Fundamentals of Remote Sensing with Google Earth Engine
What you'll learn
- At the end of this course, students will be able to master concepts in remote sensing
- Learn the basics of remote sensing principles
- Master the image processing skills: mosaicking, compositing, resampling, reprojection, spectral unmixing, and classification
- Access and download freely available Earth observation satellite data
- Get familiarized with various satellite sensors and remotely sensed products
- Understand the applications of remote sensing
- Process and analyze big Earth observation data using cloud computing
Requirements
- This course has no requirements.
Description
Do you want to learn the fundamentals of remote sensing?
Do you want to learn how to access, process, and analyze remote sensing and GIS data using free open-source tools?
Do you want to solve a real-world problem using freely available satellite data?
Do you want to acquire new hands-on Remote Sensing skills that will prepare you for a remote sensing and GIS job in the geospatial industry?
Enroll in this Fundamentals of Remote Sensing with Google Earth Engine course.
I will provide you with hands-on training with examples of GIS and Remote Sensing data, sample scripts, and real-world applications.
By taking this course, you will take your satellite remote sensing skills to the next level by gaining proficiency in satellite remote sensing and geospatial analysis with GEE, a cloud-based Earth observation, and GIS data visualization analysis powered by Google.
In this Fundamentals of Remote Sensing and Image Analysis course, I will help you get up and running on the Google Earth Engine JavaScript API platform form to process and analyze geospatial data. By the end of this course, you will be equipped with a set of new Remote Sensing skills including accessing, downloading processing, analyzing, and visualizing GIS and Earth Observation big data.
The course covers various topics including introduction to remote sensing, types of resolutions, remote sensing data sources, digital image processing, and image classification.
In this course, I will use real satellite data including Landsat, MODIS, Sentinel-2, and others to provide you with a hands-on practical experience of working with freely available remotely sensed data. I will walk you through using a step by step video tutorials to process and analyze remote sensing data using a cloud platform. In addition to learning the basic concepts, theories, and terminologies, you will also learn the steps for image processing including mosaicking, resampling, reprojections, compositing, spectral unmixing, spectral transformation, and classification using real-world satellite data and example scripts. All sample data and scripts will be provided to you as an added bonus throughout the course.
Jump in right now to enroll. To get started click the enroll button.
Who this course is for:
- Anyone interested in learning how to process and analyze Earth observation data with Google earth Engine
- Anyone interested to learning the basics of satellite remote sensing
Instructor
- 3.9 Instructor Rating
- 2,604 Reviews
- 21,161 Students
- 23 Courses
Dr. Alemayehu Midekisa is a geospatial data scientist with over 15 years of professional experience in academia and industry. His research focus is on leveraging geospatial AI, big Earth observation data, and cloud computing to monitor environmental changes. Dr. Midekisa is particularly interested in applying machine learning models, large-scale remote sensing data, and cloud computing such as Google Earth Engine to quantify land surface changes including land cover changes, urbanization trends, disease outbreaks, and surface water dynamics.