Cloud based spatio-temporal analysis of change in sequences of Sentinel images

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Abstract

An important task in remote sensing Earth observation involves the detection of changes which may signal for example environmentally significant events. The Sentinel-1 synthetic aperture radar (SAR) and the Sentinel-2 as well as the Landsat optical/visible-infrared spaceborne platforms, with spatial resolutions of the order of 10-20-30 meters and revisit times of the order of days, provide an attractive source of data for change detection tasks. Specifically, the SAR imagery provide complete independence from solar illumination and cloud cover. A convenient source of such data is the Google Earth Engine which gives near real time data access and which has an application programming interface for the access and for processing the data. Here we make available open-source automatic change detection software and for optical data also automatic radiometric normalization software for both cloud and local processing.
Original languageEnglish
Title of host publicationProceedings of 2019 Big Data from Space
Publication date2019
Pages105-108
Publication statusPublished - 2019
EventConference on Big Data from Space - Alte Kongresshalle, Munich, Germany
Duration: 19 Feb 201921 Feb 2019

Conference

ConferenceConference on Big Data from Space
LocationAlte Kongresshalle
CountryGermany
CityMunich
Period19/02/201921/02/2019

Cite this

@inproceedings{e11745a3d8ad48919d5f6c926b5532a5,
title = "Cloud based spatio-temporal analysis of change in sequences of Sentinel images",
abstract = "An important task in remote sensing Earth observation involves the detection of changes which may signal for example environmentally significant events. The Sentinel-1 synthetic aperture radar (SAR) and the Sentinel-2 as well as the Landsat optical/visible-infrared spaceborne platforms, with spatial resolutions of the order of 10-20-30 meters and revisit times of the order of days, provide an attractive source of data for change detection tasks. Specifically, the SAR imagery provide complete independence from solar illumination and cloud cover. A convenient source of such data is the Google Earth Engine which gives near real time data access and which has an application programming interface for the access and for processing the data. Here we make available open-source automatic change detection software and for optical data also automatic radiometric normalization software for both cloud and local processing.",
author = "Nielsen, {Allan Aasbjerg} and Canty, {Morton J.} and Henning Skriver and Knut Conradsen",
year = "2019",
language = "English",
pages = "105--108",
booktitle = "Proceedings of 2019 Big Data from Space",

}

Nielsen, AA, Canty, MJ, Skriver, H & Conradsen, K 2019, Cloud based spatio-temporal analysis of change in sequences of Sentinel images. in Proceedings of 2019 Big Data from Space . pp. 105-108, Conference on Big Data from Space, Munich, Germany, 19/02/2019.

Cloud based spatio-temporal analysis of change in sequences of Sentinel images. / Nielsen, Allan Aasbjerg; Canty, Morton J.; Skriver, Henning; Conradsen, Knut.

Proceedings of 2019 Big Data from Space . 2019. p. 105-108.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

TY - GEN

T1 - Cloud based spatio-temporal analysis of change in sequences of Sentinel images

AU - Nielsen, Allan Aasbjerg

AU - Canty, Morton J.

AU - Skriver, Henning

AU - Conradsen, Knut

PY - 2019

Y1 - 2019

N2 - An important task in remote sensing Earth observation involves the detection of changes which may signal for example environmentally significant events. The Sentinel-1 synthetic aperture radar (SAR) and the Sentinel-2 as well as the Landsat optical/visible-infrared spaceborne platforms, with spatial resolutions of the order of 10-20-30 meters and revisit times of the order of days, provide an attractive source of data for change detection tasks. Specifically, the SAR imagery provide complete independence from solar illumination and cloud cover. A convenient source of such data is the Google Earth Engine which gives near real time data access and which has an application programming interface for the access and for processing the data. Here we make available open-source automatic change detection software and for optical data also automatic radiometric normalization software for both cloud and local processing.

AB - An important task in remote sensing Earth observation involves the detection of changes which may signal for example environmentally significant events. The Sentinel-1 synthetic aperture radar (SAR) and the Sentinel-2 as well as the Landsat optical/visible-infrared spaceborne platforms, with spatial resolutions of the order of 10-20-30 meters and revisit times of the order of days, provide an attractive source of data for change detection tasks. Specifically, the SAR imagery provide complete independence from solar illumination and cloud cover. A convenient source of such data is the Google Earth Engine which gives near real time data access and which has an application programming interface for the access and for processing the data. Here we make available open-source automatic change detection software and for optical data also automatic radiometric normalization software for both cloud and local processing.

M3 - Article in proceedings

SP - 105

EP - 108

BT - Proceedings of 2019 Big Data from Space

ER -

Nielsen AA, Canty MJ, Skriver H, Conradsen K. Cloud based spatio-temporal analysis of change in sequences of Sentinel images. In Proceedings of 2019 Big Data from Space . 2019. p. 105-108