Diploma in SAR/Optical/Hyperspectral Data Processing
Online postgraduate diploma of 800 hours in SAR, optical and hyperspectral data processing: 8 modules covering satellite imagery fundamentals, optical and SAR processing, SAR interferometry, hyperspectral imaging, machine learning and operational processing chains, with an assigned technical tutor.
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
Handle optical, SAR and hyperspectral satellite products.
Apply atmospheric and radiometric corrections to optical images.
Process SAR images and generate backscatter products.
Measure ground deformation using interferometry.
Analyse hyperspectral data with spectral unmixing.
Use machine learning for image classification.
Design validated operational processing chains.
Who it's for
- Remote sensing analysts
- Satellite image processing engineers
- SAR specialists
- Geospatial data scientists
- GIS technicians
- EO processing chain developers
- Engineering or science graduates looking to enter Earth observation
What you'll work with
- ISO 19115-1 (geographic information metadata)
- ISO 19157-1 (geographic data quality)
- ISO 19123-1 (schema for coverage geometry and functions)
- ISO 19159-2 (calibration and validation of lidar sensors)
- OGC Web Coverage Service 2.0 (web access to coverage data)
- Regulation (EU) 377/2014 (Copernicus programme)
- Directive 2007/2/EC (INSPIRE) (European spatial data infrastructure)
- SNAP
- QGIS
- Google Earth Engine
- ENVI
- GDAL/Python
8 modules
1.1Processing levels from L0 to L31.2Data formats: GeoTIFF, NetCDF and SAFE1.3Reference systems and map projections1.4Resampling and orthorectification1.5Access platforms: Copernicus and USGS1.6Cloud computing with data cubes1.7Product metadata structure1.8Managing large image volumes1.9Free processing tools1.10Workshop: downloading and preparing Sentinel-2 scenes
2.1Atmospheric correction with Sen2Cor and 6S2.2Cloud and shadow detection2.3NDVI, NDWI and NBR spectral indices2.4Band fusion by pansharpening2.5Topographic illumination correction2.6Supervised and unsupervised classification2.7Multitemporal change detection2.8Cloud-free temporal composites2.9Thematic accuracy assessment2.10Practical exercise: land-cover map with Sentinel-2
3.1Radar geometry: slant range and ground range3.2Speckle and adaptive filters3.3Radiometric calibration to sigma nought3.4Terrain correction with a DEM3.5Polarimetry and decompositions3.6Backscatter over water, vegetation and urban areas3.7Flood detection with SAR3.8Ship tracking in radar images3.9Sentinel-1 time series3.10Laboratory: processing a Sentinel-1 GRD scene
4.1Interferometric phase and coherence4.2Co-registration of SLC images4.3Phase unwrapping4.4Generation of digital elevation models4.5DInSAR for ground deformation4.6PSInSAR and SBAS techniques4.7Atmospheric contributions to phase4.8Monitoring subsidence and infrastructure4.9Validation with GNSS4.10Case study: post-earthquake deformation with DInSAR
5.1PRISMA, EnMAP and AVIRIS sensors5.2Radiometric and smile corrections5.3Dimensionality reduction with PCA and MNF5.4Endmember extraction5.5Linear spectral unmixing5.6Spectral libraries and matching5.7Spectral anomaly detection5.8Applications in mining and agriculture5.9Water quality with hyperspectral data5.10Practical exercise: mineral mapping with EnMAP data
6.1Random Forest and SVM for classification6.2Convolutional networks for segmentation6.3U-Net and transformer architectures6.4Training sets and labelling6.5Multispectral data augmentation6.6SAR and optical data fusion6.7Transfer learning between sensors6.8Spatial validation and data leakage6.9Deployment on cloud platforms6.10Workshop: building segmentation with U-Net
7.1Design of automated processing chains7.2Orchestration with containers7.3OGC standards for data services7.4STAC metadata catalogues7.5Automated quality control7.6Copernicus emergency management services7.7Operational agricultural products7.8Forest monitoring and deforestation7.9Delivery of products to end users7.10Case study: flood monitoring chain
8.1Problem definition and study area8.2Selection of sensors and data8.3Processing chain design8.4Optical and SAR pre-processing8.5Analysis and information extraction8.6Validation of results8.7Product visualisation and delivery8.8Discussion of limitations8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
A 100% online programme on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. You work with SNAP, QGIS, Google Earth Engine, ENVI and GDAL/Python in free, academic or evaluation versions. Practical work is based on real procedures: flood monitoring with radar, multitemporal land-cover mapping and ground deformation measurement using interferometry. Assessment is continuous by module, plus the final project.
Standards covered: ISO 19115-1, ISO 19157-1, ISO 19123-1, ISO 19159-2, OGC Web Coverage Service 2.0, Regulation (EU) 377/2014, Directive 2007/2/EC (INSPIRE).
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
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 over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with SNAP, QGIS, Google Earth Engine, ENVI and GDAL/Python, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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