2025

Remote Sensing

Name: Remote Sensing
Code: ERU13357L
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area: Geography

Teaching languages: Portuguese
Languages of tutoring support: Portuguese, English, Spanish
Regime de Frequência: Presencial

Sustainable Development Goals

Learning Goals

To obtain knowledge of the theoretical concepts of remote sensing; to develop practical skills in the interpretation and digital processing of satellite images and their connection with the geographic databases. To know the behavior of the natural surfaces with electromagnetic radiation, namely through the study of the respective spectral signatures. Satellite image classification, using differente methods, in order to obtain different types of information on the terrestrial surface, at different scales. Realize the importance of new technologies in the development of modern societies.

Contents

I.GNSS concepts
II.Photointerpretation Concepts
III.Fundamentals of Remote Sensing
3.1.Earth observation data 3.2.Electromagnetic Radiation/Spectrum 3.3.Laws of thermal radiation, 3.4.Interaction with the atmosphere and image correction; 3.5.Interaction with the Earth's surface 3.6.Active and passive sensors
IV.Characteristics of images
4.1.Concept of resolution (spectral, spatial, temporal, radiometric)
V.Remote Sensing systems
5.1.Platforms and their characteristics 5.2.Components and orbits of satellites; 5.3.Sensors and their characteristics; 5.5.Applications and characteristics of its satellites and optical sensors
VI.Processing and image analysis
6.1.Visual interpretation,6.2.Pre-processing (geometric and radiometric corrections),4.3.Transformation of the data (Vegetation indices, principal component analysis; Tasseled Cap Transformation),6.4.Multispectral segmentation; 6.5.Classification imaging (supervised, unsupervised, object-oriented);6.6.Change detection
VII.GEE

Teaching Methods

In each class, theoretical concepts are presented using PowerPoint, and practical exercises are performed in an image processing program, where skills in the analysis, interpretation, and digital processing of satellite images are developed.

Various materials are available on the Moodle platform (e.g., a textbook with theoretical concepts, support text for the exercises carried out in class, PowerPoint presentations, web pages, and videos with resolution of the practical exercises).

Assessment

The assessment is continuous and includes two tests, the first in the middle of the semester and the second in the last week of the semester. Both cover theoretical concepts and practical exercises performed using the image processing program utilized in class. Additionally, students complete four practical assignments throughout the semester, with the first being conducted entirely in the classroom, while the remaining assignments are completed partly in and partly as independent work by the student.

The final grade is obtained as follows:
Average score of the two tests - 80%
Practical work - 20%