Non-gaussian clustering of SAR images for glacier change detection

Source at https://earth.esa.int/web/guest/document-library/browse-document-library/-/article/esa-living-planet-symposium-7438 . Our aim is to use unsupervised, non-Gaussian clustering of Arctic glaciers for post-classification change detection. Firstly, we demonstrate the consistency of non-Gaussian...

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Bibliographic Details
Main Authors: Akbari, Vahid, Doulgeris, Anthony Paul, Eltoft, Torbjørn
Format: Article in Journal/Newspaper
Language:English
Published: European Space Agency 2010
Subjects:
VDP::Mathematics and natural science: 400::Geosciences: 450::Quaternary geology
glaciology: 465
VDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Kvartærgeologi
glasiologi: 465
SAR
Clustering
Glacier
Change detection
Arctic
Asar
Online Access:https://hdl.handle.net/10037/15322
Description
Summary:Source at https://earth.esa.int/web/guest/document-library/browse-document-library/-/article/esa-living-planet-symposium-7438 . Our aim is to use unsupervised, non-Gaussian clustering of Arctic glaciers for post-classification change detection. Firstly, we demonstrate the consistency of non-Gaussian clustering algorithms for Envisat ASAR images by characterizing the expected random error level for different SAR acquisition conditions (such as incidence angle). This allows us to determine whether an observed variation is statistically significant and therefore can be used for post-classification change detection of Arctic glaciers. Real significant change was not detected with mixed configurations during the time period of this study.

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