A 5-day course on the analysis of remotely-sensed topographical and spectral datasets. Through a combination of lectures, computer exercises and fieldwork, delegates will gain advanced knowledge and practical skills manipulating geospatial datasets to characterise and detect changes in land and water surfaces. Read more Read less

Remote sensing has opened up significant opportunities for researchers in earth and environmental sciences. Datasets from a wide range of sources can now be used to study fundamental questions in hydrology, geosciences, terrestrial/aquatic ecology, soil science, etc. These same datasets and analytical approaches are also central to modern environmental assessment / monitoring programmes that inform the development of sustainable environmental management strategies. Consequently, an understanding of how remote sensing data can be used to characterise land and water surfaces is essential for today’s environmental scientist and manager.

This 5 day course will provide delegates with an up-to-date, advanced introduction to the use of remote sensing for environmental sciences. The course will provide an overview of the range of topographical and spectral datasets available, explain their uses and limitations, and demonstrate how they can be applied for research and management purposes. Through a combination of lectures, computer exercises and fieldwork, delegates will learn how to analyse existing remotely-sensed datasets and to collect and analyse their own using digital photography and Structure-from-Motion (SfM) photogrammetry. Case studies will focus on river-floodplain systems, as these present specific challenges to researchers and practitioners.

The course is funded by the Natural Environment Research Council (NERC) Advanced Training Short Course programme. Current PhD students funded by NERC are entitled to a full fee waiver, which covers all costs for the course including fees, UK transportation, accommodation and food. Funded places will be assigned on a first-come, first-serve basis until 18 Dec 2016. After this deadline, funded positions will be opened up to other current PhD students in the order in which they applied. We welcome delegates from outside academia who would like a rigorous introduction to remote sensing, and full details of short course fees can be found below.

At a glance

Course structure

A combination of lectures, computer practicals and fieldwork

What you will learn

At the end of the course, delegates will have achieved the following intended learning outcomes (ILOs):

  • Describe best-practice for the management, assimilation, visualisation and analysis of large RS datasets for geomorphological research and application.
  • Compare the different types of RS data commonly used in environmental research and understand how they can be used to answer fundamental questions in fluvial geomorphology.
  • Visualise, manipulate and analyse topographical data (e.g. Environment Agency’s LiDAR datasets) using GIS to delineate and characterise catchments, rivers and landforms using terrain analysis techniques.
  • Extend terrain analysis through the incorporation and integrated analysis of existing spectral datasets (e.g. aerial and satellite multispectral imagery) to identify and classify landforms, vegetation, and sediment characteristics (e.g. grain size).
  • Summarise and assess the suitability of monitoring sensors and instruments to collect topographical data; and explain the concept of and procedure for SfM-based topographic surveying.
  • Devise and execute a field data collection campaign using a SfM approach to develop a digital elevation model of a site, demonstrating best-practice in data management and survey design

Core content

  • Remotely-sensed (RS) data: types, uses in geomorphology
  • RS data management: best-practices in data acquisition, storage, visualisation, assimilation and analysis
  • Terrain analysis using topographical data
  • Detection and quantification of topographic change
  • Spectral RS datasets and uses in terrain analysis and fluvial geomorphology; classification / segmentation
  • Use of imagery collected by Unmanned Aerial Vehicles (UAVs, drones)
  • Structure-from-Motion (SfM) photogrammetry
  • Design and implementation of a field survey using SfM

Who should attend

This short course is aimed at environmental scientists who are interested in using remote sensing data in their research. The focus is on geomorphology characterisation and detection of change, but it is also suitable for those studying related disciplines, e.g. geology/earth sciences, landscape ecology, soil sciences. The course is also ideal for environmental managers, consultants and practitioners who would like to expand their capabilities in remote sensing data analysis.

Prior experience and a familiarity with GIS, preferably ArcGIS software, is a must for delegates to get the most out of the course.


Not accredited, but it is sponsored by NERC


20% discount for Cranfield alumni, 10% discount for colleagues of alumni

£1200 – member of British Society for Geomorphology or British Hydrological Society

£700  - current PhD student

A number of fully-funded places are available for current PhD students, with priority to those that are NERC-funded. Funding covers fees, UK travel, accommodation and feed. If you would like to be considered for a funded place, please apply immediately  as they will be allocated on a first-come, first-serve basis.

Accommodation options and prices

Accommodation in Mitchell Hall is included for delegates receiving the full NERC fees waiver.

Accommodation is available at Mitchell Hall which is located on campus. All rooms are en-suite and bookings are on a half-board basis. If you would like to book accommodation for this short course at Mitchell Hall, please indicate this on the registration form and we will arrange this for you.

Alternatively, you may wish to make your own arrangements at a nearby hotel.

Location and travel

Cranfield University is situated in Bedfordshire close to the border with Buckinghamshire. The University is located almost midway between the towns of Bedford and Milton Keynes and is conveniently situated between junctions 13 and 14 of the M1.

London Luton, Stansted and Heathrow airports are 30, 90 and 90 minutes respectively by car, offering superb connections to and from just about anywhere in the world. 

Further location and travel details

Location address

Cranfield University
College Road
MK43 0AL

Read our Professional development (CPD) booking conditions.