Evaluation of spectral similarity indices in unsupervised change detection approaches

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Autore principale: Jeisson Fabián Ramos
Natura: Artículo científico
Lingua:en
Pubblicazione: Universidad Nacional de Colombia 2018
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author Jeisson Fabián Ramos
author_facet Jeisson Fabián Ramos
contents Evaluation of spectral similarity indices in unsupervised change detection approaches Jeisson Fabián Ramos Diego Renza Dora M. Ballesteros L. Ingeniería remote sensing change detection spectral indices accuracy assessment Unsupervised change detection (UCD) is a subject of Remote Sensing whose objective is to detect the differences between two multi-temporal images. In some cases, spectral similarity indices have been used as the comparison block in algorithms of UCD. The aim of this paper is to show in a quantitative way the performance of four spectral similarity indices in the correct identification of changes. Comparison is performed in terms of precision (overall accuracy and kappa index) over medium and high-resolution images (SPOT-5: Satellite Pour l'Observation de la Terre and Quickbird), with a reference obtained through a post-classification method (based on Support Vector Machines, SVM). The results show dependence on the automatic thresholding technique, as well as on the classes associated with the change. 2018 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49655628014 https://www.redalyc.org/journal/496/49655628014/ https://www.redalyc.org/journal/496/49655628014/html/ https://www.redalyc.org/journal/496/49655628014/49655628014.epub https://www.redalyc.org/journal/496/49655628014/movil 10.15446/dyna.v85n204.68355 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.204 Vol.85
format Artículo científico
id redalyc_49655628014
institution Redalyc
language en
publishDate 2018
publisher Universidad Nacional de Colombia
spellingShingle Evaluation of spectral similarity indices in unsupervised change detection approaches
Jeisson Fabián Ramos
Ingeniería
remote sensing
change detection
spectral indices
accuracy assessment
Evaluation of spectral similarity indices in unsupervised change detection approaches Jeisson Fabián Ramos Diego Renza Dora M. Ballesteros L. Ingeniería remote sensing change detection spectral indices accuracy assessment Unsupervised change detection (UCD) is a subject of Remote Sensing whose objective is to detect the differences between two multi-temporal images. In some cases, spectral similarity indices have been used as the comparison block in algorithms of UCD. The aim of this paper is to show in a quantitative way the performance of four spectral similarity indices in the correct identification of changes. Comparison is performed in terms of precision (overall accuracy and kappa index) over medium and high-resolution images (SPOT-5: Satellite Pour l'Observation de la Terre and Quickbird), with a reference obtained through a post-classification method (based on Support Vector Machines, SVM). The results show dependence on the automatic thresholding technique, as well as on the classes associated with the change. 2018 artículo científico 0012-7353 https://www.redalyc.org/articulo.oa?id=49655628014 https://www.redalyc.org/journal/496/49655628014/ https://www.redalyc.org/journal/496/49655628014/html/ https://www.redalyc.org/journal/496/49655628014/49655628014.epub https://www.redalyc.org/journal/496/49655628014/movil 10.15446/dyna.v85n204.68355 en http://www.redalyc.org/revista.oa?id=496 Dyna application/pdf Universidad Nacional de Colombia Dyna (Colombia) Num.204 Vol.85
title Evaluation of spectral similarity indices in unsupervised change detection approaches
topic Ingeniería
remote sensing
change detection
spectral indices
accuracy assessment
url https://www.redalyc.org/articulo.oa?id=49655628014
https://www.redalyc.org/journal/496/49655628014/
https://www.redalyc.org/journal/496/49655628014/html/
https://www.redalyc.org/journal/496/49655628014/49655628014.epub
https://www.redalyc.org/journal/496/49655628014/movil