MSc Data Science (Earth and Environmental Analytics)

Year of entry: 2024

Course unit details:
Fundamentals of Synthetic Aperture Radar (SAR) applied to Environmental Monitoring

Course unit fact file
Unit code GEOG70632
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Available as a free choice unit? No


LIDAR (Light Detection and Ranging) is a remote sensing technology. LiDAR technology uses the pulse from a laser to collect measurements. These are used to create 3D models and maps of objects and environments. Synthetic Aperture Radar (SAR) images provide day-and-night and weather-independent images. LIDAR and SAR can be used for several applications in the fields of geosciences and climate change research, environmental and Earth system monitoring, change detection, security-related applications and planetary exploration (Moreira et al, 2013).

The course will be focusing on practical classes mainly using R studio and SNAP software freely available from ESA (European Space Agency) and also the freely available images from Sentinel 1 (SAR in C band). Some guest speakers from other institutions will be invited to present their work using SAR image processing and other kind of remote sensing images to monitor and estimate forest and land use and land cover characteristics.

Examples of topics that will be covered include:

1. What is SAR? Brief History of Microwaves

2. Applications of SAR to environment studies

3. Fundamentals of SAR

4. What is LIDAR? Applications of SAR to environment studies

6. Practical classes 1: SAR image processing: Backscattering

7. Practical classes 2 SAR processing: Polarimetry

8.  Practical classes 3 LIDAR image processing

9: Practical classes 5: Land use/Land cover change detection

10. Practical classes: Forest structure estimation


Moreira et al, 2013.



The unit aims to: give opportunity to the students to learn the principles, techniques, methods of SAR/ LIDAR remote sensing. Different applications of SAR/LIDAR images will be explored with a focus on forest structure (especially biomass and carbon stocks) and land use / land cover monitoring. At the moment with the increasable growth of the Earth Observation (EO) science and industry it is important to offer opportunities to the students to be in contact with advanced technologies in the remote sensing field.

Teaching and learning methods

The classes will be delivered as a mix of lecture and practical. The course material will be delivered via Blackboard

Knowledge and understanding

  • Have an understanding of principles and applications of remote sensing using SAR and LIDAR
  • Develop an awareness of the importance of using SAR and LIDAR datasets (for the Earth Observation, Ecological and Climate modelling scientific communities) and the possibilities of use and discoveries emerging in science and industry from their use.
  • Learn in practical how to process, analyse and interpret SAR and LIDAR images in environmental studies
  • Develop an awareness of the wide range of remote sensing SAR and LIDAR systems and understand how and why they suit different environmental applications.

Intellectual skills

  • Be able to handle and apply technical concepts of SAR and LIDAR remote sensing and critically evaluate the results.
  • Be able to critically assess and evaluate the suitability of SAR and LIDAR remote sensing for particular applications such as forest structure estimation and land use/land cover monitoring.
  • Develop research skills such as selective reading, critical thinking and evaluating scientific evidence
  • Develop their knowledge by abstracting, synthesising, rethinking ideas and share them.

Practical skills

  • Be able to handle SAR and LIDAR data from a range of systems using computers and appropriate software.
  • Apply key algorithms to interpret SAR remotely sensed imagery.
  • Manage raster data, other spatial data files and filed datastes or field surveys.
  • Source appropriate SAR and LIDAR images from online image archives

Transferable skills and personal qualities

  • Communicate, write and present ideas clearly
  • Process and analyse SAR and LIDAR images
  • Develop logical rationing, numerical (multivariate data-handling and statistical analyses) and presentation skills
  • Develop research plans for SAR and LIDAR image applications and analyses: questions, hypotheses, planning, execution, analyses and conclusions

Assessment methods

Method Weight
Written assignment (inc essay) 60%
Report 40%

Feedback methods

Formative feedback will take place through in class discussions and summative feedback will be provided as written feedback

Recommended reading

Core texts:

  • Jin, Ya-Qiu, and Feng Xu. Polarimetric scattering and SAR information retrieval. John Wiley & Sons, 2013.

Extra books that the Library could buy:

  • Woodhouse, I.H., 2017. Introduction to microwave remote sensing. CRC press.
  • Lusch, D.P., 1999. Introduction to microwave remote sensing. Center for Remote Sensing and Geographic Information Science Michigan State University.

Other learning materials:

Scientific Journals: 

Remote Sensing of Environment (

IEEE Transactions on Geoscience and Remote Sensing (



Study hours

Scheduled activity hours
Lectures 15
Practical classes & workshops 15
Seminars 6
Tutorials 3
Independent study hours
Independent study 111

Teaching staff

Staff member Role
Polyanna Da Conceicao Bispo Unit coordinator

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