linear and area arrays) and active systems (Lidar, RAR and SAR concepts).
    Spatial resolution and geometry.
    Orbits and platforms.
    Review of satellite and airborne systems.
    Data reception and distribution: data suppliers, product levels, access, manipulation (download and in the cloud such as Google Earth Engine).

Intended learning outcomes On successful completion of this module you should be able to: 
Define the primary physical quantities that are directly related to measured radiance.
Compare the nature of surface and atmospheric interactions with electromagnetic radiation between passive and active satellite sensors.
Evaluate appropriate data for surface monitoring applications, considering how images are formed and the physical relations underlying the retrieval of satellite measured reflectance, temperature and backscattering coefficients.
Analyse the complete remote sensing process from data reception to information extraction, including applying calibration and atmospheric correction methods to image data.

Image Processing and Analysis

Module Leader
  • Dr Daniel Simms

    Extracting information from satellite, aerial and drone image data requires knowledge of a wide variety of image processing techniques. This module will give you the skills to select and apply appropriate image processing techniques for the extraction and analysis of information from image data for applications of remote sensing, for example in land use monitoring and surface change detection.


    Radiometric, spectral and spatial image enhancement: contrast stretching (linear, bilinear, Gaussian, histogram equalisation and manual), digital filtering in the spatial domain (low-pass, high-pass, high-boost, median and directional).

    Band algebra: Derivation of soil and vegetation indices: ratios, normalised differences, PVI, SBI, tasselled cap concept.

    Geometric correction: map projections, selection of ground control points, transform equations, resampling methods (nearest neighbour, bilinear interpolation, cubic convolution).

    Supervised and unsupervised image classification: parametric and non-parametric techniques, clustering, segmentation, pixel and object-based approaches, machine learning, deep learning, and validation (accuracy assessment).

    Post processing, processing chains, change detection, cloud computing and applications.

Intended learning outcomes

On successful completion of this module you should be able to:

Evaluate a wide range of image processing techniques and their underlying mathematical principles.

Select appropriate image processing sequences to achieve predetermined objectives.

Operate and manage an image processing system.

Integrate image processing techniques into applications of remote sensing.

Advanced GIS Methods

Module Leader
  • Dr Abdou Khouakhi

    GIS analyses are based upon increasingly sophisticated methods, but the results are subject to both error and uncertainty. A range of advanced methods are introduced that will have potential use to students in their group and thesis projects and their future careers. Emphasis will be given to the role of GIS in modelling environmental systems and the programming tools available to develop applications.


    Analysis approaches in QGIS – geopackage, database manipulation, handling of geographic data, spatial modelling.
    Spatial analysis: digital terrain modelling and analysis, network analysis.
    Python in ArcGIS Pro (Editor and Notebook).
    The Python editor in ArcGIS and as a standalone program.
    Writing Python scripts (ArcPy and Python API) and handling errors.
    Processing files.
    The object model in GIS.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Assess the quality of geographic data.
  • Apply advanced spatial analyses.
  • Analyse the requirements of a proposed application and synthesise an appropriate solution.
  • Develop scripts to efficiently run complex/time consuming processes.

Environmental Resource Survey

Module Leader
  • Dr Toby Waine

    This module covers the importance of environmental resource surveys that are required to obtain the data used in environmental information management.

    • Introduction to geographical resource survey. Why, when, where and how? Understanding constraints.
    • Introduction to R – a software environment for statistical computing and graphics – and its use in manipulating and visualising survey data.
    • Survey strategies for environmental resources: census with thematic mapping, ground sampling, sampling with property mapping, integrated ground sampling and property mapping.
    • Development of classification schemes – user requirements, data availability, class definitions.
    • Sampling and rapid estimates for plant communities, water and soil quality – biomass, cover and species assessment, count plot methods, plotless sample technique, soil and water survey techniques.
    • Assessment of existing data quality and use in survey design.
    • Statistical design and analysis for environmental resource surveys: area frames, point samples, bulk samples, area samples, sampling at global scales, multi-scale sampling.
    • Quality assessment of environmental data – accuracy measures, effect of bias, quality measures and statistics, error and uncertainty sources and measures.
    • Introduction to interpolation methods, generating maps from point survey data.
    • Integration data sources and types (data fusion) and statistical models with survey data (model data fusion) to increase survey cost effectiveness..
    • Review of example surveys.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Determine the appropriate survey method to undertake an assessment of environmental resources.
  • Evaluate existing information and models which complement the survey method.
  • Design and conduct field surveys for data collection and verification.
  • Select and carry out appropriate modelling and statistical analyses.
  • Summarise and present results of a survey for users effectively.

Web Mapping

Module Leader
  • Professor Stephen Hallett

    Geographical information is now increasingly prevalent in our daily life, affecting personal leisure activities as much as the workplace. Geographical information represents a key theme in environmental management and, indeed, it has been estimated that some 80% of the data used for environmental, business and policy-oriented decision making is geographical in nature. This poses particular challenges to its efficient and timely dissemination to stakeholders and potential end users. Today, the Internet offers a pervasive medium for real-time delivery of geographical information and location-based web services, across a range of computing platforms. Such approaches offer extremely powerful means to reach out to a broad audience of users, particularly those who do not necessarily have the required skills to access or operate specialist GIS software packages. Web mapping offers a means to ‘democratise’ geospatial data – but with a wealth of technical approaches available to develop contemporary web data services and mapping solutions, there needs to be a sound understanding of these choices and approaches if the maximum benefit is to be derived from their analysis and dissemination online. This module provides a solid introduction to the issues concerning the management and dissemination of web mapping and spatial data on the Internet.

    • Introduction to web mapping, spatial data and the Internet.
    • Principles of and strategies for web site development.
    • Introduction to HTML. Review of Internet mapping technologies and solutions: Google Maps API; ESRI JavaScript API; Open Layers API; Leaflet API; ArcGIS Enterprise Server, ArcGIS Online, ArcGIS Server, GeoServer.
    • Introduction to XML/XSLD, GML, JSON/GeoJSON.
    • Proprietary and Open-source toolkits and frameworks (e.g. Dojo).
    • Case study applications of Internet mapping: local authorities, location based services, ‘g-business’.

Intended learning outcomes

On successful completion of this module you should be able to:

  • Appraise contemporary Internet technologies and their application relevant to geographical data dissemination.
  • Apply HTML and CSS to develop web frameworks, drawing on templates as required, demonstrating the application of JavaScript, and the use of mapping Application Programming Interfaces (APIs).
  • Evaluate emergent Internet GIS standards and data transfer strategies and formats (e.g. GML; XML; JSON/GeoJSON).
  • Prepare an internet mapping website, and appraise the utility and use of proprietary versus open source contemporary internet mapping technologies (e.g. ESRI ArcGIS Enterprise and ArcGIS Server, ESRI JavaScript API, Google Maps API, Geoserver, Open Layers API, Leaflet API etc).
  • Evaluate and compare leading proprietary and open source data server technologies (e.g. GeoServer, ESRI ArcGIS Server, ESRI ArcGIS Online, Oracle, Postgres/PostGIS) and examine and debate a selection of real-world internet mapping projects, examples and case studies.


The MSc in Advanced GIS and Remote Sensing is accredited by the Royal Institution of Chartered Surveyors and the Chartered Institution of Civil Engineering Surveyors.

Accreditation provides you with the assurance that the course has been independently assessed as meeting professional standards.

RICS accredited course logo

ICES accreditation logo

How to apply

Click on the ‘Apply now’ button below to start your online application.

See our Application guide for information on our application process and entry requirements.