Master’s Degree in Satellite Observation of the Oceans
Why this master’s programme?
The Master in Satellite Ocean Observation
Offers a comprehensive overview of marine remote sensing techniques and applications. Learn to interpret satellite data to monitor currents, temperatures, water quality, and marine life. Master image processing and the creation of predictive models for the sustainable management of ocean resources and the mitigation of the impact of climate change. This program prepares you to become an expert at the forefront of oceanography.
Differential Advantages
- Cutting-edge Technology: Access to state-of-the-art geospatial analysis software and platforms.
- Real-world Case Studies: Analysis of international marine monitoring and conservation projects.
- Leading Experts: Masterclasses taught by renowned researchers and professionals.
- Practical Approach: Development of individual and collaborative projects using real data.
- Career Opportunities: Extensive opportunities in research, environmental consulting, and resource management.
- Modality: Online
- Level: Masters
- Hours: 1600 H
- Start date: 25-08-2026
Availability: 1 in stock
Who is it aimed at?
- Oceanographers and climatologists interested in monitoring large-scale ocean variables and understanding their impact on global climate.
- Environmental engineers and consultants seeking advanced tools for coastal management, risk assessment, and resource planning.
- Fisheries and aquaculture researchers who need accurate data on water temperature, salinity, and biomass to optimize their studies.
- Maritime industry professionals who want to improve the safety and efficiency of navigation by using real-time satellite information.
- Students and recent graduates in marine science, geophysics, or related fields seeking a cutting-edge specialization with applications Work experience in the job market.
Flexibility and Application
The master’s program adapts to your pace: flexible online format, practical projects, and focus on solving real-world problems in the sector.
Objectives and skills
Managing oceanographic satellite data:
“Process and validate the information, integrating it into oceanographic models and visualization systems for decision-making.”
Assess and predict the impact of climate change on the oceans:
“Analyze oceanographic data and climate models to identify coastal risks and propose mitigation strategies adapted to each marine ecosystem.”
Develop and apply algorithms for advanced analysis of ocean satellite images:
“Implement deep learning-based segmentation techniques to identify and classify ocean objects and phenomena with high accuracy.”
Design and validate numerical models of ocean circulation:
Ensure the stability and accuracy of the model by calibrating it with observational data and evaluating its sensitivity to different parameters and forcing conditions.
Implement and optimize coastal and ocean monitoring systems:
Integrate data from multiple sources (in situ sensors, satellites, numerical models) to generate robust and representative information on the state of the ocean and coast.
Leading research and development projects in ocean remote sensing:
“Define objectives, scope and resources, managing risks and multidisciplinary teams to generate innovative results and high-impact scientific publications.”
Study plan – Modules
- Fundamentals of satellite sensors: physical principles, electromagnetic spectra, and properties of electromagnetic radiation in the visible, infrared, and microwave ranges for oceanographic studies.
- Types of satellite sensors: classification, operation, and specific applications of passive (radiometric, spectroradiometer) and active (synthetic aperture radar – SAR, altimeters) sensors.
- Emerging technologies in oceanographic sensors: hyperspectral sensors, satellite LIDAR, and combinations of multispectral sensors for an integrated view of the marine environment.
- Satellite platforms: detailed analysis of constellations, polar and geostationary orbits, and their implications for the temporality and spatial coverage of oceanographic data.
- Advanced data acquisition and preprocessing processes: radiometric correction, geometric correction, In-situ calibration and multi-sensor fusion techniques to improve the quality and accuracy of observations.
Digital signal processing models applied to marine satellite imagery: spatial filtering, texture analysis, pattern extraction, and automatic detection of oceanographic phenomena.
Quantitative monitoring of oceanographic variables: sea surface temperature (SST), chlorophyll concentration, marine altimetry, waves, currents, and salinity from satellite data.
Interpretation and validation of satellite data through integration with oceanographic stations, buoys, CTD profiles, and numerical ocean models.
Advanced tools and software for satellite image analysis: GIS platforms, machine learning algorithms, and artificial intelligence techniques focused on marine monitoring.
Practical applications and case studies: Monitoring extreme events, such as red tides and oil spills, and monitoring climate change through continuous satellite observations.
[…]
- Fundamentals of satellite remote sensing: physical principles, types of sensors, and orbital platforms
- Spectral characteristics of the oceans: analysis of reflectance, fluorescence, and thermal emission
- Advanced satellite image processing: atmospheric correction, georeferencing, and temporal mosaicking
- Detection and quantification of oceanographic parameters: surface temperature, chlorophyll, turbidity, and suspended matter concentration
- Interpretation models for water quality and monitoring of biogeochemical events
- Integration of in-situ data with satellite observations for calibration and validation
- Application of artificial intelligence and machine learning algorithms in the analysis of satellite ocean data
- Monitoring of marine ecosystems: coral reefs, upwelling zones, and benthic habitats using
- Remote observation
- Temporal and spatial analysis for sustainable management: assessing trends, extreme events, and changes in biodiversity
- Design of satellite-based early warning systems for mitigating environmental impacts and marine disasters
- Specialized software tools for processing and visualizing large volumes of satellite data
- Case studies and advanced studies of ocean management using satellite data in international contexts
- International regulations and standards for the management and use of satellite data in the marine environment
- Ethical and legal aspects of the collection, use, and dissemination of satellite information for marine environmental management
- Future perspectives and technological trends in satellite observation applied to oceanography and marine ecosystem conservation
- Fundamentals of Satellite Sensors: physical principles, types of sensors (optical, radar, altimetry, spectrometry) and technical characteristics for ocean observation
- Satellite Platforms: polar, geostationary, and sun-synchronous satellite constellations; Orbits, revisits, and global coverage
Data Acquisition Technologies: radiometry, interferometry, and spectroscopy applied to oceanographic parameters
Digital Image Processing: radiometric and geometric calibration, atmospheric correction, and multisensor fusion algorithms
Interpretation of satellite data for ocean variables: surface temperature, chlorophyll concentration, salinity, and sea state
Monitoring of Dynamic Phenomena: analysis of currents, waves, and eddies using advanced remote sensing techniques
Validation and Correction Models: use of oceanographic buoys, ARGO profiles, and in-situ campaigns to ensure precision and accuracy
Integrated Geographic Information Systems (GIS) and advanced visualization for spatial and temporal analysis of ecosystems Marine Environments
- Applications of Artificial Intelligence and Machine Learning: automatic classification, anomaly detection, and prediction of extreme oceanographic events
- Case Studies: monitoring of critical coastal areas, assessment of anthropogenic impacts, and sustainable management based on satellite data
- International Standards and Regulations: compliance and interoperability of satellite data for scientific and regulatory use
- Resolving Capabilities and Technological Limitations: critical analysis of spatial, temporal, and spectral resolution for decision-making
- Optimization of workflows for continuous and real-time management of satellite oceanographic information
- Multidisciplinary Integration: combining satellite data with oceanographic modeling and environmental early warning systems
- Future perspectives and technological advances in satellite sensors: nanosatellites, Commercial constellations and improvements in digital processing
- Fundamentals of multisensor fusion: physical principles, algorithms, and techniques for integrating satellite and in-situ data
- Types of satellite sensors: optical sensors, synthetic aperture radar (SAR), altimeters, spectroradiometers, and sea surface temperature (SST) sensors
- In-situ measurements: oceanographic buoys, CTD profiles, coastal radars, and autonomous platforms
- Advanced signal processing: normalization, time synchronization, and atmospheric correction
- Oceanographic operational modeling: mathematical foundations, hydrodynamic modeling, atmosphere-ocean coupling, and data assimilation into numerical models
- Prediction of oceanographic phenomena: waves, currents, internal tides, extreme events, and coastal processes
- Development and validation of early warning systems: design, thresholds, protocols, and feedback
- operational
- Smart coastal services: real-time monitoring, sustainable resource management, and environmental risk mitigation
- Satellite-based fisheries applications: aggregation detection, biomass estimation, and adaptive fisheries management
- Case studies and practical applications: multisensor integration for red tide management, environmental monitoring, and emergency response
- Specialized platforms and software: real-time visualization, processing, analysis, and distribution of oceanographic products
- Challenges and future perspectives in multisensor fusion and operational modeling: artificial intelligence, big data, and cloud computing applied to satellite oceanography
- Fundamentals of Big Data in Satellite Oceanography: characteristics, sources, and types of massive data applied to ocean observation
- Technological infrastructure for storage and processing: distributed architectures, cloud systems, and NoSQL databases specialized in geospatial data
- Advanced techniques for preprocessing and cleaning satellite data: radiometric correction, noise filtering, handling missing data, and multi-sensor calibration
- Supervised and unsupervised machine learning models applied to classification and segmentation of ocean images: convolutional neural networks, Random Forest, SVM, and advanced clustering
- Deep learning for automatic detection of dynamic patterns on ocean surfaces: detection of extreme events, algal blooms, thermal fronts, and surface currents
- Implementation of real-time analysis pipelines: orchestration of data flows Satellite imagery, streaming processing, and predictive alerts using adaptive algorithms.
Multi-source data integration: combining optical imagery, radar, and in-situ data to improve the accuracy of predictive models and contextual interpretation.
Advanced visualization of oceanographic Big Data: using GIS tools, interactive 3D platforms, and customized dashboards for scientific and operational decision-making.
Model validation and evaluation: specific metrics for interpreting satellite imagery, cross-testing, and uncertainty analysis in oceanographic predictions.
Real-world case studies and practical application: detailed analysis of recent ocean events using Big Data and machine learning, with an emphasis on their environmental and economic relevance.
- Fundamentals of satellite remote sensing: physical and electromagnetic principles applied to oceanographic sensors
- Types of satellite sensors: synthetic aperture radar (SAR), passive radiometers, altimeters, and hyperspectral spectrometers
- Innovations in optical sensors: multispectral detection and advanced techniques for the discrimination of organic matter and sediments
- Monitoring key oceanographic parameters: surface temperature, salinity, chlorophyll, turbidity, and sea level
- Advanced satellite signal processing: calibration algorithms, atmospheric correction, and multisensor data fusion
- Emerging satellite platforms and constellations: CubeSats, nanosatellites, and continuous observation systems
- Integrating satellite data with oceanographic models
Numerical methods for prediction and sustainable management
Applications in coastal management and environmental protection: detection of spills, marine toxin events, and monitoring of sensitive habitats
International standards and regulations in oceanographic satellite observation: interoperability and open access to data
Development and use of specialized software platforms for the visualization, analysis, and dissemination of ocean satellite information
- Fundamentals of satellite sensors: physical and technological principles of remote sensing in the electromagnetic spectrum applied to oceans
- Design and evolution of optical, multispectral, hyperspectral, and synthetic aperture radar (SAR) sensors for marine monitoring
- Advanced satellite data processing: atmospheric correction, radiometric calibration, and filtering algorithms to improve data quality
- Integration of satellite systems with in-situ platforms and oceanographic data for the validation and improvement of remote sensing products
- Predictive modeling applied to ocean dynamics: development and implementation of numerical models based on satellite data to predict physical and biogeochemical variables
- Application of artificial intelligence and machine learning in the interpretation and multitemporal analysis of satellite series for the early detection of ecological anomalies
- Techniques Advanced remote sensing techniques for monitoring critical oceanographic phenomena: coral bleaching events, harmful algal blooms, and oil spills.
Methodologies for assessing human impact on marine ecosystems using indicators derived from satellite sensors and ecosystem modeling.
Development of decision support systems for sustainable management based on near real-time satellite data.
Case studies and regional and global impact assessments in marine conservation, using state-of-the-art satellite technology and integrated predictive models.
- Fundamentals of digital satellite signal processing: acquisition, preprocessing, and radiometric calibration
- Development and application of advanced artificial intelligence (AI) algorithms for the automatic detection and classification of ocean parameters
- Convolutional neural networks (CNNs) and deep learning for the segmentation and analysis of marine satellite images
- Implementation of supervised and unsupervised learning techniques for the identification of biogeochemical and physical patterns in marine ecosystems
- Optimization of predictive models using genetic algorithms and evolutionary methods in the sustainable management of ocean resources
- Integration of multisensor data from optical, radar, and altimetry satellites for improved spatial and temporal resolution
- Application of artificial intelligence for the real-time monitoring of critical oceanographic phenomena such as fronts, upwellings and bleaching events
- Evaluation of satellite data quality and advanced atmospheric correction techniques to increase observational accuracy
- Design of automated and interoperable workflows for the massive processing of satellite data in high-performance computing (HPC) environments
- Analysis of case studies and integrated projects that apply artificial intelligence for the adaptive management of marine protected areas and mitigation of environmental impacts
- Fundamental Principles of Satellite Observation: Physical and Technological Concepts Behind Remote Sensing Applied to Oceans
- Advanced Types of Satellite Sensors: Hyperspectral Spectroradiometers, SAR Radars, Multi-Mission Altimeters, and LiDAR Systems for Ocean Sensing
- Satellite Data Processing and Calibration: Atmospheric, Radiometric, and Geometric Correction to Ensure Accuracy in Time Series
- Oceanographic Modeling: Integration of Satellite Data with Hydrodynamic, Biochemical, and Climate Models for Simulation and Prediction of Marine Variables
- Sensor Fusion Techniques: Multi-Platform and Multi-Spectral Combination to Improve the Spatial and Temporal Resolution of Monitoring
- Big Data in Oceanography: Data Architectures, Cloud Storage, and Management Systems for Large Volumes Ocean information
- Application of artificial intelligence and machine learning in satellite data analysis: automatic detection of phenomena such as algal blooms, acidification events, and currents
- Real-time monitoring and operational control: sensor platforms and networks for monitoring vulnerable ecosystems and responding to critical events
- Advanced visualization tools and geographic information systems (GIS) for interpretation and decision-making in marine management
- Case studies and integrated applications: sustainable management of marine protected areas, monitoring of pollutants and fisheries resources, prevention of natural disasters and climate change
- Design and structuring of the final project: comprehensive planning and definition of scientific and applied objectives
- Satellite data sources: optical sensors, radar, altimetry, spectroradiometers, and multispectral systems for ocean monitoring
- Advanced satellite data processing: atmospheric correction, radiometric calibration, data fusion, and time-spectral analysis
- Predictive modeling: numerical techniques and machine learning algorithms applied to ocean dynamics and biogeochemical variables
- Integration of satellite data with hydrodynamic and ecological models for assessing the health status of marine ecosystems
- Applications for sustainable management: monitoring habitat changes, extreme weather events, species proliferation, and water quality
- Development of specific satellite indicators for marine conservation and environmental policy assessment
- Management of large volumes of data: cloud platforms, Big Data, and Geographic Information Systems (GIS) applied to remote oceanography
- Validation and verification of results: comparison with in-situ data, uncertainty analysis, and continuous improvement methodologies
- Preparation of technical and outreach reports: professional structuring, advanced data visualization, and effective communication for scientific and political stakeholders
Career prospects
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- Oceanographic Data Scientist: Analysis of satellite data for studies of climate, ocean currents, and water quality.
- Coastal Hazard Analyst: Modeling and prediction of extreme events such as storm surges and coastal flooding.
- Environmental Consultant: Environmental impact assessment of maritime activities and development of mitigation strategies.
- Researcher at Academic Institutions: Development of new techniques for ocean observation and modeling.
- Officer in Government Agencies: Monitoring of illegal fishing, control of marine pollution, and management of marine protected areas.
- Marine Remote Sensing Specialist for Companies: Development of products and services based on satellite data for the maritime, energy, and insurance industries.
- Geospatial Software Developer: Creation of tools and platforms for the processing and visualization of oceanographic satellite data.
- Earth Observation Project Manager: Coordination of multidisciplinary teams for the implementation of satellite missions and ocean monitoring programs.
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Entry requirements
Academic/professional profile:
Bachelor’s degree in Nautical Science/Maritime Transport, Naval/Marine Engineering or a related qualification; or proven professional experience on the bridge/in operations.
Language proficiency:
Functional Maritime English (SMCP) recommended for simulations and technical materials.
Documentation:
Updated CV, copy of qualification or seaman’s book, national ID/passport, motivation letter.
Technical requirements (for online):
Device with camera/microphone, stable internet connection, monitor ≥ 24” recommended for ECDIS/Radar-ARPA.
Admissions process and dates
Online
application
(form + documents).
Academic review and interview
Admissions decision
Admissions decision
(+ scholarship offer if applicable).
Place reservation
(deposit) and enrolment.
Induction
(access to the virtual campus, calendars, simulator guides).
Scholarships and financial support
- Advanced Analysis: Master the techniques for processing and analyzing ocean satellite data.
- Cutting-edge Technology: Work with the latest platforms and sensors for ocean observation.
- Practical Applications: Learn to apply knowledge in areas such as marine resource management, climate change, and navigation.
- Leading Experts: Train with renowned professionals in the field of satellite oceanography.
- Innovative Research: Participate in leading-edge projects and contribute to the advancement of knowledge oceanic.
Testimonials
This master’s program provided me with the tools and knowledge necessary to develop an algorithm that detects harmful algal blooms with 95% accuracy, using Sentinel-2 data. This algorithm is already being implemented in an early warning system for the aquaculture industry, mitigating millions in losses and protecting public health.
During the Master’s program in Space & Satellite Technology applied to the Sea, I developed a satellite image processing algorithm that improved the detection of microplastics by 30% compared to traditional methods, and this algorithm is already being implemented by a marine conservation organization.
I applied the knowledge I gained from my Master’s degree in Satellite Ocean Observation to develop an algorithm that detects harmful algal blooms with 95% accuracy, surpassing traditional methods. This algorithm is already being used by a government agency to protect public health and local aquaculture.
I applied my Master’s degree knowledge to develop an algorithm that detects harmful algal blooms with 95% accuracy, anticipating red tide events and minimizing their impact on the local aquaculture industry. This algorithm was successfully implemented in the regional monitoring system, generating early warnings that reduced economic losses by 30% in the last year.
Frequently asked questions
Yes. The itinerary includes ECDIS/Radar-ARPA/BRM with harbor, ocean, fog, storm, and SAR scenarios.
Online with live sessions; hybrid option for simulator/practical placements through agreements.
Satellite remote sensing data, such as sea surface temperature, ocean color, sea surface height, surface winds, ocean currents, and waves.
Recommended functional SMCP. We offer support materials for standard phraseology.
Yes, with a relevant degree or experience in maritime/port operations. The admissions interview will confirm suitability.
Optional (3–6 months) through Companies & Collaborations and the Alumni Network.
Simulator practice (rubrics), defeat plans, SOPs, checklists, micro-tests and applied TFM.
A degree from Navalis Magna University + operational portfolio (tracks, SOPs, reports and KPIs) useful for audits and employment.
- Design and structuring of the final project: comprehensive planning and definition of scientific and applied objectives
- Satellite data sources: optical sensors, radar, altimetry, spectroradiometers, and multispectral systems for ocean monitoring
- Advanced satellite data processing: atmospheric correction, radiometric calibration, data fusion, and time-spectral analysis
- Predictive modeling: numerical techniques and machine learning algorithms applied to ocean dynamics and biogeochemical variables
- Integration of satellite data with hydrodynamic and ecological models for assessing the health status of marine ecosystems
- Applications for sustainable management: monitoring habitat changes, extreme weather events, species proliferation, and water quality
- Development of specific satellite indicators for marine conservation and environmental policy assessment
- Management of large volumes of data: cloud platforms, Big Data, and Geographic Information Systems (GIS) applied to remote oceanography
- Validation and verification of results: comparison with in-situ data, uncertainty analysis, and continuous improvement methodologies
- Preparation of technical and outreach reports: professional structuring, advanced data visualization, and effective communication for scientific and political stakeholders
Request information
Complete the Application Form.
Attach your CV/degree certificate (if you have it to hand).
Indicate your preferred cohort (January/May/September) and whether you would like the hybrid option with simulator sessions.
An academic advisor will contact you within 24–48 hours to guide you through the admission process, scholarships, and compatibility with your professional schedule.
Faculty
Eng. Tomás Riera
Full Professor
Eng. Tomás Riera
Full Professor
Naval engineer specializing in the selection, integration, and optimization of propulsion systems for yachts, high-speed craft, and service vessels.
Eng. Sofía Marquina
Full Professor
Eng. Sofía Marquina
Full Professor
Materials engineer specializing in marine composites and corrosion protection systems for ships, yachts, and port structures.
Eng. Javier Bañuls
Full Professor
Eng. Javier Bañuls
Full Professor
Naval electrical engineer with over fifteen years of experience in the design, integration, and operation of power and automation systems.
Dr. Nuria Llobregat
Full Professor
Dr. Nuria Llobregat
Full Professor
Specialist in meteorological and operational decision-making for coastal and offshore navigation, integrating wind, wave, and current models.
Dr. Pau Ferrer
Full Professor
Dr. Pau Ferrer
Full Professor
Naval engineer with a PhD in applied hydrodynamics and over a decade of experience designing high-performance hulls and marine structures.
Cap. Javier Abaroa (MCA)
Full Professor
Cap. Javier Abaroa (MCA)
Full Professor
MCA-certified captain with command of ocean-going vessels, specializing in advanced maneuvering, navigation management, and bridge safety.