Advanced remote sensing
Objectives and Contextualisation
This optional module, expands the knowledge acquired in the module of obtaining geographic information of this same master's degree from the study of techniques and applications specific to remote sensing in fields such as meteorology, oceanography, geology and the study of vegetation.
At the end of the course, the student will be able to:
Apply the methodologies to alleviate the different sources of error in order to visualize and extract physical parameters of the received data.
Apply remote sensing techniques to different fields of research and applied.
RS & METEOROLOGY. TECHNIQUES & EXAMPLES
1. Introduction
2. Classical meteorology
3. Interpretation of satellite images
3.1 Images in the visible spectrum
3.2 Images in the thermal infrared
3.3 Images of water vapor
3.4 Compositions RGB
4. The weather radar
4.1 Propagation of the microwave into the atmosphere
4.2 The radar equation
4.3 Observations of the Doppler radar
RS & OCEANOGRAPHY. TECHNIQUES & EXAMPLES
1. Introduction
2. Fundamentals of Oceanography
2.1 Descriptive oceanography
2.2 Dynamic oceanography
2.3 Remotely observable phenomena
3. Observation with passive sensors
3.1 Observation in the visible spectrum
3.2 Observation in the infrared spectrum
3.3 Observation in the microwave spectrum
4. Observation with active sensors
4.1 Generalities
4.2 The dispersometer
4.3 The SAR
4.4 The altimeter
5. Application: sea currents
RS & GEOLOGY. TECHNIQUES & EXAMPLES
Contents based on a series of guided practical exercises dedicated to showing examples of the use of Remote Sensing in the monitoring of volcanoes, episodes of floods, monitoring of the evolution of snow and ice, etc.
RS & VEGETATION. TECHNIQUES & EXAMPLES
1. The problematic thematic/spectral classes. Land uses and land coverings.
2. Specific techniques.
2.1 Spectral separability
2.2 Vegetation indexes
2.3 Tasseled Cap Transformation.
3. Prevention of forestfires.
4. Active fire.
5. Techniques of analysis of changes in time.
5.1 Assessment of burnt surfaces.
5.2 Studies of regeneration of vegetation after forest fires.
6. Analysis and multitemporal classification of roofs (example of crops)
6.1 Spectral signatures
6.2 Phenology and temporary signatures
6.3 Classification
6.4 Analysis of changes
6.5 Enrichment of databases
7. Examples of practical applications
Competences
Apply different methodologies for the primary processing of images obtained by remote sensors in order to subsequently extract geographic information.
Continue the learning process, to a large extent autonomously.
Identify and propose innovative, competitive applications based on the knowledge acquired.
Take a holistic approach to problems, offering innovative solutions and taking appropriate decisions based on knowledge and judgement.
Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
Use the different techniques for obtaining information from remote images.
Write up and publicly present work done individually or in a team in a scientific, professional context.
Learning Outcomes
Apply remote sensing techniques to different research and applied-research fields.
Continue the learning process, to a large extent autonomously.
Correctly apply methodologies to mitigate the different sources of error in order to visualise and extract physical parameters from the data received.
Identify and propose innovative, competitive applications based on the knowledge acquired.
Take a holistic approach to problems, offering innovative solutions and taking appropriate decisions based on knowledge and judgement.
Use acquired knowledge as a basis for originality in the application of ideas, often in a research context.
Write up and publicly present work done individually or in a team in a scientific, professional context.
Presential
FALSE
Advanced remote sensing
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or HaDEA. Neither the European Union nor the granting authority can be held responsible for them. The statements made herein do not necessarily have the consent or agreement of the ASTRAIOS Consortium. These represent the opinion and findings of the author(s).
