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34 Lessons (3h)
    • 1. Welcome

      2:10
    • 2. Section Intro: Introduction Remote Sensing

      0:21
    • 3. Definition of Remote Sensing

      12:23
    • 4. Passive & Active Sensors

      4:30
    • 5. Remote Sensing Applications

      4:13
    • 6. Section Intro: Explore Earth Engine API

      0:22
    • 7. Explore Earth Engine API

      8:46
    • 8. Introduction to Earth Engine API

      1:46
    • 9. Sign Up with Earth Engine API

      3:32
    • 10. Section Intro: Earth Engine Code Editor

      0:27
    • 11. Basic JavaScript Syntax

      5:27
    • 12. Code Editor

      8:13
    • 13. Image Visualization

      7:15
    • 14. Section Intro: Remote Sensing Data Sources

      0:24
    • 15. Earth Observation Satellites

      13:46
    • 16. Sources of Geospatial Data

      6:56
    • 17. Section Intro: Image Resolution

      0:24
    • 18. Types of Resolutions

      6:06
    • 19. Image Resolution

      15:00
    • 20. Section Intro: Digital Image Processing

      0:24
    • 21. Compositing

      8:23
    • 22. Convolutions

      6:35
    • 23. EdgeDetection

      4:06
    • 24. Mosaicking

      8:01
    • 25. Resampling

      4:16
    • 26. Reprojection

      5:29
    • 27. Section Intro: Spectral Transformation

      0:22
    • 28. NDVI

      7:05
    • 29. EVI

      5:42
    • 30. SpectralUnmixing

      5:32
    • 31. Section Intro: Image Classification

      0:22
    • 32. Object Based Classification

      4:36
    • 33. Unsupervised Classification

      6:05
    • 34. Supervised Classification

      11:04

About This Class

Do you want to learn the fundamentals of remote sensing?

Do you want to learn how to access, process and analyze remote sensing 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 job in the geospatial industry?

Enroll in my new course Satellite Remote Sensing Fundamentals.

I will provide you with hands-on training with example 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 data visualization analysis by powered by Google.

 

What makes me qualified to teach you?

I am Dr. Alemayehu Midekisa, PhD and I am a lecturer and research scientist at the University of California. I have over 10 years of experience in processing and analyzing real big Earth observation data from various sources including Landsat, MODIS, Sentinel-2, SRTM and other remote sensing products.

I am also the recipient of one the prestigious NASA Earth and Space Science Fellowship. 

In this Satellite Remote Sensing Fundamentals course, I will help you get up and running on the Google Earth Engine cloud platform 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 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 a hands-on practical experience of working with freely available remotely sensed data. I will walk you through a step by step video tutorials to process and analyze remote sensing data with using 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 script 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.

 

Best,

Alemayehu