List of Great Tutorials for ESA SNAP

This time I've collected a list of tutorials for ESA SNAP for beginners and for advanced users. Some are already a few years old, but still can be used with the current SNAP version. Please forgive me, that I have not watched and stepped through all these videos. But at least I went through them quickly. If you have any problems with the tutorials, let me know.

If you are not yet familiar with SNAP: SNAP is an application for processing and analysing Earth observation data and can be downloaded from the ESA STEP website.

#1 SNAP - First Steps | EO College

This video, presented by Chris Stewart, gives you a quick step-by-step introduction at the example of Sentinel-1 data. It starts with explaining the application interface components and the menu of SNAP. And further shows how to calibrate S1 data radiometrically and how to apply a terrain correction.

Tutorial: SNAP – First Steps – EO College (eo-college)

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#2 Complete SNAP Tutorials | RS & GIS

This series of videos has tutorials at beginners and advanced level. It starts with an introduction into the user interface and guides you through several applications like, mosaicking, SAR preprocessing, DEM generation and more.

Tutorial: Complete SNAP Tutorials (RS & GIS)

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#3 Getting Started with SNAP Toolbox in Python | Aditya Sharma

In this tutorial, by Aditya Sharma, you learn how to install and configure snappy (now esa-snappy) and how to use it in a first example script. With SNAP 10 snappy has been updated and while the general procedure is still the same you should also acknowledge what the SNAP developers wrote in the wiki.

Tutorial: Getting Started with SNAP Toolbox in Python (Aditya Sharma)

Wiki: Configure Python to use the new SNAP-Python (esa_snappy) interface (SNAP version 10+)

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#4 Synergetic use of radar and optical data | SkyWatch

This lesson provided by the developers, prepared by Andreas Braun, uses landcover analysis as an example and illustrates a method for combining Sentinel-1 radar images and Sentinel-2 multispectral imagery to showcase their synergetic usage and complimentary information.

Tutorial: ESA Synergetic use of S1 and S2 data (SkyWatch)

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#5 SNAP Command Line Tutorial | SkyWatch

SNAP not only provides a graphical user interface but can also be used from the command line. Luis Veci, one of the developers of SNAP, explains in this tutorial how the command line can be used for data processing. The command line tool gpt and the creation complex of processing graphs are explained.

Tutorial: SNAP Command Line Tutorial (SkyWatch)

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#6 Bulk Processing with GPT | Brockmann Consult

This tutorial, by Marco Peters (yes me 🙂), gives an introduction on bulk processing with the command line on Windows and Unix systems. The provided scripts try to stay very generic to serve multiple processing requirements.

Tutorial: Bulk Processing with GPT (Brockmann Consult)

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#7 Flood mapping using the Sentinel-1 imagery and the ESA SNAP S1 Toolbox | Luigi Selmi

At the example of a flood in Germany in 2021 Luigi Selmi shows how a flood event can be mapped. Sentinel-1 data is used. The lesson not only provides information on the workflow but also on how SAR data can be interpreted and the structure of a Sentinel-1 product.

Tutorial: Flood mapping using the Sentinel-1 imagery and the ESA SNAP S1 Toolbox (Luigi Selmi)

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#8 ESA SNAP Tutorials | GEO 2004

This collection of tutorials provides twenty-six lessons for various Earth observation applications. Starting from automatic cloud masking, extraction of built-up areas, ship detection, DEM correction and many more.

Tutorial: ESA SNAP Tutorials (GEO 2004)

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#9 Change Detection Using Optical Data in SNAP | ESA

This tutorial, by Fabricio Ramoino, from an ESA training course shows you how Sentinel-2 data can be used for change detection. Both, water and forest change detection are covered.

Tutorial: Change Detection Using Optical Data in SNAP (ESA)

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#10 Rayleigh Correction Tutorial | Brockmann Consult

This tutorial, by Ana B. Ruescas and Dagmar Müller, does not only show you how to do a Rayleigh correction at the example of Sentinel-2, but also gives you scientific background information. The correction is not only applicable to Sentinel-2 MSI data, but also to Sentinel-3 OLCI and Envisat MERIS data.

Tutorial: Rayleigh Correction Tutorial (Brockmann Consult)

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#11 EO Data Processing with SNAP and Excel! | EOMasters

If you are not so much into the usage of the command line, this tutorial by Marco Peters (yes me 🙂), shows you how Excel can help you to simplify bulk processing of EO data. In the example a time lapse of lake Garda is created using the C2RCC processor.

Tutorial: EO Data Processing with SNAP and Excel! (EOMasters)

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#12 Introductory Remote Sensing | GEARS

In this series of videos Shaun Levick explores Sentinel-2 data, calculates NDVI and classifies data using different classification methodologies, like unsupervised, supervised and supervised Random Forest.

Tutorial: Introductory R emote Sensing (GEARS)

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#13 Sentinel-1 displacements map in SNAP | MrGIS

Przemysław Slesiński shows in this video tutorial the workflow for obtaining a simple displacement map with ESA SNAP and Copernicus Sentinel-1 SAR data.

Tutorial: Sentinel-1 displacements map in SNAP (MrGIS)

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#14 ESA Echoes in Space - SNAP Tutorials | EO-College

This series of videos focuses on the work with SAR data. The tutorials presented by various experts cover mapping of floods, volcanic eruptions, forest, oil spill and crop type mapping.

Tutorial: ESA Echoes in Space - SNAP Tutorials (EO-College)

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#15 SNAP-Python Repository | Techforspace

Antonio Vecoli provides here a repository of Python examples for esa-snappy. They can be used as starting point for your own developments.

Tutorial: SNAP-Python Repository (Techforspace)

That's it. Tschüs and Goodbye.

Marco