{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T00:57:36Z","timestamp":1780448256031,"version":"3.54.1"},"reference-count":98,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T00:00:00Z","timestamp":1646870400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Since 2014, Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data have become an important source in the field of displacement detection thanks to regular acquisitions and 7.5 years of temporal coverage at global level. Despite the increasing number of publications on the role of S1 in landslide detection, there is still a need for research to further clarify the capabilities of the sensor and the applicable image analysis techniques. Previous studies have successfully exploited high-resolution ALOS-PALSAR image-based intensity and coherence analysis at the 2018 Hokkaido landslides. Nevertheless, they expressed a clear need to analyse the capabilities of other sensors (such as S1). This raises the question: Do we need SAR imagery with higher spatial resolution (such as ALOS-PALSAR) or are freely available S1 imagery also suitable for rapid landslide detection? The S1 images could provide suitable material for a comparative analysis and could answer the aforementioned question. Therefore, 17 ascending and 19 descending S1 images were analysed to test S1 accuracy on landslide detection. Multitemporal analyses of both intensity and coherence were performed along with coherence differences, multitemporal features (MTF) and MTF differences of coherence images. In addition, the spatial analysis of the classification results was also evaluated to highlight the potential of S1 coherence analysis. S1 was found to have limitations at the site, as single coherence differences provided low-quality results. However, the results were significantly improved by calculating the MTF on coherence and almost reached the success rate of the ALOS-PALSAR-based coherence analysis, even though the improvement of the results with intensity was not possible. Half of the false positives were identified in the 30\u201345-m buffer zone of the agreement, underlining that the spatial resolution of the S1 is not appropriate for accurate landslide detection. Only an approximation of the landslide-affected area can be given with considerable overestimation. Due to the inclusion of post-event images, the sensor is not perfectly applicable for rapid detection purposes here.<\/jats:p>","DOI":"10.3390\/rs14061350","type":"journal-article","created":{"date-parts":[[2022,3,10]],"date-time":"2022-03-10T20:19:10Z","timestamp":1646943550000},"page":"1350","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Do We Need a Higher Resolution? Case Study: Sentinel-1-Based Change Detection of the 2018 Hokkaido Landslides, Japan"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0270-4365","authenticated-orcid":false,"given":"Istv\u00e1n P\u00e9ter","family":"Kov\u00e1cs","sequence":"first","affiliation":[{"name":"Department of Cartography and Geoinformatics, University of P\u00e9cs, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia","family":"Tessari","sequence":"additional","affiliation":[{"name":"Sarmap SA, 6987 Caslano, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7702-9109","authenticated-orcid":false,"given":"Fumitaka","family":"Ogushi","sequence":"additional","affiliation":[{"name":"L3 Harris Geospatial, Tokyo 113-0033, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Riccardi","sequence":"additional","affiliation":[{"name":"Sarmap SA, 6987 Caslano, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Levente","family":"Ronczyk","sequence":"additional","affiliation":[{"name":"Department of Cartography and Geoinformatics, University of P\u00e9cs, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5403-6410","authenticated-orcid":false,"given":"D\u00e1niel M\u00e1rton","family":"Kov\u00e1cs","sequence":"additional","affiliation":[{"name":"Doctoral School of Earth Sciences, University of P\u00e9cs, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2542-6775","authenticated-orcid":false,"given":"D\u00e9nes","family":"L\u00f3czy","sequence":"additional","affiliation":[{"name":"Department of Physical and Environmental Geography, University of P\u00e9cs, 7624 P\u00e9cs, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Pasquali","sequence":"additional","affiliation":[{"name":"Sarmap SA, 6987 Caslano, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"673","DOI":"10.5194\/nhess-9-673-2009","article-title":"Evaluation of a preliminary satellite-based landslide hazard algorithm using global landslide inventories","volume":"9","author":"Kirschbaum","year":"2009","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1683","DOI":"10.1007\/s12665-011-0990-3","article-title":"Advances in landslide nowcasting: Evaluation of a global and regional modeling approach","volume":"66","author":"Kirschbaum","year":"2012","journal-title":"Environ. Earth Sci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hungr, O., Fell, R., Couture, R., and Eberhardt, E. (2005). The analysis of global landslide risk through the creation of a database of worldwide landslide fatalities. Landslide Risk Management, CRC Press.","DOI":"10.1201\/9781439833711"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1130\/G33217.1","article-title":"Global patterns of loss of life from landslides","volume":"40","author":"Petley","year":"2012","journal-title":"Geology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1007\/s10346-016-0689-3","article-title":"Fatal landslides in Europe","volume":"13","author":"Haque","year":"2016","journal-title":"Landslides"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2357","DOI":"10.1007\/s10346-018-1037-6","article-title":"Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016","volume":"15","author":"Lin","year":"2018","journal-title":"Landslides"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/s10346-009-0166-3","article-title":"statistical assessment on international landslide literature (1945\u20132008)","volume":"6","author":"Gokceoglu","year":"2009","journal-title":"Landslides"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/S0169-555X(99)00078-1","article-title":"Landslide hazard evaluation: A review of current techniques and their application in a multi-scale study, Central Italy","volume":"31","author":"Guzzetti","year":"1999","journal-title":"Geomorphology"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.geomorph.2005.06.002","article-title":"Probabilistic landslide hazard assessment at the basin scale","volume":"72","author":"Guzzetti","year":"2005","journal-title":"Geomorphology"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.geomorph.2015.10.027","article-title":"Assessment of ground-based monitoring techniques applied to landslide investigations","volume":"253","author":"Uhlemann","year":"2016","journal-title":"Geomorphology"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.enggeo.2008.03.010","article-title":"Spatial data for landslide susceptibility, hazards and vulnerability assessment: An overview","volume":"102","author":"Castellanos","year":"2008","journal-title":"Eng. Geol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s10346-017-0887-7","article-title":"Displacement of a landslide retaining wall and application of an enhanced failure forecasting approach","volume":"15","author":"Macciotta","year":"2018","journal-title":"Landslides"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.geomorph.2009.09.011","article-title":"Landslide monitoring with high resolution tilt measurements at the Dollendorfer Hardt landslide, Germany","volume":"120","author":"Garcia","year":"2010","journal-title":"Geomorphology"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10346-018-1091-0","article-title":"Estimation of earth-slide displacement from GPS-based surface-structure geometry reconstruction","volume":"16","author":"Guerriero","year":"2018","journal-title":"Landslides"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.earscirev.2012.02.001","article-title":"Landslide inventory maps: New tools for an old problem","volume":"112","author":"Guzzetti","year":"2012","journal-title":"Earth-Sci. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1007\/s10346-018-1118-6","article-title":"An efficient method of monitoring slow- moving landslides with long-range terrestrial laser scanning: A case study of the Dashu landslide in the Three Gorges Reservoir Region, China","volume":"16","author":"Huang","year":"2018","journal-title":"Landslides"},{"key":"ref_17","unstructured":"Sassa, K., Guzzetti, F., Yamagishi, H., Abranas, Z., Casagli, N., and McSaveney, M. (2015). Ground-based Interferometry for landslide monitoring. Landslide Dynamics: ISRD-ICL Landslide Interactive Teaching Tools, Volume 1 Fundamentals, Mapping and Monitoring, Springer."},{"key":"ref_18","unstructured":"Savvaidis, P.D. (2003). Existing landslide monitoring systems and techniques. From Stars to Earth and Culture, in Honor of the Memory of Professor Alexandros Tsioumis, The Aristotle University of Thessaloniki."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ma\u010dek, M., Petkov\u0161ek, A., Bojan, M., and Miko\u0161, M. (2014). Landslide Monitoring Techniques Database. World Landslide Forum 3, Bejing, China. Volume: Landslide Science for a Safer Geoenvironment, Vol. 1: The International Programme on Landslides, Springer.","DOI":"10.1007\/978-3-319-04999-1_24"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/S0013-7952(99)00122-2","article-title":"A critical review of landslide monitoring experiences","volume":"55","author":"Angeli","year":"2000","journal-title":"Eng. Geol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Chen, Z., Zhang, J.-M., Ho, K., and Wu, F.-Q. (2008). Choice of surveying methods for landslides monitoring. Landslides and Engineered Slopes, Taylor and Francis Group.","DOI":"10.1201\/9780203885284-170"},{"key":"ref_22","unstructured":"Arbanas, S.M., and Arbanas, Z. (2014, January 25\u201328). Landslide mapping and monitoring: Review of conventional and advanced techniques. Proceedings of the 4th Symposium of Macedonian Association for Geotechnics, Skopje, North Macedonia."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s11069-010-9634-2","article-title":"Use of LIDAR in landslide investigations: A review","volume":"61","author":"Jaboyedoff","year":"2012","journal-title":"Nat. Hazards"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhao, C., and Lu, Z. (2018). Remote Sensing of Landslides\u2014A Review. Remote Sens., 10.","DOI":"10.3390\/rs10020279"},{"key":"ref_25","first-page":"87","article-title":"Monitoring landslides using C-band interferometry. A case study: Dunaszekcs\u0151 Landslide, Southern Transdanubia, Hungary","volume":"51\u201352","author":"Bugya","year":"2018","journal-title":"Studia Geomorphol. Carpatho-Balc."},{"key":"ref_26","first-page":"693","article-title":"How to avoid false interpretations of Sentinel-1A TOPSAR interferometric data in landslide mapping? A case study: Recent landslides in Transdanubia, Hungary","volume":"96","author":"Bugya","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Glade, T., Anderson, M., and Crozier, M.J. (2005). Landslide Hazard and Risk, John Wiley & Sons Ltd.","DOI":"10.1002\/9780470012659"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.3390\/rs5031045","article-title":"Persistent Scatterer Interferometry (PSI) technique for land-slide characterization and monitoring","volume":"5","author":"Tofani","year":"2013","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1007\/s10346-018-1068-z","article-title":"Monitoring strategies for local landslide early warning systems","volume":"16","author":"Pecoraro","year":"2018","journal-title":"Landslides"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1007\/s12303-017-0034-4","article-title":"Landslide prediction, monitoring and early warning: A concise review of state-of-the-art","volume":"21","author":"Chae","year":"2017","journal-title":"Geosci. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1186\/2193-1801-2-523","article-title":"Landslide hazard assessment: Recent trends and techniques","volume":"2","author":"Pardeshi","year":"2013","journal-title":"SpringerPlus"},{"key":"ref_32","first-page":"209","article-title":"Recommendations for the quantitative analysis of landslide risk","volume":"73","author":"Corominas","year":"2014","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.earscirev.2018.03.001","article-title":"A review of statistically-based landslide susceptibility models","volume":"180","author":"Reichenbach","year":"2018","journal-title":"Earth-Sci. Rev."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hein, A. (2004). Processing of SAR Data. Fundamentals, Signal Processing, Interferometry, Springer.","DOI":"10.1007\/978-3-662-09457-0"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1080\/19475705.2016.1171258","article-title":"First insights on the potential of Sentinel-1 for landslides detection","volume":"7","author":"Barra","year":"2016","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.earscirev.2016.08.011","article-title":"Landslides in a changing climate","volume":"162","author":"Gariano","year":"2016","journal-title":"Earth-Sci. Rev."},{"key":"ref_37","first-page":"230","article-title":"Mexico City land subsidence in 2014\u20132015 with Sentinel-1 IW TOPS: Results using Intermittent SBAS (ISBAS) technique","volume":"52","author":"Sowter","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s12517-018-3531-5","article-title":"Analysis and evaluation of landslide susceptibility: A review on articles published during 2005\u20132016 (periods of 2005\u20132012 and 2013\u20132016)","volume":"11","author":"Pourghasemi","year":"2018","journal-title":"Arab. J. Geosci."},{"key":"ref_39","first-page":"179","article-title":"Current and Future Status of GIS-based Landslide Susceptibility Mapping: A Literature Review","volume":"35","author":"Lee","year":"2019","journal-title":"Korean J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent scatterers in SAR interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ferretti, A. (2014). Satellite InSAR Data. Reservoir Monitoring from Space, EAGE Publications.","DOI":"10.3997\/9789073834712"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Holecz, F., Pasquali, P., and Milisavljevic, N. (2014). Mapping of ground deformations with interferometric stacking techniques. Land Applications of Radar Remote Sensing, InTechOpen.","DOI":"10.5772\/58225"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1007\/s11069-015-1740-8","article-title":"Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): An example from the northwestern coast of Malta","volume":"78","author":"Piacentini","year":"2015","journal-title":"Nat. Hazards"},{"key":"ref_44","unstructured":"Davies, T. (2015). Remote sensing of landslide motion with emphasis on satellite multitemporal interferometry applications: An overview. Landslide Hazards, Risk, and Disasters, Elsevier."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.enggeo.2014.03.003","article-title":"Investigating landslides and unstable slopes with satellite Multi Temporal Interferometry: Current issues and future perspectives","volume":"174","author":"Wasowski","year":"2014","journal-title":"Eng. Geol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1016\/j.asr.2005.06.059","article-title":"The contribution of radar interferometry to assessment of landslide hazards","volume":"37","author":"Rott","year":"2006","journal-title":"Adv. Space Res."},{"key":"ref_47","unstructured":"Preiss, M., and Stacy, J.S. (2006). Coherent Change Detection: Theoretical Description and Experimental Results, Defence Science and Technology Organisation, Intelligence, Surveillance and Reconnaissance Division."},{"key":"ref_48","unstructured":"Dwyer, E., Monaco, S., and Pasquali, P. (2000, January 16\u201320). An operational forest mapping tool using spaceborne SAR data. Proceedings of the ERS-ENVISAT Symposium, Gothenburg, Sweden."},{"key":"ref_49","unstructured":"Holecz, F., Barbieri, M., Cantone, A., Pasquali, P., and Monaco, S. (2009). Synergetic Use of ALOS PALSAR, ENVISAT ASAR and Landsat TM\/ETM+ Data for Land Cover and Change Mapping. JAXA Kyoto and Carbon Initiative, Japan Aerospace Exploration Agency, Earth Observation Research Cente."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Closson, D., Holecz, F., Pasquali, P., and Milisavljevic, N. (2014). Large scale mapping of forests and land cover with synthetic aperture radar data. Land Applications of Radar Remote Sensing, InTechOpen.","DOI":"10.5772\/55833"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Closson, D., Holecz, F., Pasquali, P., and Milisavljevic, N. (2014). Estimation of Cultivated Areas Using Multi-Temporal SAR Data. Land Applications of Radar Remote Sensing, InTechOpen.","DOI":"10.5772\/55833"},{"key":"ref_52","first-page":"387","article-title":"Detecting human-induced changes using coherent change detection in SAR images","volume":"Volume 38","author":"Wagner","year":"2010","journal-title":"Proceedings of the ISPRS TC VII Symposium, Vienna, Austria, 5\u20137 July 2010"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.14358\/PERS.70.10.1179","article-title":"Detection of Rapid Erosion in SE Spain: A GIS Approach Based on ERS SAR Coherence Imagery","volume":"70","author":"Liu","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1619","DOI":"10.1080\/014311600209931","article-title":"Comparison of SAR amplitude vs. coherence flood detection methods-a GIS application","volume":"21","author":"Nico","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.1029\/2012JB009178","article-title":"The 2010\u20132011 Canterbury, New Zealand seismic sequence: Multiple source analysis from InSAR data and modeling","volume":"117","author":"Atzori","year":"2012","journal-title":"J. Geophys. Res. (Solid Earth)"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.5194\/isprs-archives-XLII-3-1857-2018","article-title":"SAR coherence change detection of urban areas affected by disasters using Sentinel-1 imagery","volume":"42","author":"Washaya","year":"2018","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Washaya, P., Balz, T., and Mohamadi, B. (2018). Coherence Change-Detection with Sentinel-1 for Natural and Anthropogenic Disaster Monitoring in Urban Areas. Remote Sens., 10.","DOI":"10.3390\/rs10071026"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s12665-017-6403-5","article-title":"Phase and amplitude analyses of SAR data for landslide detection and monitoring in non-urban areas located in the North-Eastern Italian pre-Alps","volume":"76","author":"Tessari","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_59","first-page":"90","article-title":"Time series analysis of InSAR data: Methods and trends","volume":"115","author":"Sunar","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Bovenga, F., Pasquariello, G., and Refice, A. (2021). Statistically-Based Trend Analysis of MTInSAR Displacement Time Series. Remote Sens., 13.","DOI":"10.3390\/rs13122302"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s10291-021-01118-x","article-title":"JUST: MATLAB and python software for change detection and time series analysis","volume":"25","author":"Ghaderpour","year":"2021","journal-title":"GPS Solut."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"4870","DOI":"10.3390\/rs6064870","article-title":"Rapid damage assessment by means of multi-temporal SAR\u2014A comprehensive review and outlook to Sentinel-1","volume":"6","author":"Plank","year":"2014","journal-title":"Remote Sens."},{"key":"ref_63","first-page":"156","article-title":"Extraction of damaged regions using SAR data and neural networks. International Archives of Photogrammetry","volume":"33","author":"Ito","year":"2000","journal-title":"Remote Sens."},{"key":"ref_64","unstructured":"Ito, Y., and Hosokawa, M. (2002, January 24\u201328). Damage Estimation Model Using Temporal Coherence Ratio. Proceedings of the IEEE IGARSS, Toronto, ON, Canada."},{"key":"ref_65","unstructured":"Yonezawa, C., Tomiyama, N., and Takeuchi, S. (2002, January 24\u201328). Urban Damage Detection Using Decorrelation of SAR Interferometric Data. Proceedings of the IEEE IGARSS, Toronto, ON, Canada."},{"key":"ref_66","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_67","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1193\/1.2098987","article-title":"Earthquake-induced change detection in the 2003 Bam, Iran, earthquake by complex analysis using Envisat ASAR data","volume":"21","author":"Mansouri","year":"2005","journal-title":"Earthq. Spectra"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1193\/1.2101027","article-title":"Building damage mapping of the 2003 Bam, Iran, earthquake using Envisat\/ASAR intensity imagery","volume":"21","author":"Matsuoka","year":"2005","journal-title":"Earthq. Spectra"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3891","DOI":"10.1080\/01431160701871112","article-title":"Uplift and subsidence due to the 26 December 2004 Indonesian earthquake detected by SAR data","volume":"29","author":"Chini","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_70","unstructured":"Matsuoka, M., and Yamazaki, F. (2002, January 24\u201328). Application of the Damage Detection Method Using SAR Intensity Images to Recent Earthquakes. Proceedings of the IEEE IGARSS, Toronto, ON, Canada."},{"key":"ref_71","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_72","unstructured":"Matsuoka, M., and Yamazaki, F. (2000, January 24\u201328). Characteristics of Satellite SAR Images in the Areas Damaged by Earthquakes. Proceedings of the IEEE IGARSS, Honolulu, HY, USA."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Aimaiti, Y., Liu, W., Yamazaki, F., and Maruyama, Y. (2019). Earthquake-induced landslide mapping for the 2018 Hokkaido Eastern Iburi Earthquake using PALSAR-2 data. Remote Sens., 11.","DOI":"10.3390\/rs11202351"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1186\/s40623-019-1046-2","article-title":"Detection and interpretation of local surface deformation from the 2018 Hokkaido Eastern Iburi Earthquake using ALOS-2 SAR data","volume":"71","author":"Fujiwara","year":"2019","journal-title":"Earth Planets Space"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Jung, J., and Yun, S. (2020). Evaluation of Coherent and Incoherent Landslide Detection Methods Based on Synthetic Aperture Radar for Rapid Response: A Case Study for the 2018 Hokkaido Landslides. Remote Sens., 12.","DOI":"10.3390\/rs12020265"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1007\/s10346-019-01207-6","article-title":"Characteristics of landslides triggered by the 2018 Hokkaido Eastern Iburi earthquake, Northern Japan","volume":"16","author":"Zhang","year":"2019","journal-title":"Landslides"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"2521","DOI":"10.1007\/s10346-018-1092-z","article-title":"Landslides by the 2018 Hokkaido Iburi-Tobu Earthquake on September 6","volume":"15","author":"Yamagishi","year":"2018","journal-title":"Landslides"},{"key":"ref_78","first-page":"33","article-title":"Preliminary report of slope movements at Atsuma Town and its surrounding areas caused by the 2018 Hokkaido Eastern Iburi Earthquake","volume":"90","author":"Hirose","year":"2018","journal-title":"Rep. Local Indep. Adm. Agency Hokkaido Res. Organ."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1007\/s10346-019-01187-7","article-title":"Coseismic landslides triggered by the 2018 Hokkaido, Japan (Mw 6.6), earthquake: Spatial distribution, controlling factors, and possible failure mechanism","volume":"16","author":"Wang","year":"2019","journal-title":"Landslides"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"23","DOI":"10.5575\/geosoc.2015.0037","article-title":"Interior structure and sliding process of landslide body composed of stratified pyroclastic fall deposits at the Apporo 1 archaeological site, southeastern margin of the Ishikari Lowland, Hokkaido, North Japan","volume":"122","author":"Tajika","year":"2016","journal-title":"J. Geol. Soc. Jpn."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"13119","DOI":"10.1038\/s41598-019-48820-y","article-title":"Fluidized landslides triggered by the liquefaction of subsurface volcanic deposits during the 2018 Iburi-Tobu earthquake, Hokkaido","volume":"9","author":"Kameda","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_82","first-page":"102","article-title":"A New Method to Derive Precise Land-use and Land-cover Maps Using Multi-temporal Optical Data","volume":"34","author":"Hashimoto","year":"2014","journal-title":"J. Remote Sens. Soc. Jpn."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.geomorph.2012.11.005","article-title":"Geomorphons\u2014A pattern recognition approach to classification and mapping of landforms","volume":"182","author":"Jasiewicz","year":"2013","journal-title":"Geomorphology"},{"key":"ref_84","unstructured":"(2022, March 03). Alaska Satellite Facility Server. Available online: https:\/\/search.asf.alaska.edu\/#\/."},{"key":"ref_85","unstructured":"(2022, March 03). European Centre for Medium-Range Weather Forecasts (ECMWF) Data Dissemination Service. Available online: https:\/\/apps.ecmwf.int\/datasets\/data\/interim-full-daily\/levtype=sfc\/."},{"key":"ref_86","unstructured":"(2022, March 03). Sentinel Playground. Available online: https:\/\/www.sentinel-hub.com\/explore\/sentinelplayground\/."},{"key":"ref_87","unstructured":"(2022, March 03). Geospatial Information Authority of Japan, AW3D Standard. Available online: https:\/\/www.aw3d.jp\/en\/products\/standard\/."},{"key":"ref_88","unstructured":"(2022, March 03). ALOS Research and Application Project, High-Resolution Land Use and Land Cover Map Products. Available online: https:\/\/www.eorc.jaxa.jp\/ALOS\/en\/dataset\/lulc_e.htm."},{"key":"ref_89","unstructured":"(2022, March 03). Characteristics of Lanslides Triggered by the 2018 Hokkaido Eastern Iburi Earthquake, North Japan. Available online: https:\/\/zenodo.org\/record\/2577300#.YiInDOjMJhE."},{"key":"ref_90","first-page":"6","article-title":"Towards monitoring land cover and land use changes at a global scale: The Global Land Survey 2005","volume":"74","author":"Gutman","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Closson, D., Holecz, F., Pasquali, P., and Milisavljevic, N. (2014). Change Detection and Classification Using HighResolution SAR Interferometry. Land Applications of Radar Remote Sensing, InTechOpen.","DOI":"10.5772\/55833"},{"key":"ref_92","unstructured":"Beumier, C., Closson, D., Lacroix, V., Milisavljevic, N., and Yvinec, Y. (2014). InSAR Coherence and Intensity Changes Detection. Mine Action\u2014The Research Experience of the Royal Military Academy of Belgium, InTechOpen."},{"key":"ref_93","unstructured":"De Grandi, G.F., Leysen, M., Lee, J.S., and Schuler, D. (1997, January 3\u20138). Radar reflectivity estimation using multiple SAR scenes of the same target: Technique and applications. Proceedings of the IGARSS\u201997, IEEE International Geoscience and Remote Sensing Symposium Proceedings, Remote Sensing\u2014A Scientific Vision for Sustainable Development, Singapore."},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Campos-Taberner, M., Garc\u00eda-Haro, F.J., Camps-Valls, G., Grau-Muedra, G., Nutini, F., Busetto, L., Katsantonis, D., Stavrakoudis, D., Minakou, C., and Gatti, L. (2017). Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index. Remote Sens., 9.","DOI":"10.3390\/rs9030248"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2014.02.015","article-title":"Good practices for estimating area and assessing accuracy of land change","volume":"148","author":"Olofsson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_96","unstructured":"(2022, March 03). ESA WorldCover\u2014Worldwide Land Cover Mapping. Available online: https:\/\/esa-worldcover.org\/en."},{"key":"ref_97","unstructured":"(2022, March 03). ALOS Research and Application Project. Available online: https:\/\/www.eorc.jaxa.jp\/ALOS\/en\/index_e.htm."},{"key":"ref_98","unstructured":"(2022, March 03). The European Space Agency\u2014Sentinel Mission Guide. Available online: https:\/\/sentinel.esa.int\/web\/sentinel\/missions\/sentinel-1."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/6\/1350\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:34:28Z","timestamp":1760135668000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/6\/1350"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,10]]},"references-count":98,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["rs14061350"],"URL":"https:\/\/doi.org\/10.3390\/rs14061350","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,10]]}}}