ECTS credits ECTS credits: 3
ECTS Hours Rules/Memories Hours of tutorials: 3 Expository Class: 9 Interactive Classroom: 12 Total: 24
Use languages Spanish, Galician
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: Agroforestry Engineering
Areas: Cartographic Engineering, Geodesy and Photogrammetry
Center Higher Polytechnic Engineering School
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable
Know the basic theoretical foundations of the remote sensing process and the processing, analysis and interpretation techniques of satellite images. Ability to carry out mapping, obtaining information from satellite images in those aspects related to forest fires. Knowledge of the thematic layers necessary for management in the restoration of burned areas and fire simulators.
Basic contents included in the programme documentation:
- Use of satellites and drones.
- Digital image corrections and processing.
- Extraction and analysis of information.
- Fire and burned area detection and monitoring.
- Thematic layers and use of Geographic Information Systems.
These basic contents are developed along the course duration following the following structure of theoretical lessons:
• Unit 1: Remote sensing fundamentals (2 h).
• Unit 2: Correction levels (2 h).
• Unit 3: Spectral indices (2 h).
• Unit 4: Fire detection and subsequent regeneration (2 h).
• Unit 5: Monitoring the degree of humidity of the vegetation (1 h).
And the following list of practical sessions using Google Earth Engine:
• Session 1. Introduction to Google Earth Engine (2 h).
• Session 2. Image collections in GEE (2 h).
• Session 3. Spectral indices (2 h).
• Session 4. Mapping of burned areas (2 h).
• Session 5. Spatial analysis of burned areas (4 h).
Basic bibliography
• Schowengerdt, R. A. (2007). Remote Sensing. Models and Methods for Image Processing (3rd ed.). Academic Press, Elsevier.
• Chuvieco Salinero, E. (2008). Teledetección ambiental : la observación de la Tierra desde el espacio. Ariel.
• Liu, J.G., Mason, P.J. (2016). Image Processing and GIS for Remote Sensing: Techniques and Applications, Second Edition. Wiley/Blackwell.
• Cardille, J.A., Crowley, M.A., Saah, D., Clinton, N.E. (eds.) (2024). Cloud-Based Remote Sensing with Google Earth Engine. Fundamentals and Applications. Springer.
Complementary bibliography
• Wegmann, M., Benjamin Leutner, Stefan Dech (eds.) (2016). Remote sensing and GIS for ecologists : using open source software. Pelagic Publishing.
• Camara, G., Simoes, R., Souza, F., Sanchez, A., Santos, L., Andrade, P.R., Peletier, Ch., Carvalho, A., Ferreira, K., Queiroz, G., Maus, V. (2022). sits: Data Analysis and Machine Learning on Earth Observation Data Cubes with Satellite Image Time Series.
• Simoes, R., Camara, G., Queiroz, G., Souza, F., Andrade, P.R., Santos, L., Carvalho, A., Ferreira, K. 2021. Satellite Image Time Series Analysis for Big Earth Observation Data. Remote Sensing 13, p. 2428.
• Thenkabail, P.S, John G. Lyon, Alfredo Huete (eds.) (2019). Hyperspectral indices and image classifications for agriculture and vegetation. CRC Press.
• Jensen, John R. (2014). Remote sensing of the environment : an Earth resource perspective. Pearson Education.
• Richards, John A. (2013). Remote sensing digital image analysis : an introduction. Springer.
• Chuvieco, E., Alfredo Huete (2010). Fundamentals of satellite remote sensing. Taylor & Francis.
- COM5-09: Remote sensing technologies and geographic information systems applicable to forest fire prevention, management and analysis.
- HAM5-08: Use remote sensing and geographic information systems to analyse events and processes related to forest fires.
- CM5-01: Ability to design strategies for preventing and fighting forest fires.
• Theoretical lectures (competences COM5-09, CM5-01)
• Practical sessions (competences HAM5-08, CM5-01)
Theoretical and practical sessions will be complemented by:
• Use of the virtual campus (Moodle).
• Practical cases and projects.
• Individualized and group tutoring.
• Autonomous study.
• Evaluation of competence.
Assessment of students’ performance will be based on two components:
• Continuous assessment, based on practical assignments along the duration of the course (HAM5-08, CM5-01). Will account for 70% of final grade.
• Written test (COM5-09, CM5-01). Will account for 30% of final grade.
A minimum of 5 points out of 10 will be required for a passing grade. There will be no minimum required grade in each of the two components. The criteria and requirements will be the same in 1st and 2nd opportunities. Students enrolled for a second time in the course can ask for the grade of one of the elements to be kept.
Students exempt of attendance to classes as provided for in the Attendance Regulations will follow the same assessment system.
The USC Norm for Assessment of Academic Performance will be automatically applied if fraud or fabrication of assessment materials is detected.
This course includes 9 hours of theoretical lectures, 12 hours of practical lectures, and implies around 54 hours of personal work.
It is advisable that students have access to a personal computer in order to install the software applications used in class.
David Miranda Barros
- Department
- Agroforestry Engineering
- Area
- Cartographic Engineering, Geodesy and Photogrammetry
- Phone
- 982822830
- david.miranda [at] usc.es
- Category
- Professor: University Professor
Eduardo Jose Corbelle Rico
Coordinador/a- Department
- Agroforestry Engineering
- Area
- Cartographic Engineering, Geodesy and Photogrammetry
- Phone
- 982823324
- eduardo.corbelle [at] usc.es
- Category
- Professor: University Lecturer
| Tuesday | |||
|---|---|---|---|
| 09:00-11:00 | Grupo /CLE_01 | Galician | Classroom 19 (Pav.II-PPS) |