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CourseInsurance, Risk & Actuarial Data Applications open

Course in Satellite Data Analytics for Catastrophic Risks

Online 300-hour course in satellite data analytics for catastrophic risks. 6 modules covering Directive 2007/2/EC (INSPIRE), ISO 19115 (geographic metadata) and Google Earth Engine. Assigned tutor and open enrolment.

Duration300 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute certificate
Enrol now View syllabus Ask an advisor

Course in Satellite Data Analytics for Catastrophic Risks — studying from the United States

Insurance and risk analysis are central to the American financial system, with major hubs in Hartford, New York, Chicago and Des Moines. Insurers, reinsurers and consulting firms rely on actuarial models, catastrophe modeling and data analytics to price risk and manage capital. Engineers with quantitative skills contribute to underwriting, claims analysis and risk assessment for sectors such as automotive, aviation and property. State insurance regulators and professional credentialing bodies shape the profession's standards.

Fees for the United States: 830 US$ (US Dollars), with instalments and employer sponsorship available.

Relevant bodies in the United States

  • National Association of Insurance Commissioners (NAIC)
  • Society of Actuaries (SOA)
  • Casualty Actuarial Society (CAS)
  • American Academy of Actuaries

Typical roles

  • Actuarial Analyst
  • Risk Engineer
  • Catastrophe Modeling Analyst
  • Underwriting Data Analyst

Questions from the United States

Are fees shown in US Dollars?

Yes. All fees on this site are shown in US Dollars, and instalment options are available for many programmes.

Do I get a tutor?

Yes. Every learner is assigned a dedicated technical tutor who supports progress throughout the programme and the final project.

Virtual lab · try it before you enrol

Take the controls.

Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.

SIM · LIVE ●
Learning outcomes

What you will be able to do

01

Understand the satellite missions and products useful for natural hazard analysis.

02

Pre-process optical and radar imagery: correction, masking and mosaicking.

03

Detect and map floods, fires and wind damage from space.

04

Overlay insured exposure with hazard and vulnerability layers.

05

Estimate losses after an event and prioritise claims response.

06

Assess the quality, resolution and limitations of satellite data.

07

Carry out a complete satellite analysis of a real catastrophic event.

Profile

Who it's for

  • Catastrophic risk analyst wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Remote sensing specialist wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Geospatial analyst in insurance wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Catastrophe modeller wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Environmental data scientist wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Risk accumulation technician wishing to specialise in Satellite Data Analytics for Catastrophic Risks.
  • Engineering or science graduates seeking to enter insurance and reinsurance.
Standards & tools

What you'll work with

  • Directive 2007/2/EC (INSPIRE)
  • ISO 19115 (geographic metadata)
  • ISO 19157 (geographic data quality)
  • Directive 2007/60/EC (flood risk assessment and management)
  • Regulation (EU) 377/2014 (Copernicus programme)
  • Directive 2009/138/EC (Solvency II)
Syllabus

6 modules · 300 h

  1. 1.1What a satellite can see and what it cannot, however much one insists
  2. 1.2Orbits and spatial, temporal and spectral resolution
  3. 1.3Optical, radar and thermal sensors
  4. 1.4Public programmes and commercial providers
  5. 1.5Product processing levels
  6. 1.6Cost, latency and real data availability
  7. 1.7Use cases in insurance and risk management
  8. 1.8Limitations: cloud cover, night-time and revisit period
  9. 1.9Remote sensing vocabulary for non-specialists
  10. 1.10Exercise: choosing the right source for three problems
  1. 2.1Geometric and radiometric correction
  2. 2.2Mosaics, clipping and time series
  3. 2.3Spectral indices and what each one measures
  4. 2.4Supervised and unsupervised classification
  5. 2.5Change detection between two dates
  6. 2.6Synthetic aperture radar and interferometry
  7. 2.7Digital elevation models
  8. 2.8Fusion with ground and meteorological data
  9. 2.9Validation with ground truth
  10. 2.10Practice: calculating an index and validating it
  1. 3.1Flood: mapping extent and estimating depth
  2. 3.2Fire: active detection and delineation of burnt area
  3. 3.3Drought and vegetation water stress
  4. 3.4Storm and hail: footprint and severity
  5. 3.5Earthquake and structural damage detection
  6. 3.6Subsidence and slow ground movements
  7. 3.7Coastal erosion and shoreline change
  8. 3.8Surface temperature and heatwaves
  9. 3.9Combined hazards and cascading effects
  10. 3.10Practice: delineating the extent of a real flood
  1. 4.1Locating and characterising assets from imagery
  2. 4.2Inferred construction typology and its limits
  3. 4.3Crops: area and vegetative condition
  4. 4.4Linear infrastructure and its monitoring
  5. 4.5Cross-referencing with the insured portfolio
  6. 4.6Accumulation and risk concentration
  7. 4.7Underwriting control with prior imagery
  8. 4.8Verification of client declarations
  9. 4.9Prevention and recommendations to the insured
  10. 4.10Practice: analysing the exposure of a portfolio
  1. 5.1Parametric triggers based on satellite observation
  2. 5.2Remote loss adjustment and prioritisation after the event
  3. 5.3Rapid loss estimation
  4. 5.4Fraud detection by comparing before and after imagery
  5. 5.5Uncertainty and how the result is communicated
  6. 5.6Integration into company systems
  7. 5.7Cost of analysis versus savings achieved
  8. 5.8Data protection and privacy
  9. 5.9Model governance and audit
  10. 5.10Practice: claims report with satellite support
  1. 6.1Choice of hazard and territory
  2. 6.2Selection of data sources
  3. 6.3Design of the processing workflow
  4. 6.4Analysis and results obtained
  5. 6.5Validation with field data
  6. 6.6Integration with the portfolio
  7. 6.7Proposal for operational use
  8. 6.8Cost-benefit analysis
  9. 6.9Project report
  10. 6.10Project defence
Methodology, software & labs

How you'll learn

100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, making it possible to combine with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Google Earth Engine, QGIS, SNAP (ESA), Python (rasterio), ArcGIS Pro, in free, academic or evaluation versions. Case studies are based on real procedures for mapping flood footprints using radar imagery, cross-referencing insured exposure with hazard maps, and post-event damage analysis of portfolios. Assessment is continuous by module plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with track records in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, OT cyber-security, DIH and compliance as pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Choice of hazard and territory

Understand the satellite missions and products useful for natural hazard analysis.

Selection of data sources

Pre-process optical and radar imagery: correction, masking and mosaicking.

Design of the processing workflow

Detect and map floods, fires and wind damage from space.

Analysis and results obtained

Overlay insured exposure with hazard and vulnerability layers.

Validation with field data

Estimate losses after an event and prioritise claims response.

Career opportunities

Where this takes you

Catastrophic risk analystRemote sensing specialistGeospatial analyst in insuranceCatastrophe modellerEnvironmental data scientistRisk accumulation technician
Admissions & scholarships

Requirements

  • No prior qualification required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient level of Spanish to follow technical standards reading.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

Apply now Scholarships
FAQ

Frequently asked questions

The programme totals 300 hours, spread over 3 to 5 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.

You work with Google Earth Engine, QGIS, SNAP (ESA), Python (rasterio), ArcGIS Pro. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

SEIUM's own diploma upon passing continuous assessment and the integrative project. It is in-house training, not an official title issued by the Ministry.

Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Check the recognition policy when you enrol.

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