Multispectral Earth Observation Applications using ESA SNAP

Multispectral Earth Observation Applications using ESA Sentinel Application Platform

Learn how to process Sentinel-2 images and build Earth Observation Applications

Learn Multispectral Earth Observation Applications

using ESA's SNAP software and Sentinel-2 imagery

Become an expert on Sentinel-2 image processing!

During this course you will learn how to process ESA's COPERNICUS Sentinel-2 data using SNAP software.

The objective of the course is to make the student capable of creating optical-based Earth Observation Applications. 

To be more precise: 

  1. Vegetation Mapping
  2. Burn Area Mapping
  3. Chlorophyll Mapping
  4. Supervised Land Cover Classification

are the main applications examined.

The Graph Builder module is used extensively during the course in order to create workflows.

Example XML workflow files are provided within the course to better help students practice at their own computers!

Example Sentinel-2 images are also included in the course, so you can test the contents of course presented directly to your computer!

By the end of the course can claim your blockchain based digital certificate to better prove your skills! Best part? It come with price of the course, no hidden costs. Just enroll to the course, successfully finish all lessons in the course, and claim you certificate.

Learn to create multispectral applications with SNAP and capture the opportunities

You won’t regret it!

According to the "Study to examine the socio-economic impact of Copernicus in the EU", more than 10.000 related jobs will be needed!

Become an expert on SNAP now and tap to the fast growing Earth Observation Downstream market!


Access Multispectral Sentinel-2 imagery


  • Lesson 1: Getting the Sentinel-2 images to learn multispectral Earth Observation Applications FREE TRIAL
  • Lesson 2: Dataset preparation
  • Lesson 3: Sentinel-2 Dataset used during the course

Atmospheric Corrections


  • Lesson 4: Atmospherically correct Sentinel-2 using Sen2Cor
  • Lesson 5: Comparing non-atmospherically corrected (L1C) with atmospherically corrected (L2A) Sentinel-2 images
  • Lesson 6: Resampling Sentinel-2 atmospherically corrected images

Vegetation and Burn Area Mapping


  • Lesson 7: Sampling Spectral Signatures
  • Lesson 8: Leaf Area Index (LAI) calculation FREE TRIAL
  • Lesson 9: Leaf Area Index (LAI) Evolution time
  • Lesson 10: Improved Masking before Mapping
  • Lesson 11: Normalized Burn Ration Index
  • Lesson 12: Burn Area Mapping Workflow
  • Lesson 13: Burn Area Mapping workflow XML file to use

Chlorophyll Mapping


  • Lesson 14: Chlorophyll Mapping



  • Lesson 15: Supervised Classification Part 1
  • Lesson 16: Supervised Classification Part 2
  • Lesson 17: Supervised Classification Part 3

Testing your skills


  • Lesson 18: Introduction to the purpose of the current chapter
  • Lesson 19: Getting the data for the skill test
  • Lesson 20: Preparing the datasets
  • Lesson 21: Open the Sentinel-2 multispectral image
  • Lesson 22: Crop the reference classification dataset
  • Lesson 23: Open both Sentinel-2 and reference classification map in SNAP
  • Lesson 24: Remember the resampling operator before collocating the data
  • Lesson 25: Collocate or stack multispectral image with reference map in a single file
  • Lesson 26: Resample and subset step using the Graph Builder

What will you learn?

Sentinel-2 preprocessing to start building any Earth Observation application

Atmospherically correct Sentinel-2 images

Vegetation mapping with Sentinel-2

Burn area mapping using bi-temporal Sentinel-2 images

Chlorophyll mapping with Sentinel-2 coastal images

Supervised (Land cover) classification of Sentinel-2 images

Any prerequisites?

Basic knowledge of Earth Observation

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

Be familiar with ESA Sentinels Application Platform (SNAP) software

Student Profile?

Under/post graduate students

Master students and PhD candidates


Researchers and Academics


$19.90 Regular Price Buy $19.90

About Your Instructor

Dimitris Sykas

Dimitris Sykas

Remote Sensing Expert

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.

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