Total study time: 24 hours
How do you analyze satellite data using open source tools? In this one-on-one course, you’ll learn how to process and interpret remote sensing imagery using QGIS, ESA SNAP, and GRASS GIS. You’ll explore techniques like image classification, dimensionality reduction, and working with radar data such as ALOS PALSAR. With personal guidance and hands-on online modules, you’ll develop practical skills in geospatial analysis that you can apply right away.
Earth observation gives us a deeper understanding of our changing world. With the help of satellites, we continuously gather data about landscapes, climate patterns, and human activity. This data is the foundation of remote sensing and geospatial analysis—powerful tools used to identify trends, monitor environmental changes, and create meaningful visualizations.
Thanks to open source tools like QGIS, ESA SNAP, GRASS GIS, and R, this type of analysis is now more accessible than ever. You can edit satellite imagery, apply classification methods, and turn complex datasets into clear maps and actionable insights. These methods are widely used in fields such as urban planning, environmental management, and conservation.
What makes Earth observation truly valuable is the combination of timeliness, accuracy, and scale. Whether you’re tracking deforestation, measuring water levels, or studying land use, the right tools—and the skills to use them—can help you turn raw data into smart, evidence-based decisions.
In this course, you’ll learn how to analyze satellite data and turn it into meaningful insights. You’ll work with both optical and radar imagery to track landscape changes, monitor climate patterns, and study urban growth.
To do this, you’ll use powerful open source tools like QGIS, ESA SNAP, GRASS GIS, and R. These tools help you prepare imagery, analyze raster data, and detect spatial patterns. As you progress, you’ll also apply land cover classification methods and use dimensionality reduction to simplify complex datasets.
A key focus of the course is the Semi-Automatic Classification Plugin (SCP) in QGIS. This tool makes it easier to classify remote sensing images. Plus, it offers features for downloading satellite data, preprocessing it, and turning it into clear visual outputs.
In addition, you’ll explore radar datasets like ALOS PALSAR, which provide highly detailed imagery for advanced analysis.
By the end of the course, you’ll know how to use these techniques across real-world applications—from environmental monitoring to spatial planning and geo-information projects.
Blended learning gives you the best of both worlds—live interaction and flexible self-paced study—so you can build real, job-ready skills in geospatial data analysis. In this course, you’ll get hands-on with tools like QGIS, ESA SNAP, and GRASS GIS, and learn how to turn satellite data into clear, actionable insights.
We start with a live session where you’ll jump right into working with real satellite data. With expert guidance, you’ll learn how to download, prepare, and classify imagery using the SCP plugin in QGIS—making sense of complex datasets from day one.
Then, through our self-paced modules, you’ll continue developing your skills at your own rhythm. You’ll cover key topics like remote sensing fundamentals, satellite image processing, and raster analysis in a GIS environment. You’ll work with both optical and radar data—including ALOS PALSAR—and practice using dimensionality reduction to simplify and analyze large datasets.
In a second live session, you’ll apply what you’ve learned in a realistic analysis task. You’ll refine your workflow, solve challenges, and get feedback as you turn raw imagery into professional-grade results.
What sets this course apart is its focus on real-world application. You’ll tackle case-based exercises that reflect the kinds of projects professionals face in environmental science, land use planning, and remote sensing.
By combining expert-led training with flexible, hands-on learning, this course prepares you to go beyond theory. By the end, you’ll be ready to work independently—processing satellite data, generating insights, and supporting data-driven decisions in your field.
After completing this course, you’ll be able to:
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
We aim to make our courses accessible to as many people as possible. If the course fee is a concern, instead of registering directly, you can indicate on the registration form that you’d like to receive a quote tailored to your needs. In many cases, we can offer flexible solutions. For instance, we can adjust the course content for large groups, shorten the course based on existing knowledge, or offer daily rates to suit your requirements.
Yes, you can reach out to the instructor with questions for up to 2 weeks after the course. Since the instructor is likely teaching other courses, we recommend emailing your questions to info@geo-ict.com. We’ll forward your inquiry to the instructor, and you’ll receive a response within 24 hours. After the 2-week period, we recommend using our Personalized Online Support for continued assistance.
Yes, we offer on-site training regularly throughout the Netherlands. Our instructor will bring laptops for the participants, and all you need to do is arrange a suitable room at your location.
Please send your requirements to info@geo-ict.com, and we will provide a customized quote, which will include travel and accommodation costs. Once the quote is confirmed, our course coordinator will reach out to schedule the training days.
After each course, participants receive a link to our evaluation portal where you can share your feedback on what you liked and didn’t like. We strive to provide a great experience for all our participants, but if you have a complaint, please click on ‘Complaints Procedure’ in the portal. This document will guide you through the steps to take. Geo-ICT Training Center, Netherlands, is a member of the Dutch Council for Training and Education (NRTO), ensuring a fair and transparent process.
Courses are typically scheduled according to the Dutch time zone, with sessions running from 9:00 AM to 12:00 PM and 1:00 PM to 4:00 PM. For participants in different time zones, we adjust the course times in consultation with you.