Multispectral Earth Observation Applications using ESA Sentinel Application Platform
Learn how to process Sentinel-2 images and build Earth Observation Applications
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:
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.
This remote sensing online course is what you need to learn how to process Sentinel 2 satellite images!
€30,00
Regular price
Lesson 1: Getting the Sentinel-2 images to learn multispectral Earth Observation Applications
FREE PREVIEWLesson 2: Dataset preparation
Lesson 3: Sentinel-2 Dataset used during the course
Quiz 1
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
Quiz 2
Lesson 7: Sampling Spectral Signatures
Lesson 8: Leaf Area Index (LAI) calculation
FREE PREVIEWLesson 9: Leaf Area Index (LAI) Evolution time
Lesson 10: Improved Masking before Mapping
Lesson 11: Normalized Burn Ratio Index
Lesson 12: Burn Area Mapping Workflow
Lesson 13: Burn Area Mapping workflow XML file to use
Quiz 3
Lesson 14: Chlorophyll Mapping
Lesson 15: Supervised Classification Part 1
Lesson 16: Supervised Classification Part 2
Lesson 17: Supervised Classification Part 3
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
Sentinel-2 preprocessing to start building any Earth Observation application
Vegetation mapping with Sentinel-2
Chlorophyll mapping with Sentinel-2 coastal images
Atmospherically correct Sentinel-2 images
Burn area mapping using bi-temporal Sentinel-2 images
Supervised (Land cover) classification of Sentinel-2 images
Basic knowledge of Earth Observation
Be familiar with ESA Sentinels Application Platform (SNAP) software
A simple laptop or desktop computer to follow the course's steps
Under/post graduate students
Professionals and Companies
Master students and PhD candidates
Researchers and Academics
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