Remote Sensing with Google Earth Engine Cloud Computing
What you'll learn
- Learn the basics of remote sensing principles
- Scale your analysis to large regions and over long periods of time
- Get familiarized with various satellite sensors and remotely sensed products
- Master the digital image processing methods
- Carry out time-series analysis and change detection with earth observation data
- Use machine learning techniques with remote sensing datasets
- Build interactive apps for data exploration
- This course has no requirements.
Google Earth Engine is a cloud-based platform that enables large-scale processing of satellite imagery to detect land surface changes, identify temporal trends, and quantify environmental changes such as urbanization, climate change, land cover change, flooding, drought monitoring, and many more. This course covers a comprehensive list of topics ranging from the basics of Google Earth Engine to intermediate digital image processing to advanced remote sensing applications on Google’s cloud infrastructure. By the end of this course, you will be able to master the Earth Engine cloud computing platform and understand remote sensing techniques to implement in your remote sensing projects.
You will have access to real-world data, scripts, and hands-on exercises to help manage and process large-scale remote sensing data on the cloud. By taking this course, you will take your spatial data science skills to the next level by gaining proficiency in Earth Engine powered by Google.
If you want to improve your spatial data science skills and be ready for your next geospatial tech job, take action now by taking this course.
Let's get started!
Who this course is for:
- Anyone interested in learning how to process and analyze Earth observation data with Google earth Engine
I am a geospatial data scientist with 15-plus years of experience. I am a former NASA Earth and Space Science fellow. My research interests include remote sensing, big data, and environmental change. More specifically, I am interested in applying big geospatial data, cloud computing, and machine learning to solve complex environmental problems, especially land cover change, climate change, water resources, agriculture, and public health.
Spatial eLearning provides online courses teaching remote sensing, GIS, machine learning, cloud computing, and spatial data science skills. Our mission is to make highly valuable geospatial data science skills accessible and affordable to anyone and anywhere around the world. We teach 20,000 plus students in over 170 countries around the world. Spatial eLearning’s valuable learning resources include webinars, books, free tutorials, and online courses.