Google Earth Engine provides access to a vast amount of satellite imagery and geospatial datasets. In this course, you’ll learn how to access, analyze, and visualize this data using Python for a wide range of geospatial applications. You’ll work with powerful tools for remote sensing, time-series analysis, and interactive map visualizations. This will help you develop practical skills for efficiently processing large-scale geodata and turning it into valuable insights.
Google Earth Engine provides access to a vast collection of satellite imagery, climate data, and other geospatial datasets. By combining this data with the power of cloud computing, analyses can be performed on a scale that is often not possible with traditional desktop software.
In this blended learning course, you’ll learn how to use Google Earth Engine with Python to collect, analyze, and visualize geospatial data. You’ll work with satellite imagery, time series, and global datasets, and discover how to extract valuable insights from large amounts of Earth observation data.
The course is suitable for GIS professionals, remote sensing specialists, data analysts, and anyone who wants to learn how to work with cloud-based geospatial analysis. Thanks to the hands-on approach, you’ll not only learn the theory but also apply the techniques directly to realistic datasets and applications.
In this blended learning course, you’ll learn the fundamentals of Google Earth Engine with Python. You’ll start by accessing datasets and learn how to retrieve satellite imagery and geospatial data from the Google Earth Engine environment.
Among other things, you’ll learn to work with the Earth Engine API, Geemap, EEMont, and WxEE to perform analyses and visualize results. You’ll then discover how to filter, combine, and process satellite imagery for various applications.
In addition, you’ll get hands-on experience with time-series analysis, classifications, and monitoring changes over time. You’ll learn how to analyze geospatial datasets, develop interactive maps, and automate workflows for remote sensing and Earth observation. You’ll also gain insight into the possibilities of cloud-based geospatial data analysis.
In short: this course is ideal for anyone who wants to analyze satellite imagery and geospatial data on a large scale using Google Earth Engine and Python.
Blended learning combines independent online study with hands-on guidance. You’ll have access to online course materials that allow you to learn at your own pace how to work with Google Earth Engine, satellite imagery, and cloud-based analysis. The theory is supported by practical assignments, so you can immediately practice with realistic datasets.
During the guided sessions, you can ask questions, receive additional explanations, and work on assignments related to applications in remote sensing, environmental research, agriculture, and spatial analysis. You’ll learn how to process datasets, monitor changes, and generate insights from Earth observation data.
Upon completion of this course, you will have a solid foundation in Google Earth Engine with Python. You will be able to independently perform geospatial analyses, process satellite imagery, and develop cloud-based workflows for a wide range of applications.
You’ll receive 1-on-1 guidance. After signing up, our course coordinator will contact you to schedule your first session.
Do you have questions about the course content? Or are you unsure whether the course aligns with your learning goals or preferences? Would you prefer an in-house or private course? We’d be happy to help.
