{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T12:00:36Z","timestamp":1774612836522,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,4,2]],"date-time":"2023-04-02T00:00:00Z","timestamp":1680393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Academic Melting Pot of KMITL research fund","award":["KREF206602"],"award-info":[{"award-number":["KREF206602"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Global Navigation Satellite System (GNSS)- and Remote Sensing (RS)-based Earth observations have a significant approach on the monitoring of natural disasters. Since the evolution and appearance of earthquake precursors exhibit complex behavior, the need for different methods on multiple satellite data for earthquake precursors is vital for prior and after the impending main shock. This study provided a new approach of deep machine learning (ML)-based detection of ionosphere and atmosphere precursors. In this study, we investigate multi-parameter precursors of different physical nature defining the states of ionosphere and atmosphere associated with the event in Japan on 13 February 2021 (Mw 7.1). We analyzed possible precursors from surface to ionosphere, including Sea Surface Temperature (SST), Air Temperature (AT), Relative Humidity (RH), Outgoing Longwave Radiation (OLR), and Total Electron Content (TEC). Furthermore, the aim is to find a possible pre-and post-seismic anomaly by implementing standard deviation (STDEV), wavelet transformation, the Nonlinear Autoregressive Network with Exogenous Inputs (NARX) model, and the Long Short-Term Memory Inputs (LSTM) network. Interestingly, every method shows anomalous variations in both atmospheric and ionospheric precursors before and after the earthquake. Moreover, the geomagnetic irregularities are also observed seven days after the main shock during active storm days (Kp &gt; 3.7; Dst &lt; \u221230 nT). This study demonstrates the significance of ML techniques for detecting earthquake anomalies to support the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) mechanism for future studies.<\/jats:p>","DOI":"10.3390\/rs15071904","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T02:10:13Z","timestamp":1680487813000},"page":"1904","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Deep Machine Learning Based Possible Atmospheric and Ionospheric Precursors of the 2021 Mw 7.1 Japan Earthquake"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-5445-8876","authenticated-orcid":false,"given":"Muhammad Umar","family":"Draz","sequence":"first","affiliation":[{"name":"Department of Space Science, Space Education and GNSS Lab, National Center of GIS & Space Applications, Institute of Space Technology, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6552-8445","authenticated-orcid":false,"given":"Munawar","family":"Shah","sequence":"additional","affiliation":[{"name":"Department of Space Science, Space Education and GNSS Lab, National Center of GIS & Space Applications, Institute of Space Technology, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1259-1883","authenticated-orcid":false,"given":"Punyawi","family":"Jamjareegulgarn","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Engineering, King Mongkut\u2019s Institute of Technology Ladkrabang, Prince of Chumphon Campus, Chumphon 86160, Thailand"}]},{"given":"Rasim","family":"Shahzad","sequence":"additional","affiliation":[{"name":"Department of Space Science, Space Education and GNSS Lab, National Center of GIS & Space Applications, Institute of Space Technology, Islamabad 44000, Pakistan"}]},{"given":"Ahmad M.","family":"Hasan","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Future University in Egypt, Cairo 11835, Egypt"}]},{"given":"Nivin A.","family":"Ghamry","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, Egypt"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"L15303","DOI":"10.1029\/2011GL048282","article-title":"Exploring land surface temperature earthquake precursors: A focus on the Gujarat (India) earthquake of 2001","volume":"38","author":"Blackett","year":"2011","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"L17312","DOI":"10.1029\/2011GL047908","article-title":"Ionospheric electron enhancement preceding the 2011 Tohoku-Oki earthquake","volume":"38","author":"Heki","year":"2011","journal-title":"Geophys. Res. Lett."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.jastp.2013.06.006","article-title":"Ionospheric precursors to large earthquakes: A case study of the 2011 Japanese Tohoku Earthquake","volume":"102","author":"Carter","year":"2013","journal-title":"J. Atmos. Solar-Terrestrial Phys."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.jog.2015.10.002","article-title":"Statistical characteristics of seismo-ionospheric GPS TEC disturbances prior to global Mw \u2265 5.0 earthquakes (1998\u20132014)","volume":"92","author":"Shah","year":"2015","journal-title":"J. Geodyn."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111620","DOI":"10.1016\/j.rse.2019.111620","article-title":"Possible ionosphere and atmosphere precursory analysis related to Mw > 6.0 earthquakes in Japan","volume":"239","author":"Shah","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_6","first-page":"1002705","article-title":"Possible thermal anomalies associated with global terrestrial earthquakes during 2000\u20132019 based on MODIS-LST","volume":"19","author":"Shah","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.asr.2022.04.025","article-title":"Possible seismo-ionospheric anomalies associated with Mw > 5.0 earthquakes during 2000\u20132020 from GNSS TEC","volume":"70","author":"Shah","year":"2022","journal-title":"Adv. Space Res."},{"key":"ref_8","first-page":"1291","article-title":"Outgoing longwave radiations as pre-earthquake signals: Preliminary results of 24 September 2013 (M 7.7) earthquake","volume":"106","author":"Venkatanathan","year":"2014","journal-title":"Curr. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.jseaes.2010.03.005","article-title":"Lithosphere\u2013Atmosphere\u2013Ionosphere Coupling (LAIC) model\u2014An unified concept for earthquake precursors validation","volume":"41","author":"Pulinets","year":"2011","journal-title":"J. Asian Earth Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.5194\/angeo-22-1585-2004","article-title":"Pre-earthquake ionospheric anomalies registered by continuous GPS TEC measurements","volume":"22","author":"Liu","year":"2004","journal-title":"Ann. Geophys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2532","DOI":"10.1016\/j.asr.2013.11.048","article-title":"Model for the VLF\/LF radio signal anomalies formation associated with earthquakes","volume":"54","author":"Sorokin","year":"2014","journal-title":"Adv. Space Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"109401","DOI":"10.1088\/1674-1056\/23\/10\/109401","article-title":"Study of typical space wave\u2014Particle coupling events possibly related with seismic activity","volume":"23","author":"Zhang","year":"2014","journal-title":"Chin. Phys. B"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"597","DOI":"10.5194\/angeo-21-597-2003","article-title":"High-energy charged particle bursts in the near-Earth space as earthquake precursors","volume":"21","author":"Aleksandrin","year":"2003","journal-title":"Ann. Geophys."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/S0264-3707(02)00015-7","article-title":"Charge generation and propagation in igneous rocks","volume":"33","author":"Freund","year":"2002","journal-title":"J. Geodyn."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2151","DOI":"10.1002\/2016JA023652","article-title":"A statistical study of global ionospheric map total electron content changes prior to occurrences of M \u2265 6.0 earthquakes during 2000\u20132014","volume":"122","author":"Thomas","year":"2017","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s12303-019-0038-3","article-title":"Seismo-ionospheric anomalies associated with Mw 7.8 Nepal earthquake on 2015 April 25 from CMONOC GPS data","volume":"24","author":"Shi","year":"2020","journal-title":"Geosci. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"137","DOI":"10.3846\/gac.2019.10246","article-title":"Study of TEC variations using permanent stations GNSS data in relation with seismic events. Application on Samothrace earthquake of 24 May 2014","volume":"45","author":"Pikridas","year":"2019","journal-title":"Geod. Cartogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2836","DOI":"10.1016\/j.asr.2017.07.007","article-title":"Atmospheric-ionospheric disturbances following the April 2015 Calbuco volcano from GPS and OMI observations","volume":"60","author":"Liu","year":"2017","journal-title":"Adv. Space Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"123","DOI":"10.5800\/GT-2018-9-1-0341","article-title":"Thermal anomalies prior to The 2015 Gorkha (Nepal) earthquake from modis land surface temperature and outgoing longwave radiations","volume":"9","author":"Shah","year":"2018","journal-title":"Geodyn. Tectonophys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.jog.2019.05.004","article-title":"Seismo ionospheric anomalies before the 2007 M7. 7 Chile earthquake from GPS TEC and DEMETER","volume":"127","author":"Shah","year":"2019","journal-title":"J. Geodyn."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.47264\/idea.nasij\/1.1.1","article-title":"Comparison of GPS TEC with iri models of 2007, 2012, and 1 2016 over sukkur, Pakistan","volume":"1","author":"Hussain","year":"2020","journal-title":"Nat. Appl. Sci. Int. J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2169","DOI":"10.5194\/nhess-10-2169-2010","article-title":"Study of outgoing longwave radiation anomalies associated with Haiti earthquake","volume":"10","author":"Xiong","year":"2010","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7387","DOI":"10.1007\/s13369-021-06524-4","article-title":"Evaluation of thermal anomaly preceding northern red sea earthquake, the 16th June 2020","volume":"47","author":"Mohamed","year":"2022","journal-title":"Arab. J. Sci. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.jastp.2018.10.004","article-title":"Seismoionospheric anomalies associated with earthquakes from the analysis of the ionosonde data","volume":"179","author":"Ahmed","year":"2018","journal-title":"J. Atmos. Solar-Terrestrial Phys."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.geog.2017.11.008","article-title":"Pre-seismic ionospheric anomalies of the 2013 Mw = 7.7 Pakistan earthquake from GPS and COSMIC observations","volume":"9","author":"Shah","year":"2018","journal-title":"Geod. Geodyn."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2088","DOI":"10.1016\/j.asr.2018.12.028","article-title":"Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015\u20132017","volume":"63","author":"Tariq","year":"2019","journal-title":"Adv. Space Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"101782","DOI":"10.1016\/j.jog.2020.101782","article-title":"Seismo ionospheric anomalies possibly associated with the 2018 Mw 8.2 Fiji earthquake detected with GNSS TEC","volume":"140","author":"Kiyani","year":"2020","journal-title":"J. Geodyn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1016\/j.actaastro.2020.12.042","article-title":"Assessment of improvement of the IRI model for foF2 variability over three latitudes in different hemispheres during low and high solar activities","volume":"180","author":"Inyurt","year":"2021","journal-title":"Acta Astronaut."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s40328-020-00325-1","article-title":"Possible ionospheric anomalies associated with the 2009 M w 6.4 Taiwan earthquake from DEMETER and GNSS TEC","volume":"56","author":"Abbasi","year":"2021","journal-title":"Acta Geod. Geophys."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1007\/s00704-022-04082-9","article-title":"Spatiotemporal Analysis of Drought and Rainfall in Pakistan via Standardized Precipitation Index: Homogeneous Regions, Trend, Wavelet and Influence of El Ni\u00f1o-Southern Oscillation","volume":"149","author":"Shah","year":"2022","journal-title":"Theor. Appl. Climatol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Khan, M.M., Ghaffar, B., Shahzad, R., Khan, M.R., Shah, M., Amin, A.H., Eldin, S.M., Naqvi, N.A., and Ali, R. (2022). Atmospheric anomalies associated with the 2021 M w 7.2 Haiti earthquake using machine learning from multiple satellites. Sustainability, 14.","DOI":"10.3390\/su142214782"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3731","DOI":"10.1016\/j.asr.2022.08.050","article-title":"Ionospheric-Thermospheric responses to the May and September 2017 geomagnetic storms over Asian regions","volume":"70","author":"Tariq","year":"2022","journal-title":"Adv. Space Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1109\/TDEI.2022.3218490","article-title":"Numerical Modeling of Branching-Streamer Propagation in Ester-Based Insulating Oil under Positive Lightning Impulse Voltage: Effects from Needle Curvature Radius","volume":"30","author":"Li","year":"2022","journal-title":"IEEE Trans. Dielectr. Electr. Insul."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.5194\/nhess-19-1471-2019","article-title":"Update of the tsunami catalogue of New Caledonia using a decision table based on seismic data and marigraphic records","volume":"19","author":"Roger","year":"2019","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1977890","DOI":"10.2113\/2022\/1977890","article-title":"Research on the Macro-Mesoscopic Response Mechanism of Multisphere Approximated Heteromorphic Tailing Particles","volume":"2022","author":"Wang","year":"2022","journal-title":"Lithosphere"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3591","DOI":"10.1175\/JCLI-D-20-0487.1","article-title":"Impact of the Indian Ocean Dipole on Evolution of the Subsequent ENSO: Relative Roles of Dynamic and Thermodynamic Processes","volume":"34","author":"Yue","year":"2021","journal-title":"J. Clim."},{"key":"ref_37","first-page":"7500205","article-title":"RMCHN: A Residual Modular Cascaded Heterogeneous Network for Noise Suppression in DAS-VSP Records","volume":"20","author":"Zhong","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"4022003","DOI":"10.1061\/(ASCE)ME.1943-5479.0001022","article-title":"Risk Propagation in Multilayer Heterogeneous Network of Coupled System of Large Engineering Project","volume":"38","author":"Chen","year":"2022","journal-title":"J. Manag. Eng."},{"key":"ref_39","first-page":"6502705","article-title":"Gaussian Inflection Point Selection for LiDAR Hidden Echo Signal Decomposition","volume":"19","author":"Zhou","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.1109\/TGRS.2020.3023135","article-title":"Selection of Optimal Building Facade Texture Images From UAV-Based Multiple Oblique Image Flows","volume":"59","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","first-page":"1113","article-title":"Seismic performance analysis of a wind turbine with a monopile foundation affected by sea ice based on a simple numerical method","volume":"15","author":"Huang","year":"2021","journal-title":"Eng. Appl. Comput. Fluid Mech."},{"key":"ref_42","first-page":"4500514","article-title":"Model-Based Synthetic Geoelectric Sampling for Magnetotelluric Inversion with Deep Neural Networks","volume":"60","author":"Li","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","first-page":"5205517","article-title":"Fast Inverse-Scattering Reconstruction for Airborne High-Squint Radar Imagery Based on Doppler Centroid Compensation","volume":"60","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2573","DOI":"10.1007\/s11069-021-04505-2","article-title":"A simple Monte Carlo method for estimating the chance of a cyclone impact","volume":"107","author":"Xie","year":"2021","journal-title":"Nat. Hazards"},{"key":"ref_45","first-page":"5303435","article-title":"Deduction of sudden rainstorm scenarios: Integrating decision makers\u2019 emotions, dynamic Bayesian network and DS evidence theory","volume":"45","author":"Xie","year":"2022","journal-title":"Nat. Hazards"},{"key":"ref_46","first-page":"23","article-title":"Impact of dam construction on precipitation: A regional perspective","volume":"63","author":"Zhu","year":"2022","journal-title":"Mar. Freshw. Res."},{"key":"ref_47","unstructured":"Schaer, S. (1999). Mapping and Predicting the Earth\u2019s Ionosphere Using the Global Positioning System, Schweizerische Geod\u00e4tische Kommission."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1007\/BF00876083","article-title":"Estimation of the size of earthquake preparation zones","volume":"117","author":"Dobrovolsky","year":"1979","journal-title":"Pure Appl. Geophys."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2019RS006931","article-title":"A machine learning-based detection of earthquake precursors using ionospheric data","volume":"55","author":"Akyol","year":"2020","journal-title":"Radio Sci."},{"key":"ref_50","unstructured":"Al Ibrahim, M., Park, J., and Athens, N. (2018). Earthquake Warning System: Detecting Earthquake Precursor Signals Using Deep Neural Networks, Stanford University Press."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.tecto.2006.05.042","article-title":"Outgoing long wave radiation variability from IR satellite data prior to major earthquakes","volume":"431","author":"Ouzounov","year":"2007","journal-title":"Tectonophysics"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"27","DOI":"10.5194\/nhess-13-27-2013","article-title":"Variations of multi-parameter observations in atmosphere related to earthquake","volume":"13","author":"Jing","year":"2013","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1016\/S0191-8141(01)00170-5","article-title":"Offset and evolution of the Gowk fault, SE Iran: A major intra-continental strike-slip system","volume":"24","author":"Walker","year":"2002","journal-title":"J. Struct. Geol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5636","DOI":"10.1080\/10106049.2021.1922513","article-title":"Spatio-temporal variability of sea surface temperatures in the Red Sea and their implications on Saudi Arabia coral reefs","volume":"37","author":"Hereher","year":"2022","journal-title":"Geocarto Int."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"105568","DOI":"10.1016\/j.jastp.2021.105568","article-title":"Artificial Neural Network based thermal anomalies associated with earthquakes in Pakistan from MODIS LST","volume":"215","author":"Shah","year":"2021","journal-title":"J. Atmos. Solar-Terrestrial Phys."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"7","DOI":"10.5194\/ee-2-7-2007","article-title":"Stimulated infrared emission from rocks: Assessing a stress indicator","volume":"2","author":"Freund","year":"2007","journal-title":"eEarth"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/JSTARS.2021.3134495","article-title":"Ionospheric--thermospheric responses in south America to the august 2018 geomagnetic storm based on multiple observations","volume":"15","author":"Shah","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_58","first-page":"96","article-title":"Anomalous sporadic-E layers observed before M7.2 Hyogo-ken Nanbu earthquake; Terrestrial gas emanation model","volume":"17","author":"Ondoh","year":"2003","journal-title":"Adv. Polar Upper Atmos. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s10509-020-03894-3","article-title":"Comparison of TEC from IRI-2016 and GPS during the low solar activity over Turkey","volume":"365","author":"Tariq","year":"2020","journal-title":"Astrophys. Space Sci."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Yin, L., Wang, L., Tian, J., Yin, Z., Liu, M., and Zheng, W. (2023). Atmospheric Density Inversion Based on Swarm-C Satellite Accelerometer. Appl. Sci., 13.","DOI":"10.3390\/app13063610"},{"key":"ref_61","first-page":"34","article-title":"Remote sensing and geostatistics in urban water-resource monitoring: A review","volume":"82","author":"Liu","year":"2023","journal-title":"Mar. Freshw. Res."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"e1938E","DOI":"10.1029\/2020EF001938","article-title":"Global CO2 Consumption by Silicate Rock Chemical Weathering: It\u2019s past and Future","volume":"9","author":"Zhang","year":"2021","journal-title":"Earth\u2019s Future"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"110654","DOI":"10.1016\/j.petrol.2022.110654","article-title":"Nonlinear seismic inversion by physics-informed Caianiello convolutional neural networks for overpressure prediction of source rocks in the offshore Xihu depression, East China","volume":"215","author":"Cheng","year":"2022","journal-title":"J. Pet. Sci. Eng."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Shahzad, F., Shah, M., Riaz, S., Ghaffar, B., Ullah, I., and Eldin, S.M. (2023). Integrated Analysis of LithosphereAtmosphere-Ionospheric Coupling Associated with the 2021 Mw 7.2 Haiti Earthquake. Atmosphere, 14.","DOI":"10.3390\/atmos14020347"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Shah, M., Shahzad, R., Ehsan, M., Ghaffar, B., Ullah, I., Jamjareegulgarn, P., and Hassan, A.M. (2023). Seismo Ionospheric Anomalies around and over the Epicenters of Pakistan Earthquakes. Atmosphere, 14.","DOI":"10.3390\/atmos14030601"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1904\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:08:27Z","timestamp":1760123307000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/7\/1904"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,2]]},"references-count":65,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15071904"],"URL":"https:\/\/doi.org\/10.3390\/rs15071904","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,2]]}}}