Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image

Enes Oguzhan Alatas; Gilsen Taskin

doi:10.1109/IGARSS.2019.8899308

Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image

Enes Oguzhan Alatas, Gilsen Taskin

Disaster Management Institute

Istanbul Technical University

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

4 Citations (Scopus)

Abstract

For an accurate earthquake damage assessment from very high resolution (VHR) images, contextual relations between pixels need to be included in conjunction with spectral information during the classification. To utilize the spatial information in an efficient way, specific patterns representing the earthquake-induced damage should properly be modelled. Attribute Profiles (APs) and Multi Attribute Profiles (MAPs) provide a multi-dimensional representation of an image with a successive implementation of different attribute filters, and they are able to generate the complicated features for a specific pattern. In this study, the APs and the MAPs were used for the first time to extract the additional contextual features from very high resolution satellite image of City of Bam (Iran) acquired eight days after the earthquake. The performance of the morphological attribute features was compared to the those of Haralick's features (HFs) using the k-nn classifier, and the preliminary results showed that the APs and MAPs detect the earthquake damage more accurate than the HFs.

Original language	English
Title of host publication	2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	9299-9302
Number of pages	4
ISBN (Electronic)	9781538691540
DOIs	https://doi.org/10.1109/IGARSS.2019.8899308
Publication status	Published - Jul 2019
Event	39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan Duration: 28 Jul 2019 → 2 Aug 2019

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Country/Territory	Japan
City	Yokohama
Period	28/07/19 → 2/08/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

attribute filtering
Earthquake damage assessment classifi-cation
mathematical morphology
very high resolution image

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IGARSS.2019.8899308

Cite this

Alatas, E. O., & Taskin, G. (2019). Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image. In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings (pp. 9299-9302). Article 8899308 (International Geoscience and Remote Sensing Symposium (IGARSS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2019.8899308

Alatas, Enes Oguzhan ; Taskin, Gilsen. / Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image. 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 9299-9302 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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abstract = "For an accurate earthquake damage assessment from very high resolution (VHR) images, contextual relations between pixels need to be included in conjunction with spectral information during the classification. To utilize the spatial information in an efficient way, specific patterns representing the earthquake-induced damage should properly be modelled. Attribute Profiles (APs) and Multi Attribute Profiles (MAPs) provide a multi-dimensional representation of an image with a successive implementation of different attribute filters, and they are able to generate the complicated features for a specific pattern. In this study, the APs and the MAPs were used for the first time to extract the additional contextual features from very high resolution satellite image of City of Bam (Iran) acquired eight days after the earthquake. The performance of the morphological attribute features was compared to the those of Haralick's features (HFs) using the k-nn classifier, and the preliminary results showed that the APs and MAPs detect the earthquake damage more accurate than the HFs.",

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doi = "10.1109/IGARSS.2019.8899308",

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Alatas, EO & Taskin, G 2019, Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image. in 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings., 8899308, International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc., pp. 9299-9302, 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019, Yokohama, Japan, 28/07/19. https://doi.org/10.1109/IGARSS.2019.8899308

Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image. / Alatas, Enes Oguzhan; Taskin, Gilsen.
2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 9299-9302 8899308 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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

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AB - For an accurate earthquake damage assessment from very high resolution (VHR) images, contextual relations between pixels need to be included in conjunction with spectral information during the classification. To utilize the spatial information in an efficient way, specific patterns representing the earthquake-induced damage should properly be modelled. Attribute Profiles (APs) and Multi Attribute Profiles (MAPs) provide a multi-dimensional representation of an image with a successive implementation of different attribute filters, and they are able to generate the complicated features for a specific pattern. In this study, the APs and the MAPs were used for the first time to extract the additional contextual features from very high resolution satellite image of City of Bam (Iran) acquired eight days after the earthquake. The performance of the morphological attribute features was compared to the those of Haralick's features (HFs) using the k-nn classifier, and the preliminary results showed that the APs and MAPs detect the earthquake damage more accurate than the HFs.

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Alatas EO, Taskin G. Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image. In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 9299-9302. 8899308. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2019.8899308

Attribute Profiles in Earthquake Damage Identification from Very High Resolution Post Event Image

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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