Postgraduate Diploma in Satellite Remote Sensing for Damage Assessment
Online 800-hour Postgraduate Diploma in Satellite Remote Sensing for Damage Assessment. 8 modules covering Regulation (EU) 2021/696 (Union Space Programme and Copernicus), Directive 2007/2/EC (INSPIRE) and ESA SNAP. Assigned tutor and open enrolment.
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.
What you will be able to do
Explain the physical principles of optical and radar remote sensing.
Process optical images with radiometric and geometric corrections.
Interpret and process synthetic aperture radar data.
Apply change detection techniques to delineate damage.
Train machine learning models on satellite imagery.
Integrate remote sensing products into insured claim estimation.
Evaluate the quality, legal aspects and operations of damage assessment services.
Who it's for
- Remote sensing analyst wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- GIS specialist in insurance wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- Geospatial data scientist wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- Catastrophe analyst wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- Mass claims loss adjuster wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- Earth observation consultant wishing to specialise in Satellite Remote Sensing for Damage Assessment.
- Graduates in engineering or sciences seeking to enter insurers and reinsurers.
What you'll work with
- Regulation (EU) 2021/696 (Union Space Programme and Copernicus)
- Directive 2007/2/EC (INSPIRE)
- ISO 19115-1 (Geographic Metadata)
- ISO 19157 (Geographic Data Quality)
- LAW 14/2010 (Geographic Information Infrastructures and Services in Spain)
- ISO 19130 (Sensor Models for Imagery)
- Legislative Royal Decree 7/2004 (Consolidated Legal Statute of the Insurance Compensation Consortium)
8 modules · 800 h
1.1Electromagnetic spectrum and interaction with the surface1.2Spectral signatures of materials and vegetation1.3Spatial, spectral, temporal and radiometric resolution1.4Satellite orbits and platforms1.5Passive and active sensors1.6Copernicus programme and Sentinel missions1.7Landsat missions and commercial satellites1.8Product processing levels1.9Access to data and open catalogues1.10Practical: downloading and exploring Sentinel-2 scenes
2.1Radiometric and atmospheric correction2.2Geometric correction and orthorectification2.3Cloud and shadow masks2.4Colour composites and enhancements2.5Spectral indices: NDVI, NDWI and NBR2.6Pansharpening and multispectral fusion2.7Image time series2.8SNAP, QGIS and Earth Engine software2.9Managing large image volumes2.10Laboratory: NBR index after a forest fire
3.1Principles of SAR radar3.2Polarisation and backscatter3.3Sentinel-1 and commercial SAR missions3.4Preprocessing: calibration and speckle filtering3.5Water detection for flooding3.6Interferometric coherence and change3.7InSAR interferometry and deformation3.8Advantages of SAR under cloud cover3.9Limitations in urban areas3.10Practical: flood map with Sentinel-1
4.1Image difference and ratio methods4.2Classification before and after the event4.3Principal component analysis for change4.4Building damage assessment4.5Burned areas and fire severity4.6Agricultural damage from hail and drought4.7Displacement from earthquakes and landslides4.8Copernicus Emergency Management Service4.9International Charter Space and Major Disasters4.10Case study: damage assessment after an earthquake
5.1Supervised classification with Random Forest5.2Convolutional neural networks for satellite imagery5.3Building segmentation with U-Net5.4Damage detection with datasets such as xBD5.5Geospatial foundation models5.6Labelling and training data5.7Validation with confusion matrix5.8Transfer across regions and sensors5.9Explainability and quality control5.10Laboratory: building damage classifier
6.1Rapid loss estimation after catastrophes6.2Prioritising loss adjustments6.3Claim validation and fraud detection6.4Agricultural insurance and vegetation indices6.5Satellite-based parametric insurance6.6Flood risk monitoring6.7Monitoring of insured works and assets6.8Integration with claims systems6.9Costs and commercial imagery licences6.10Case study: designing a parametric drought insurance
7.1Accuracy and field verification7.2Uncertainty in damage estimation7.3Evidentiary validity of satellite imagery7.4Privacy and image resolution7.5Copernicus and commercial data licences7.6Drone and aerial imagery as a complement7.7Operational workflows after an event7.8Communicating results to the business7.9Trends: constellations and high revisit7.10Practical: operational protocol for a DANA
8.1Selection of event and study area8.2Acquisition of pre- and post-event images8.3Data preprocessing8.4Damage detection and mapping8.5Cross-referencing with the insured portfolio8.6Loss estimation8.7Validation of results8.8Report for claims management8.9Written report and presentation8.10Final review with the tutor
How you'll learn
100 % online training on the SEIUM Institute campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the enrolment period, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ESA SNAP, QGIS, Google Earth Engine, Python (rasterio, PyTorch), ENVI, in free, academic or evaluation versions. The case studies are based on real change-detection procedures after floods using Sentinel-1 imagery, burned-area mapping with Sentinel-2, and building damage estimation after a catastrophic event. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the physical principles of optical and radar remote sensing.
Process optical images with radiometric and geometric corrections.
Interpret and process synthetic aperture radar data.
Apply change detection techniques to delineate damage.
Train machine learning models on satellite imagery.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 800 hours spread over 6 to 8 months. That is 10 to 15 hours a week on average, compatible with a full-time job.
The programme uses ESA SNAP, QGIS, Google Earth Engine, Python (rasterio, PyTorch), ENVI. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An own diploma from SEIUM Institute upon passing the continuous assessment and the final integrative project. It is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the advanced programme. Review the recognition policy when you enrol.
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