Satellite Data with SNAP
Satellite data gives us a unique view of the Earth and is increasingly used for applications such as agricultural monitoring, nature conservation, and urban development. Thanks to freely available satellite imagery—such as that from Sentinel-2—this technology is now more accessible than ever to anyone working with geoinformation or geodata.
To truly make the most of these images, you need the right tools. SNAP software (Sentinel Application Platform), developed by ESA, is a powerful free tool that allows you to analyze and process satellite data. Think of viewing multicolor image composites (RGB) to identify objects on the Earth’s surface, or correcting atmospheric distortions using the Sen2Cor algorithm.
With SNAP, you can also calculate spectral indices, such as NDVI and NDWI, to analyze vegetation or water surfaces. Even more advanced techniques like Random Forest classification or Principal Component Analysis (PCA)—which help make sense of large amounts of data—are part of the capabilities.
In short: SNAP opens the door to a world of insights from satellite imagery, whether you’re working on spatial issues, environmental analysis, or mapping land cover in areas such as Lake Tisza in Hungary.
What will you learn in this Blended Learning course?
In this blended learning course, you’ll discover how to use satellite data to gain valuable spatial insights. You’ll work with real data from the Sentinel-2 satellites, process it in the SNAP software, and learn how to map land cover around the Tisza-Tó area in Hungary in 2016.
You’ll start by downloading multispectral images and learn how to open and visualize them in SNAP. Using RGB color composites, you’ll identify landscape features and objects. Next, you’ll apply the Sen2Cor algorithm to atmospherically correct the images and prepare them for analysis.
After that, you’ll dive into the use of spectral indices such as NDVI (for vegetation) and NDWI (for water surfaces), which help you make landscape features more clearly visible. You’ll also learn to apply various classification methods, such as K-means and Random Forest, to group and analyze areas. Finally, you’ll use Principal Component Analysis (PCA) to distill large amounts of data down to its core.
The course is highly practical and aligns with current applications of geodata in the field. Whether you’re just starting out with remote sensing or want to deepen your knowledge, you’ll develop skills that allow you to work independently with satellite imagery.
Why choose this Satellite Data with SNAP course?
Blended learning combines independent online learning with practical, interactive sessions, allowing you to gain both theoretical knowledge and practical experience with SNAP and satellite data analysis. The online modules give you the freedom to learn at your own pace. They include clear instructions on processing Sentinel-2 data, applying image corrections, and performing classifications within SNAP software. You’ll discover how to download satellite images, interpret them visually, and use them to analyze land cover and changes in the landscape.
During the hands-on online sessions, you’ll immediately apply the knowledge you’ve gained. You’ll work with real satellite data from the Tisza-Tó region in Hungary and receive guidance from experienced geoinformation specialists. You will learn how to process multispectral data, apply spectral indices such as NDVI and NDWI, and use various analysis techniques to gain clear insights. By getting started right away with current datasets, you will develop practical skills that you can apply in a wide range of spatial projects.
The combination of flexible online learning and hands-on training ensures that you not only learn how to work with SNAP and satellite data, but also how to effectively apply them to realistic geoinformation projects. After completing this course, you will be able to independently process, analyze, and apply satellite imagery to support informed decision-making in your field.