Skip to main content

Advanced Search

Projected result for your current search: 0

Search Operators:

You can use operators in your search query to narrow down your results even more. Click on the search operator to see an explanation of how it works.
Finds documents with exactly this word group, in exactly this word order and spelling (e.g. "employer branding").
Finds documents with both search terms (e.g. sales AND bonus).
Finds documents with one or the other search term (e.g. porsche OR volkswagen).
Finds documents with all search terms. Blank space is understood as AND (e.g. man robot production).
Finds documents with no appearance of the word behind NOT (e.g. ford NOT "harrison ford").
Finds documents where the search term is mentioned at least "n" times."n" may be any number (e.g. COUNT(gear)>8).
Finds documents with both search terms in any word order, permitting "n" words as a maximum distance between them. Best choose between 15 and 30 (e.g. NEAR(recruit, professionals, 20)).
Finds documents with the search term in word versions or composites. The asterisk * marks whether you wish them BEFORE, BEHIND, or BEFORE and BEHIND the search term (e.g. lightweight*, *lightweight, *lightweight*).
Finds documents with the search term in different spellings. "?" allows only one character (e.g. organi?ation).
Special characters are understood as AND (e.g. Miller Bros. & Sons).

Semantic Search

powered by (Link opens in a new window)
loading …
Log in
Top

Unsupervised Learning of Robust Representations for Change Detection on Sentinel-2 Earth Observation Images

  • 2020
  • OriginalPaper
  • Chapter
Published in:
Authors
Michelle Aubrun
Andres Troya-Galvis
Mohanad Albughdadi
Romain Hugues
Marc Spigai
Published in
Environmental Software Systems. Data Science in Action
Publisher
Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The recent popularity of artificial intelligence techniques and the wealth of free and open access Copernicus data have led to the development of new data analytics applications in the Earth Observation domain. Among them, is the detection of changes on image time series, and in particular, the estimation of levels and superficies of changes. In this paper, we propose an unsupervised framework to detect generic but relevant and reliable changes using pairs of Sentinel-2 images. To illustrate this method, we will present a scenario focusing on the detection of changes in vineyards due to natural hazards such as frost and hail.

Already a customer? Then log in here to gain access.

Customer login

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Business + Economics & Engineering + Technology"

Online-Abonnement

Springer Professional "Business + Economics & Engineering + Technology" gives you access to:

  • more than 130.000 books
  • more than 540 journals

from the following subject areas:

  • Automotive
  • Construction + Real Estate
  • Business IT + Informatics
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Mechanical Engineering + Materials
  • Surfaces + Materials Technology
  • Insurance + Risk


Secure your knowledge advantage now!

inform now

Springer Professional "Engineering + Technology"

Online-Abonnement

Springer Professional "Engineering + Technology" gives you access to:

  • more than 75.000 books
  • more than 390 journals

from the following specialised fileds:

  • Automotive
  • Business IT + Informatics
  • Construction + Real Estate
  • Electrical Engineering + Electronics
  • Energy + Sustainability
  • Mechanical Engineering + Materials
  • Surfaces + Materials Technology





 

Secure your knowledge advantage now!

inform now

Springer Professional "Business + Economics"

Online-Abonnement

Springer Professional "Business + Economics" gives you access to:

  • more than 100.000 books
  • more than 340 journals

from the following specialised fileds:

  • Construction + Real Estate
  • Business IT + Informatics
  • Finance + Banking
  • Management + Leadership
  • Marketing + Sales
  • Insurance + Risk



Secure your knowledge advantage now!

inform now

For explorers: Get to know our platforms better with a free registration.

Register for free
next chapter Dietary Intake Assessment: From Traditional Paper-Pencil Questionnaires to Technology-Based Tools
Title
Unsupervised Learning of Robust Representations for Change Detection on Sentinel-2 Earth Observation Images
Authors
Michelle Aubrun
Andres Troya-Galvis
Mohanad Albughdadi
Romain Hugues
Marc Spigai
Copyright Year
2020
Book
Environmental Software Systems. Data Science in Action

Print ISBN: 978-3-030-39814-9

Electronic ISBN: 978-3-030-39815-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-39815-6_1
This content is only visible if you are logged in and have the appropriate permissions.

Premium Partner

    Image Credits
    Neuer Inhalt/© ITandMEDIA, Nagarro GmbH/© Nagarro GmbH, AvePoint Deutschland GmbH/© AvePoint Deutschland GmbH, AFB Gemeinnützige GmbH/© AFB Gemeinnützige GmbH, USU GmbH/© USU GmbH, Ferrari electronic AG/© Ferrari electronic AG