{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T04:47:28Z","timestamp":1764996448499,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,7,28]],"date-time":"2023-07-28T00:00:00Z","timestamp":1690502400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"GIS &amp; Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, UAE"},{"name":"Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna, Austria"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The problem of estimating earthquake risk is one of the primary themes for researchers and investigators in the field of geosciences. The combined assessment of spatial probability and the determination of earthquake risk at large scales is challenging. To the best of the authors\u2019 knowledge, there no updated earthquake-hazard-and-risk assessments for the Eurasia region have been published since 1999. Considering that Eurasia is characterized by a seismically active Alpine\u2013Himalayan fault zone and the Pacific Ring of Fire, which are frequently affected by devastating events, a continental-scale risk assessment for Eurasia is necessary to check the global applicability of developed methods and to update the earthquake-hazard, -vulnerability, and -risk maps. The current study proposes an integrated deep-transfer-learning approach called the gated recurrent unit\u2013simple recurrent unit (GRU\u2013SRU) to estimate earthquake risk in Eurasia. In this regard, the GRU model estimates the spatial probability, while the SRU model evaluates the vulnerability. To this end, spatial probability assessment (SPA), and earthquake-vulnerability assessment (EVA) results were integrated to generate risk A, while the earthquake-hazard assessment (EHA) and EVA were considered to generate risk B. This research concludes that in the case of earthquake-risk assessment (ERA), the results obtained for Risk B were better than those for risk A. Using this approach, we also evaluated the stability of the factors and interpreted the interaction values to form a spatial prediction. The accuracy of our proposed integrated approach was examined by means of a comparison between the obtained deep learning (DL)-based results and the maps generated by the Global Earthquake Model (GEM). The accuracy of the SPA was 93.17%, while that of the EVA was 89.33%.<\/jats:p>","DOI":"10.3390\/rs15153759","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T01:48:50Z","timestamp":1690768130000},"page":"3759","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["An Integration of Deep Learning and Transfer Learning for Earthquake-Risk Assessment in the Eurasian Region"],"prefix":"10.3390","volume":"15","author":[{"given":"Ratiranjan","family":"Jena","sequence":"first","affiliation":[{"name":"GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9808-4120","authenticated-orcid":false,"given":"Abdallah","family":"Shanableh","sequence":"additional","affiliation":[{"name":"GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates"},{"name":"Civil and Environmental Engineering Department, University of Sharjah, Sharjah 27272, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7111-0061","authenticated-orcid":false,"given":"Rami","family":"Al-Ruzouq","sequence":"additional","affiliation":[{"name":"GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates"},{"name":"Civil and Environmental Engineering Department, University of Sharjah, Sharjah 27272, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9863-2054","authenticated-orcid":false,"given":"Biswajeet","family":"Pradhan","sequence":"additional","affiliation":[{"name":"Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia"},{"name":"Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6465-6231","authenticated-orcid":false,"given":"Mohamed Barakat A.","family":"Gibril","sequence":"additional","affiliation":[{"name":"GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates"}]},{"given":"Omid","family":"Ghorbanzadeh","sequence":"additional","affiliation":[{"name":"Institute of Advanced Research in Artificial Intelligence (IARAI), Landstra\u00dfer Hauptstra\u00dfe 5, 1030 Vienna, Austria"},{"name":"Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna, Peter-Jordan Strasse 82, 1190 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2169-8009","authenticated-orcid":false,"given":"Clement","family":"Atzberger","sequence":"additional","affiliation":[{"name":"Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna, Peter-Jordan Strasse 82, 1190 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3338-0092","authenticated-orcid":false,"given":"Mohamad Ali","family":"Khalil","sequence":"additional","affiliation":[{"name":"GIS & Remote Sensing Center, Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates"}]},{"given":"Himanshu","family":"Mittal","sequence":"additional","affiliation":[{"name":"National Center for Seismology, Ministry of Earth Sciences, Government of India, New Delhi 110003, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1203-741X","authenticated-orcid":false,"given":"Pedram","family":"Ghamisi","sequence":"additional","affiliation":[{"name":"Institute of Advanced Research in Artificial Intelligence (IARAI), Landstra\u00dfer Hauptstra\u00dfe 5, 1030 Vienna, Austria"},{"name":"Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, MachineLearning Group, Chemnitzer Street 40, 09599 Freiberg, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"454","DOI":"10.3390\/eng2040028","article-title":"A Critical Look at the Need for Performing Multi-Hazard Probabilistic Risk Assessment for Nuclear Power Plants","volume":"2","author":"Aras","year":"2021","journal-title":"Eng"},{"key":"ref_2","unstructured":"Ahorner, L. (1983). Protection of Nuclear Power Plants Against Seismic Effects Reference Ground Motion: Practice Followed in European Countries: (Synthesis Report), Harwood Academic for the Commission of the European Communities."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"295","DOI":"10.13182\/NT80-A32491","article-title":"Protection of Nuclear Power Plants against Seism","volume":"49","author":"Plichon","year":"1980","journal-title":"Nucl. Technol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1080\/00223131.2014.980347","article-title":"Seismic Protection Technology for Nuclear Power Plants: A Systematic Review","volume":"52","author":"Ji","year":"2015","journal-title":"J. Nucl. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1016\/j.ress.2006.04.022","article-title":"Seismic PSA Method for Multiple Nuclear Power Plants in a Site","volume":"92","author":"Hakata","year":"2007","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.pnucene.2018.09.018","article-title":"Potential Areas for Nuclear Power Plants Siting in Saudi Arabia: GIS-Based Multi-Criteria Decision-Making Analysis","volume":"110","author":"Damoom","year":"2019","journal-title":"Prog. Nucl. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3629","DOI":"10.1007\/s10064-021-02138-0","article-title":"An Artificial Intelligence-Based Approach to Predicting Seismic Hillslope Stability under Extreme Rainfall Events in the Vicinity of Wolsong Nuclear Power Plant, South Korea","volume":"80","author":"Pradhan","year":"2021","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1111\/mice.12136","article-title":"Systemic Seismic Risk Assessment of Road Networks Considering Interactions with the Built Environment","volume":"30","author":"Argyroudis","year":"2015","journal-title":"Comput. Civ. Infrastruct. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1016\/j.scitotenv.2019.07.203","article-title":"Multi-Hazard Probability Assessment and Mapping in Iran","volume":"692","author":"Pourghasemi","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1515\/geo-2020-0314","article-title":"Multihazard Susceptibility Assessment: A Case Study\u2013Municipality of \u0160trpce (Southern Serbia)","volume":"13","author":"Mijatov","year":"2021","journal-title":"Open Geosci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1007\/s12210-020-00871-4","article-title":"Earthquakes Spatio\u2013Temporal Distribution and Fractal Analysis in the Eurasian Seismic Belt","volume":"31","author":"Tang","year":"2020","journal-title":"Rend. Lincei. Sci. Fis. Nat."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1750018","DOI":"10.1142\/S0219691317500187","article-title":"Wavelet Analysis of the Temporal-Spatial Distribution in the Eurasia Seismic Belt","volume":"15","author":"Zheng","year":"2017","journal-title":"Int. J. Wavelets Multiresolut. Inf. Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0031-9201(00)00180-1","article-title":"Premonitory Raise of the Earthquakes\u2019 Correlation Range: Lesser Antilles","volume":"122","author":"Shebalin","year":"2000","journal-title":"Phys. Earth Planet. Inter."},{"key":"ref_14","first-page":"324","article-title":"The Time Space Distribution Characteristics and Migration Law of Large Earthquakes in the Indiam-Eurasian Plate Collision Deformation Area","volume":"25","author":"Genmo","year":"2019","journal-title":"J. Geomech."},{"key":"ref_15","first-page":"271","article-title":"Structural and Dynamical Regularity of Eurasia Seismicity and Some Aspects of Seismic Hazard Prediction","volume":"1","author":"Ulomov","year":"1994","journal-title":"Proc. XXIV Gen. Ass. ESC"},{"key":"ref_16","first-page":"43","article-title":"Waves of Seismogeodynamic Activation and Long-Term Prediction of Earthquakes","volume":"4","author":"Ulomov","year":"1993","journal-title":"Fiz. Zemli"},{"key":"ref_17","first-page":"1023","article-title":"Seismic hazard of northern Eurasia","volume":"42","author":"Ulomov","year":"1999","journal-title":"Ann. Geofis."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s00024-017-1659-y","article-title":"Probabilistic Seismic Hazard Assessment for Himalayan\u2013Tibetan Region from Historical and Instrumental Earthquake Catalogs","volume":"175","author":"Rahman","year":"2018","journal-title":"Pure Appl. Geophys."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1442","DOI":"10.1126\/science.1062584","article-title":"Himalayan Seismic Hazard","volume":"293","author":"Bilham","year":"2001","journal-title":"Science"},{"key":"ref_20","first-page":"872","article-title":"New Maps of General Seismic Zoning of North Eurasia","volume":"34","author":"Strakhov","year":"1998","journal-title":"Izv. Phys. Solid Earth"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/0013-7952(84)90047-4","article-title":"The MSK-78 Intensity Scale and Seismic Risk","volume":"20","author":"Lapajne","year":"1984","journal-title":"Eng. Geol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/0040-1951(83)90048-3","article-title":"A Probabilistic Approach for Evaluating Earthquake Risks, with Application to the Afro-Eurasian Junction","volume":"91","author":"Shapira","year":"1983","journal-title":"Tectonophysics"},{"key":"ref_23","first-page":"173","article-title":"On Earthquake Risk Assessment in the Himalayan Region","volume":"23","author":"Gupta","year":"1990","journal-title":"Mem. Geol. Soc. India"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Iakubovskii, D., Komendantova, N., Rovenskaya, E., Krupenev, D., and Boyarkin, D. (2019). Impacts of Earthquakes on Energy Security in the Eurasian Economic Union: Resilience of the Electricity Transmission Networks in Russia, Kazakhstan, and Kyrgyzstan. Geosciences, 9.","DOI":"10.3390\/geosciences9010054"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1098\/rsta.2006.1805","article-title":"Fatal Attraction: Living with Earthquakes, the Growth of Villages into Megacities, and Earthquake Vulnerability in the Modern World","volume":"364","author":"Jackson","year":"2006","journal-title":"Philos. Trans. R. Soc. A Math. Phys. Eng. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.11648\/j.ajce.20150301.11","article-title":"Seismic Vulnerability Assessment of Existing Building Stocks at Chandgaon in Chittagong City, Bangladesh","volume":"3","author":"Sarraz","year":"2015","journal-title":"Am. J. Civ. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1007\/s10518-012-9400-9","article-title":"Seismic Vulnerability of Bridges in Transport Networks Subjected to Environmental Deterioration","volume":"11","author":"Zanini","year":"2013","journal-title":"Bull. Earthq. Eng."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1080\/13669877.2014.988285","article-title":"Seismic Vulnerability Assessment of Historical Urban Centres: Case Study of the Old City Centre of Faro, Portugal","volume":"19","author":"Maio","year":"2016","journal-title":"J. Risk Res."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.engstruct.2014.01.031","article-title":"Seismic Vulnerability Assessment of Historical Masonry Structural Systems","volume":"62","author":"Asteris","year":"2014","journal-title":"Eng. Struct."},{"key":"ref_30","unstructured":"(2022, July 24). Population of Europe (2019)\u2014Worldometers. Available online: https:\/\/www.worldometers.info\/world-population\/europe-population\/."},{"key":"ref_31","unstructured":"(2022, July 24). Population of Asia (2019)\u2014Worldometers. Available online: https:\/\/www.worldometers.info\/world-population\/asia-population\/."},{"key":"ref_32","first-page":"1","article-title":"India and China in Central Asia: Understanding the New Rivalry in the Heart of Eurasia","volume":"235","author":"Wani","year":"2020","journal-title":"Obs. Res. Found."},{"key":"ref_33","unstructured":"Sarker, G.M. (1998). Seismic Attenuation Variations at Range Fronts in Central Eurasia, University of Kansas."},{"key":"ref_34","first-page":"8","article-title":"A Unified Seismotectonic Zonation of Northern Eurasia","volume":"8","author":"Ioffe","year":"2000","journal-title":"J. Earthq. Predict. Res."},{"key":"ref_35","unstructured":"Batjes, N.H. (1995). A Homogenized Soil Data File for Global Environmental Research: A Subset of FAO, ISRIC and NRCS Profiles (Version 1.0), ISRIC."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1016\/j.renene.2019.07.033","article-title":"Condition Monitoring of Wind Turbines Based on Spatio-Temporal Fusion of SCADA Data by Convolutional Neural Networks and Gated Recurrent Units","volume":"146","author":"Kong","year":"2020","journal-title":"Renew. Energy"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"101756","DOI":"10.1016\/j.bspc.2019.101756","article-title":"EEG-Based Emotion Recognition Using Simple Recurrent Units Network and Ensemble Learning","volume":"58","author":"Wei","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"21101","DOI":"10.1115\/1.4053304","article-title":"Interpretable Machine Learning in Damage Detection Using Shapley Additive Explanations","volume":"8","author":"Movsessian","year":"2022","journal-title":"ASCE-ASME J. Risk Uncertain. Eng. Syst. Part B Mech. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"104445","DOI":"10.1016\/j.cageo.2020.104445","article-title":"Comparative Study of Landslide Susceptibility Mapping with Different Recurrent Neural Networks","volume":"138","author":"Wang","year":"2020","journal-title":"Comput. Geosci."},{"key":"ref_40","unstructured":"Chung, J., Gulcehre, C., Cho, K., and Bengio, Y. (2014). Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. arXiv, preprint."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Lei, T., Zhang, Y., Wang, S.I., Dai, H., and Artzi, Y. (2017). Simple Recurrent Units for Highly Parallelizable Recurrence. arXiv, preprint.","DOI":"10.18653\/v1\/D18-1477"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Jiang, C., Chen, S., Chen, Y., Bo, Y., Han, L., Guo, J., Feng, Z., and Zhou, H. (2018). Performance Analysis of a Deep Simple Recurrent Unit Recurrent Neural Network (SRU-RNN) in MEMS Gyroscope de-Noising. Sensors, 18.","DOI":"10.3390\/s18124471"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1016\/0098-3004(96)00021-0","article-title":"Multivariate Interpolation to Incorporate Thematic Surface Data Using Inverse Distance Weighting (IDW)","volume":"22","author":"Bartier","year":"1996","journal-title":"Comput. Geosci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.geomorph.2011.12.040","article-title":"GIS-Based Support Vector Machine Modeling of Earthquake-Triggered Landslide Susceptibility in the Jianjiang River Watershed, China","volume":"145","author":"Xu","year":"2012","journal-title":"Geomorphology"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","article-title":"A Survey on Transfer Learning","volume":"22","author":"Pan","year":"2010","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Tan, C., Sun, F., Kong, T., Zhang, W., Yang, C., and Liu, C. (2018, January 4\u20137). A Survey on Deep Transfer Learning. Proceedings of the 27th International Conference on Artificial Neural Networks (ICANN 2018), Rhodes, Greece.","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Wang, H., Wang, L., and Zhang, L. (2022). Transfer Learning Improves Landslide Susceptibility Assessment. Gondwana Res.","DOI":"10.1016\/j.gr.2022.07.008"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3355390","article-title":"Video Description: A Survey of Methods, Datasets, and Evaluation Metrics","volume":"52","author":"Aafaq","year":"2019","journal-title":"ACM Comput. Surv."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s11069-007-9110-9","article-title":"Earthquake Risk and Its Mitigation in Istanbul","volume":"44","author":"Erdik","year":"2008","journal-title":"Nat. Hazards"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Jena, R., Pradhan, B., and Alamri, A.M. (2020). Susceptibility to Seismic Amplification and Earthquake Probability Estimation Using Recurrent Neural Network (RNN) Model in Odisha, India. Appl. Sci., 10.","DOI":"10.3390\/app10155355"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1007\/s10950-013-9412-1","article-title":"Considering Potential Seismic Sources in Earthquake Hazard Assessment for Northern Iran","volume":"18","author":"Abdollahzadeh","year":"2014","journal-title":"J. Seismol."},{"key":"ref_52","first-page":"999","article-title":"Seismic Hazard Assessment for Central, North and Northwest Europe: GSHAP Region 3","volume":"42","author":"Grunthal","year":"1999","journal-title":"Ann. Geofis."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.4401\/ag-3778","article-title":"Global Seismic Hazard Assessment Program (GSHAP) in Continental Asia","volume":"42","author":"Zhang","year":"1999","journal-title":"Ann. Geophys."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1007\/s11069-017-2822-6","article-title":"A GIS-Based Multi-Criteria Analysis Model for Earthquake Vulnerability Assessment Using Choquet Integral and Game Theory","volume":"87","author":"Moradi","year":"2017","journal-title":"Nat. Hazards"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"103936","DOI":"10.1016\/j.autcon.2021.103936","article-title":"Machine-Learning Based Vulnerability Analysis of Existing Buildings","volume":"132","author":"Ruggieri","year":"2021","journal-title":"Autom. Constr."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1111\/j.1539-6924.2010.01528.x","article-title":"On Some Recent Definitions and Analysis Frameworks for Risk, Vulnerability, and Resilience","volume":"31","author":"Aven","year":"2011","journal-title":"Risk Anal. Int. J."},{"key":"ref_57","first-page":"65","article-title":"Vulnerability Concepts in Hazard and Risk Assessment","volume":"42","author":"Kumpulainen","year":"2006","journal-title":"Spec. Pap. Surv. Finl."},{"key":"ref_58","first-page":"75","article-title":"Earthquake Risks in Bangladesh: Causes, Vulnerability, Preparedness and Strategies for Mitigation","volume":"5","author":"Islam","year":"2016","journal-title":"ARPN J. Earth Sci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"4020269","DOI":"10.1061\/(ASCE)ST.1943-541X.0002831","article-title":"Regional Seismic Risk Assessment of Infrastructure Systems through Machine Learning: Active Learning Approach","volume":"146","author":"Mangalathu","year":"2020","journal-title":"J. Struct. Eng."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.isprsjprs.2021.07.004","article-title":"Automated Building Characterization for Seismic Risk Assessment Using Street-Level Imagery and Deep Learning","volume":"180","author":"Pelizari","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/s11069-021-04574-3","article-title":"Potential Seismogenic Asperities in the Garhwal\u2013Kumaun Region, NW Himalaya: Seismotectonic Implications","volume":"107","author":"Tiwari","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"105208","DOI":"10.1016\/j.jseaes.2022.105208","article-title":"Stress Distribution in the Western India-Eurasia Collision Zone, Its Kinematics and Seismotectonic Implications","volume":"230","author":"Prasath","year":"2022","journal-title":"J. Asian Earth Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.tecto.2017.05.007","article-title":"Crustal Velocity Structure and Earthquake Processes of Garhwal-Kumaun Himalaya: Constraints from Regional Waveform Inversion and Array Beam Modeling","volume":"712","author":"Negi","year":"2017","journal-title":"Tectonophysics"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/15\/3759\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:21:39Z","timestamp":1760127699000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/15\/3759"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,28]]},"references-count":63,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["rs15153759"],"URL":"https:\/\/doi.org\/10.3390\/rs15153759","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,7,28]]}}}