Course Description

Orfeo Toolbox is an open-source software for remote sensing image processing. The project was initiated by the French space agency in 2006 and is under heavy development. The software is released under a free licence; a number of contributors outside CNES are taking part in development and integrating into other projects. Key characteristic of ORFEO Toolbox, beside being open-source, is the fact that is one of the fastest remote sensing software available. It's code is very well optimized and you can process big amount of data very fast. It's short learning curve makes it ideal for starters, while it's API and executables structure makes it ideal to experienced users also. This course is a simple, but to the point quick tutorial on how to use some basic features of ORFEO Toolbox in order to perform hyperspectral image classification, and in general classification of remote sensing images. The aim of this course is provide you with quick steps on how to use the ORFEO Toolbox to perform a classification process.
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Course curriculum

  1. 01
  2. 02

    • Lesson 3: Hyperspectral Data

    • Lesson 4: Exploring Orfeo Toolbox

    • Lesson 5: Manage NoData in Orfeo Toolbox

    • Quiz 1
  3. 03

    • Lesson 6: K-means Classification

    • Lesson 7: Self Organizing Map (SOM) Classification
  4. 04

    • Lesson 8: Prepare Vector Training Data

    • Lesson 9: Train a classifier from multiple images

    • Lesson 10: Apply image classification
  5. 05

    • Lesson 11: Vertex Component Analysis (VCA) Endmember Extraction

    • Lesson 12: Abundance Estimation

    • Quiz 2

Pricing - Lifetime Access

Some more information

  • Certificates of Completion

    After you successfully finish the course, you can claim your Certificate of Completion with NO extra cost! You can add it to your CV, LinkedIn profile etc

  • Available at any time! Study at your best time

    We know hard it is to acquire new skills. All our courses are self paced.

  • Online and always accessible

    Even when you finish the course and you get your certificate, you will still have access to course contents! Every time an Instructor makes an update you will be notified and be able to watch it for FREE

Student Profile?

  • Under/post graduate students

  • Professionals and Companies

  • Master students and PhD candidates

  • Researchers and Academics

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1 Year Access

Any prerequisites?

  • Basic knowledge of Earth Observation

  • A simple laptop or desktop computer to follow the course's steps

What will you learn?

  • You will learn what is remote sensing and more specifically what are remote sensing data

  • Learn about ORFEO Toolbox and explore it

  • Perform K-means and Self Organizing Map (SOM) classification procedures on ORFEO Toolbox with a hyperspectral image

  • Prepare vector data for supervised classification

  • Train a supervised classifier and apply the resulting model on another image

  • Extract endmembers and calculate their abundance fraction values

About your Instructor

I'm a Remote Sensing and a Surveying Engineer. I received my degree from NTUA in 2010, where I also received my Ph.D. in hyperspectral remote sensing in 2016. From graduation in 2010, my career started as a Researcher Associate and Teaching Associate in the Laboratory of Remote Sensing of NTUA. From that time I also worked at several private companies as a Remote Sensing Expert and Geospatial Analyst. From the beginning of 2015 I was positioned as Senior Earth Observation Expert. During these years, I have participated in more than 20 funded European Commission and European Space Agency projects, have over 16 peer reviewed scientific publications in the field of Remote Sensing, and have an international patent in hyperspectral data compression.My main research and professional interests are in the optical remote sensing area, where I specialize in data (images, point measurements) processing and algorithm design and development. Some of the software tools that I operate to accomplish my research and business dreams are SNAP, ENVI, IDL, QGIS, ERDAS Imagine, ArcGIS, and Python. I have been working with these tools since 2008.

Dimitris Sykas

Remote Sensing Expert