{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:39:38Z","timestamp":1760243978783,"version":"build-2065373602"},"reference-count":13,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2009,3,3]],"date-time":"2009-03-03T00:00:00Z","timestamp":1236038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A devastating earthquake with a magnitude of Mw 7.4 occurred on the North Anatolian Fault Zone (NAFZ) of Turkey on August 17, 1999 at 00:01:39 UTC (3:01 a.m. local time). The aim of this study is to propose a new approach to automatically identify earthquake induced damage areas which can provide valuable information to support emergency response and recovery assessment procedures. This research was conducted in the Adapazari inner city, covering a 3 \u00d7 3 km area, where 11,373 buildings collapsed as a result of the earthquake. SPOT high resolution visible infrared (HRVIR) Pan images obtained before (25 June 1999) and after (4 October 1999) the earthquake were used in the study. Five steps were employed to conduct the research and these are: (i) geometric and radiometric correction of satellite images, (ii) Fast Fourier Transform (FFT) of pre- and post-earthquake images and filtering the images in frequency domain, (iii) generating difference image using Inverse Fast Fourier Transform (IFFT) pre- and post- earthquake images, (iv) application of level slicing to difference image to identify the earthquake-induced damages, (v) accuracy assessment of the method using ground truth obtained from a 1\/5,000 scale damage map. The total accuracy obtained in the research is 80.19 %, illustrating that the proposed method can be successfully used to automatically identify earthquake-induced damage areas.<\/jats:p>","DOI":"10.3390\/s90301471","type":"journal-article","created":{"date-parts":[[2009,3,3]],"date-time":"2009-03-03T13:13:11Z","timestamp":1236085991000},"page":"1471-1484","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Identification of Earthquake Induced Damage Areas Using Fourier Transform and SPOT HRVIR Pan Images"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4854-494X","authenticated-orcid":false,"given":"Elif","family":"Sertel","sequence":"first","affiliation":[{"name":"Istanbul Technical University, Faculty of Civil Engineering, Department of Geodesy and Photogrammetry, Maslak, 34469, Istanbul, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2009,3,3]]},"reference":[{"key":"ref_1","first-page":"405","article-title":"The Earthquake Catalogues for Turkey","volume":"17","author":"Tan","year":"2008","journal-title":"Turkish. 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Remote Sens"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1109\/TGRS.2007.894019","article-title":"Use of semi-variograms to identify earthquake damage in an urban area","volume":"45","author":"Sertel","year":"2007","journal-title":"IEEE Trans. Geosci. Remot. Sen"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4433","DOI":"10.1080\/01431160600675895","article-title":"Satellite radar and optical remote sensing for earthquake damage detection: results from different case studies","volume":"27","author":"Stramondo","year":"2006","journal-title":"Int. J. Remote Sens"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.1080\/0143116031000070427","article-title":"SPOT HRV data analysis for detecting earthquake-induced changes in Izmit, Turkey","volume":"24","author":"Turker","year":"2003","journal-title":"Int. J. Remote Sens"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1080\/01431160412331330239","article-title":"Fusion of multispectral and panchromatic satellite sensor imagery based on tailored filtering in the Fourier domain","volume":"26","author":"Gonzalo","year":"2005","journal-title":"Int. J. Remote Sens"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1595","DOI":"10.1080\/01431160600887698","article-title":"Monitoring Sahelian floodplains using Fourier analysis of MODIS time-series data and artificial neural networks","volume":"28","author":"Westra","year":"2007","journal-title":"Int. J. Remote Sens"},{"key":"ref_10","unstructured":"USGS U.S. Geological Survey Earthquake Hazards Program 2008, available at http:\/\/earthquake.usgs.gov. (accessed 10 October 2008)."},{"key":"ref_11","unstructured":"TSI. Turkish Statistical Institute available at www.tuik.gov.tr. (accessed 10 October 2008)."},{"key":"ref_12","unstructured":"Erdas Field Guide, Geospatial Imaging, LLC Norcross, Georgia, 2005."},{"key":"ref_13","unstructured":"Gonzalez, R.C., and Wintz, P. (1977). Digital Image Processing, Addison-Wesley Publishing Company."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/9\/3\/1471\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T22:09:57Z","timestamp":1760220597000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/9\/3\/1471"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,3,3]]},"references-count":13,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2009,3]]}},"alternative-id":["s90301471"],"URL":"https:\/\/doi.org\/10.3390\/s90301471","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2009,3,3]]}}}