{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T10:43:41Z","timestamp":1769424221530,"version":"3.49.0"},"reference-count":42,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T00:00:00Z","timestamp":1534118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["DFG BO 2933\/3-1"],"award-info":[{"award-number":["DFG BO 2933\/3-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6\u201312 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth\u2019s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.<\/jats:p>","DOI":"10.3390\/rs10081272","type":"journal-article","created":{"date-parts":[[2018,8,13]],"date-time":"2018-08-13T11:27:13Z","timestamp":1534159633000},"page":"1272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9092-0964","authenticated-orcid":false,"given":"Stephanie","family":"Olen","sequence":"first","affiliation":[{"name":"Institute for Earth and Environmental Science, University of Potsdam, 14469 Potsdam, Germany"}]},{"given":"Bodo","family":"Bookhagen","sequence":"additional","affiliation":[{"name":"Institute for Earth and Environmental Science, University of Potsdam, 14469 Potsdam, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1177\/0309133309339563","article-title":"A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters","volume":"33","author":"Joyce","year":"2009","journal-title":"Prog. Phys. Geogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.isprsjprs.2005.02.002","article-title":"Satellite remote sensing of earthquake, volcano, flood, landslide and coastal inundation hazards","volume":"59","author":"Tralli","year":"2005","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1002\/ppp.619","article-title":"Remote sensing of permafrost-related problems and hazards","volume":"19","year":"2008","journal-title":"Permafr. Periglac. Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1146\/annurev.earth.28.1.169","article-title":"Synthetic aperture radar interferometry to measure Earth\u2019s surface topography and its deformation","volume":"28","author":"Rosen","year":"2000","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/36.739146","article-title":"Coherence estimation for SAR imagery","volume":"37","author":"Touzi","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1785\/0220150152","article-title":"Rapid Damage Mapping for the 2015 M w 7.8 Gorkha Earthquake Using Synthetic Aperture Radar Data from COSMO--SkyMed and ALOS-2 Satellites","volume":"86","author":"Yun","year":"2015","journal-title":"Seismol. Res. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Fielding, E.J., Talebian, M., Rosen, P.A., Nazari, H., Jackson, J.A., Ghorashi, M., and Walker, R. (2005). Surface ruptures and building damage of the 2003 Bam, Iran, earthquake mapped by satellite synthetic aperture radar interferometric correlation. J. Geophys. Res. Solid Earth, 110.","DOI":"10.1029\/2004JB003299"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1080\/01431160600928567","article-title":"Mapping damage during the Bam (Iran) earthquake using interferometric coherence","volume":"28","author":"Hoffmann","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1080\/01431160118187","article-title":"Decorrelation of SAR data by urban damages caused by the 1995 Hyogoken-nanbu earthquake","volume":"22","author":"Yonezawa","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1109\/LGRS.2011.2182030","article-title":"Analysis of Urban Areas Affected by the 2011 Off the Pacific Coast of Tohoku Earthquake and Tsunami With L-Band SAR Full-Polarimetric Mode","volume":"9","author":"Watanabe","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sharma, C.R., Tateishi, R., Hara, K., Nguyen, T.H., Gharechelou, S., and Nguyen, V.L. (2017). Earthquake Damage Visualization (EDV) Technique for the Rapid Detection of Earthquake-Induced Damages Using SAR Data. Sensors, 17.","DOI":"10.3390\/s17020235"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1109\/TGRS.2009.2031062","article-title":"The TerraSAR-X mission and system design","volume":"48","author":"Werninghaus","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.jog.2010.01.001","article-title":"COSMO-SkyMed an existing opportunity for observing the Earth","volume":"49","author":"Covello","year":"2010","journal-title":"J. Geodyn."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Geudtner, D., Torres, R., Snoeij, P., Davidson, M., and Rommen, B. (2014, January 13\u201318). Sentinel-1 system capabilities and applications. Proceedings of the 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6946711"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A tutorial on synthetic aperture radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","unstructured":"(2018, August 13). InSAR Scientific Computing Environment\u2014The Home Stretch, Available online: https:\/\/trs.jpl.nasa.gov\/bitstream\/handle\/2014\/43527\/11-5426_A1b.pdf?sequence=1&isAllowed=y."},{"key":"ref_19","unstructured":"(2018, August 13). InSAR Scientific Computing Environment. Available online: http:\/\/abstractsearch.agu.org\/meetings\/2010\/FM\/IN43B-1397.html."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1002\/2013EO070001","article-title":"New radar interferometric time series analysis toolbox released","volume":"94","author":"Agram","year":"2013","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Farr, T.G., Rosen, P.A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., and Roth, L. (2007). The shuttle radar topography mission. Rev. Geophys., 45.","DOI":"10.1029\/2005RG000183"},{"key":"ref_22","unstructured":"(2018, August 13). Copernicus Open Access Hub. Available online: https:\/\/scihub.copernicus.eu\/."},{"key":"ref_23","unstructured":"United States Geological Survey (USGS) (2017). M 7.3\u201329 km S of Halabjah, Iraq."},{"key":"ref_24","unstructured":"(2017). Gridded Population of the World, Version 4 (GPWv4), Revision, Models the Distribution of Human Population (Counts and Densities) on a Continuous Global Raster Surface."},{"key":"ref_25","unstructured":"(2018, August 13). Google Earth Engine. Available online: https:\/\/code.earthengine.google.com\/."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1175\/BAMS-D-13-00164.1","article-title":"The Global Precipitation Measurement Mission","volume":"95","author":"Hou","year":"2014","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Smith, E.A., Asrar, G., Furuhama, Y., Ginati, A., Mugnai, A., Nakamura, K., Adler, R.F., Chou, M.-D., Desbois, M., and Durning, J.F. (2007). International global precipitation measurement (GPM) program and mission: An overview. Measuring Precipitation from Space, Springer.","DOI":"10.1007\/978-1-4020-5835-6_48"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1130\/B25602.1","article-title":"Processes of oscillatory basin filling and excavation in a tectonically active orogen: Quebrada del Toro Basin, NW Argentina","volume":"117","author":"Hilley","year":"2005","journal-title":"Geol. Soc. Am. Bull."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.epsl.2017.06.001","article-title":"100 kyr fluvial cut-and-fill terrace cycles since the Middle Pleistocene in the southern Central Andes, NW Argentina","volume":"473","author":"Tofelde","year":"2017","journal-title":"Earth Planet. Sci. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Bookhagen, B., and Strecker, M.R. (2008). Orographic barriers, high-resolution TRMM rainfall, and relief variations along the eastern Andes. Geophys. Res. Lett., 35.","DOI":"10.1029\/2007GL032011"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"11679","DOI":"10.1002\/2016GL070868","article-title":"River-discharge dynamics in the Southern Central Andes and the 1976\u201377 global climate shift","volume":"43","author":"Castino","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1007\/s00382-016-3127-2","article-title":"Rainfall variability and trends of the past six decades (1950\u20132014) in the subtropical NW Argentine Andes","volume":"48","author":"Castino","year":"2017","journal-title":"Clim. Dyn."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Purinton, B., and Bookhagen, B. (2018). Measuring Decadal Vertical Land-level Changes from SRTM-C (2000) and TanDEM-X (~2015) in the South-Central Andes. Earth Surf. Dyn.","DOI":"10.5194\/esurf-2018-51"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Milillo, P., Giardina, G., DeJong, J.M., Perissin, D., and Milillo, G. (2018). Multi-Temporal InSAR Structural Damage Assessment: The London Crossrail Case Study. Remote Sens., 10.","DOI":"10.3390\/rs10020287"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1109\/36.551931","article-title":"C-band repeat-pass interferometric SAR observations of the forest","volume":"35","author":"Askne","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/TGRS.1995.8746014","article-title":"Repeat-pass SAR interferometry over forested terrain","volume":"33","author":"Hagberg","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/0022-1694(95)02968-0","article-title":"Radar mapping of surface soil moisture","volume":"184","author":"Ulaby","year":"1996","journal-title":"J. Hydrol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0168-1923(00)00189-1","article-title":"Soil moisture evaluation using multi-temporal synthetic aperture radar (SAR) in semiarid rangeland","volume":"105","author":"Moran","year":"2000","journal-title":"Agric. For. Meteorol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4903","DOI":"10.1038\/s41598-017-05123-4","article-title":"InSAR constraints on soil moisture evolution after the March 2015 extreme precipitation event in Chile","volume":"7","author":"Scott","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"303","DOI":"10.5194\/nhess-9-303-2009","article-title":"Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data","volume":"9","author":"Martinis","year":"2009","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ray, R.L., Fares, A., He, Y., and Temimi, M. (2017). Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations over Texas, US. Water, 9.","DOI":"10.3390\/w9060372"},{"key":"ref_42","first-page":"5621","article-title":"Error characterisation of global active and passive microwave soil moisture data sets","volume":"7","author":"Dorigo","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1272\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:18:26Z","timestamp":1760195906000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,13]]},"references-count":42,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["rs10081272"],"URL":"https:\/\/doi.org\/10.3390\/rs10081272","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,8,13]]}}}