Urban area extraction in SAR data

H. Aghababaee; S. Niazmardi; J. Amini

doi:10.5194/isprsarchives-XL-1-W3-1-2013

Urban area extraction in SAR data

H. Aghababaee^*, S. Niazmardi, J. Amini

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

Abstract

In this paper, the performance of different texture measures for detection of urban areas from SAR data is evaluated. The used texture measures are categorized into two groups, the first group include the SAR specific textures and the second one considers the general texture measures. ffmax is selected from the first category and LISA, SRPD, Wavelet measures and fractal dimensions are used as general texture measures. For a better discrimination, all texture measures are calculated and a PCA rotation is applied to them and the first PC is multiplied by the urban inhomogeneity parameter and the obtained image is segmented. The obtained results of this procedure comparing with the K-Means clustering algorithm show the better performance of this algorithm for urban area detection.

Original language	English
Title of host publication	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Place of Publication	Teheran
Publisher	International Society for Photogrammetry and Remote Sensing (ISPRS)
Pages	1-5
Number of pages	5
Volume	40
Edition	1W3
DOIs	https://doi.org/10.5194/isprsarchives-XL-1-W3-1-2013
Publication status	Published - 24 Sept 2013
Externally published	Yes
Event	2nd International Conference on Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2013 - Tehran, Iran, Islamic Republic of Duration: 5 Oct 2013 → 8 Oct 2013 Conference number: 2 http://toc.proceedings.com/20463webtoc.pdf (Table of Content) https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W3/ (ISPRS Archive page)

Publication series

Name	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Publisher	Copernicus
ISSN (Print)	1682-1750

Conference

Conference	2nd International Conference on Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2013
Abbreviated title	SMPR 2013
Country/Territory	Iran, Islamic Republic of
City	Tehran
Period	5/10/13 → 8/10/13
Internet address	http://toc.proceedings.com/20463webtoc.pdf (Table of Content) https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W3/ (ISPRS Archive page)

Keywords

Classification
Feature selection
SAR data
Urban area extraction
ITC-CV

Access to Document

10.5194/isprsarchives-XL-1-W3-1-2013

Cite this

Aghababaee, H., Niazmardi, S., & Amini, J. (2013). Urban area extraction in SAR data. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (1W3 ed., Vol. 40, pp. 1-5). (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). International Society for Photogrammetry and Remote Sensing (ISPRS). https://doi.org/10.5194/isprsarchives-XL-1-W3-1-2013

Aghababaee, H. ; Niazmardi, S. ; Amini, J. / Urban area extraction in SAR data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. 40 1W3. ed. Teheran : International Society for Photogrammetry and Remote Sensing (ISPRS), 2013. pp. 1-5 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).

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title = "Urban area extraction in SAR data",

abstract = "In this paper, the performance of different texture measures for detection of urban areas from SAR data is evaluated. The used texture measures are categorized into two groups, the first group include the SAR specific textures and the second one considers the general texture measures. ffmax is selected from the first category and LISA, SRPD, Wavelet measures and fractal dimensions are used as general texture measures. For a better discrimination, all texture measures are calculated and a PCA rotation is applied to them and the first PC is multiplied by the urban inhomogeneity parameter and the obtained image is segmented. The obtained results of this procedure comparing with the K-Means clustering algorithm show the better performance of this algorithm for urban area detection.",

keywords = "Classification, Feature selection, SAR data, Urban area extraction, ITC-CV",

author = "H. Aghababaee and S. Niazmardi and J. Amini",

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booktitle = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",

edition = "1W3",

note = "2nd International Conference on Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2013, SMPR 2013 ; Conference date: 05-10-2013 Through 08-10-2013",

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Aghababaee, H, Niazmardi, S & Amini, J 2013, Urban area extraction in SAR data. in International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 1W3 edn, vol. 40, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, International Society for Photogrammetry and Remote Sensing (ISPRS), Teheran, pp. 1-5, 2nd International Conference on Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2013, Tehran, Iran, Islamic Republic of, 5/10/13. https://doi.org/10.5194/isprsarchives-XL-1-W3-1-2013

Urban area extraction in SAR data. / Aghababaee, H.; Niazmardi, S.; Amini, J.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. 40 1W3. ed. Teheran: International Society for Photogrammetry and Remote Sensing (ISPRS), 2013. p. 1-5 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Aghababaee, H.

AU - Niazmardi, S.

AU - Amini, J.

N1 - Conference code: 2

PY - 2013/9/24

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N2 - In this paper, the performance of different texture measures for detection of urban areas from SAR data is evaluated. The used texture measures are categorized into two groups, the first group include the SAR specific textures and the second one considers the general texture measures. ffmax is selected from the first category and LISA, SRPD, Wavelet measures and fractal dimensions are used as general texture measures. For a better discrimination, all texture measures are calculated and a PCA rotation is applied to them and the first PC is multiplied by the urban inhomogeneity parameter and the obtained image is segmented. The obtained results of this procedure comparing with the K-Means clustering algorithm show the better performance of this algorithm for urban area detection.

AB - In this paper, the performance of different texture measures for detection of urban areas from SAR data is evaluated. The used texture measures are categorized into two groups, the first group include the SAR specific textures and the second one considers the general texture measures. ffmax is selected from the first category and LISA, SRPD, Wavelet measures and fractal dimensions are used as general texture measures. For a better discrimination, all texture measures are calculated and a PCA rotation is applied to them and the first PC is multiplied by the urban inhomogeneity parameter and the obtained image is segmented. The obtained results of this procedure comparing with the K-Means clustering algorithm show the better performance of this algorithm for urban area detection.

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KW - Feature selection

KW - SAR data

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KW - ITC-CV

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Aghababaee H, Niazmardi S, Amini J. Urban area extraction in SAR data. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 1W3 ed. Vol. 40. Teheran: International Society for Photogrammetry and Remote Sensing (ISPRS). 2013. p. 1-5. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). doi: 10.5194/isprsarchives-XL-1-W3-1-2013

Urban area extraction in SAR data

Abstract

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Keywords

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