Remote Sensing and Spatial Modelling

Recommended Prerequisites

There are no specific requirements beyond the general conditions for admission to the study cycle.

Teaching Methods

This unit can be taught partially or totally by e-learning.
Theoretical classes.
Resolution of practical exercises with support on analogical and digital techniques, in this last case, based on GIS software.

Learning Outcomes

By the end of the course the students should be able to:
- understand the theoretical basics of the Remote Sensing techniques;
- know the working of Remote Sensing technologies and how the data are acquired, stored and transferred;
- apply data processing techniques and make a correct interpretation of the same data;
- do data modelling of spatial data using GIS tools;
- apply the bulk of knowledge to resources/environment case studies.

Work Placement(s)

No

Syllabus

- Basic principles of Remote Sensing: nature and properties of the radiation; radiation spectrum, radiation laws; the interaction of radiation with the objects;
- Platforms and sensors - orbits; passive and active sensors (radar and lidar); the case of SAR; examples of sensors and typology of the acquired data;
- The digital image and resolution: the pixel and the raster format; spatial, spectral, radiometric and temporal resolution; the spectral signature of the surfaces;
- Digital image processing and classification: conventional techniques and others, like artificial intelligence and cloud computing;
- Case studies in land, sea and atmosphere, using also non-remote sensing data and modelling in a GIS platform.

Head Lecturer(s)

Alcides José Sousa Castilho Pereira

Assessment Methods

Assessment
Resolution Problems: 40.0%
Exam: 60.0%

Bibliography

John A. Richards, Remote Sensing Digital Image Analysis. An introduction, 6th edition. Springer, 2023.
Morton John Canty, Image Analysis, Classification and Change Detection in Remote Sensing, 4th Edition, CRC Press, 2023.
Emilio Chuvieco, Fundamentals of Satellite Remote Sensing An Environmental Approach, 3rd edition, CRC Press, 2020.
Qingyan Meng, Remote Sensing of Urban Green Space. Springer, 2023.
Jian Guo Liu and Philippa J. Mason, Image Processing and GIS for Remote Sensing. Techniques and Applications, 2nd ed., Wiley Blackwell, 2016.
Elementos de apoio às aulas fornecidos pelos docentes/Elements to support lessons provided by teachers.