• The gEOsphere Learning Hub is an online learning platform focused on geospatial education and training. It provides learners with access to a wide range of GIS-related courses, interactive content, and collaborative tools designed to enhance both foundational and advanced skills in geospatial science and technology.

    With a user-friendly interface and flexible learning environment, the platform supports self-paced learning, instructor-led courses, resource sharing, and community interaction. The gEOsphere Learning Hub serves students, educators, and professionals looking to deepen their understanding of spatial data, analysis, and real-world applications in various sectors.


Site announcements

Welcome to the gEOsphere Learning Hub – Now Live!

by Kostas Vlachos -

Dear learners and educators,

We’re excited to announce the official launch of the gEOsphere Learning Hub – your new digital home for geospatial learning and collaboration!

Our platform is designed to provide a seamless, engaging, and resource-rich environment where you can access course materials, submit assignments, participate in discussions, and grow your skills in the world of geospatial science and technology.

🧭 What’s waiting for you inside?

  • Interactive courses tailored for geospatial learning

  • Resources, assignments, and forums to keep you engaged

  • A growing community of learners and mentors

  • Easy access anytime, anywhere

Whether you're just starting out or looking to deepen your expertise, gEOsphere is here to support your learning journey.

📅 Get Started Today
Log in to explore your courses, check announcements, and begin your learning adventure!

Welcome aboard,
The gEOsphere Team

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Available courses

Course image Sentinel-2 time-series exploration
Sentinel-2
Sentinel-2 time-series exploration
Level of Expertise: Novice

This course provides a comprehensive introduction to the analysis and interpretation of time-series data derived from Sentinel-2 satellite imagery. Emphasizing both theoretical foundations and practical applications, students will explore temporal patterns in multispectral data to monitor land surface dynamics, vegetation phenology, and environmental change. Key topics include preprocessing techniques, cloud masking, time-series feature extraction, and change detection methods. The course integrates hands-on exercises using open-source tools and platforms, equipping participants with the skills to conduct independent remote sensing analyses for research and applied projects.

Kostas Vlachos

Kostas Vlachos

Teacher