{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T23:40:35Z","timestamp":1778542835548,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,16]],"date-time":"2023-04-16T00:00:00Z","timestamp":1681603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41929001"],"award-info":[{"award-number":["41929001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFC3004302"],"award-info":[{"award-number":["2022YFC3004302"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["JAT220325"],"award-info":[{"award-number":["JAT220325"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["MJY23002"],"award-info":[{"award-number":["MJY23002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["41929001"],"award-info":[{"award-number":["41929001"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2022YFC3004302"],"award-info":[{"award-number":["2022YFC3004302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["JAT220325"],"award-info":[{"award-number":["JAT220325"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["MJY23002"],"award-info":[{"award-number":["MJY23002"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fujian Educational Bureau","award":["41929001"],"award-info":[{"award-number":["41929001"]}]},{"name":"Fujian Educational Bureau","award":["2022YFC3004302"],"award-info":[{"award-number":["2022YFC3004302"]}]},{"name":"Fujian Educational Bureau","award":["JAT220325"],"award-info":[{"award-number":["JAT220325"]}]},{"name":"Fujian Educational Bureau","award":["MJY23002"],"award-info":[{"award-number":["MJY23002"]}]},{"name":"Initial Scientific Research Fund of Talents in Minjiang University","award":["41929001"],"award-info":[{"award-number":["41929001"]}]},{"name":"Initial Scientific Research Fund of Talents in Minjiang University","award":["2022YFC3004302"],"award-info":[{"award-number":["2022YFC3004302"]}]},{"name":"Initial Scientific Research Fund of Talents in Minjiang University","award":["JAT220325"],"award-info":[{"award-number":["JAT220325"]}]},{"name":"Initial Scientific Research Fund of Talents in Minjiang University","award":["MJY23002"],"award-info":[{"award-number":["MJY23002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Today, synthetic aperture radar (SAR) satellites provide large amounts of SAR data at unprecedented temporal resolutions, which promotes hazard dynamic monitoring and disaster mitigation with interferometric SAR (InSAR) technology. This study focuses on big InSAR data dynamical processing in areas of serious decorrelation and large gradient deformation. A new stepwise temporal phase optimization method is proposed to alleviate the decorrelation, customized for deformation parameter dynamical estimation. Subsequently, the sequential estimation theory is introduced to the intermittent small baseline subset (ISBAS) approach to dynamically obtain deformation time series with dense coherent targets. Then, we analyze the reason for the unstable accuracy of deformation parameters using sequential distributed scatterers-ISBAS technology, and construct five indices to describe the quality of deformation parameters pixel-by-pixel. Finally, real data of the post-failure Baige landslide at the Jinsha River in China is used to demonstrate the validity of the proposed approach.<\/jats:p>","DOI":"10.3390\/rs15082097","type":"journal-article","created":{"date-parts":[[2023,4,17]],"date-time":"2023-04-17T02:02:59Z","timestamp":1681696979000},"page":"2097","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Sequential DS-ISBAS InSAR Deformation Parameter Dynamic Estimation and Quality Evaluation"],"prefix":"10.3390","volume":"15","author":[{"given":"Baohang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geography and Oceanography, Minjiang University, Fuzhou 350108, China"},{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5730-9602","authenticated-orcid":false,"given":"Chaoying","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojie","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Geological Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhong","family":"Lu","sequence":"additional","affiliation":[{"name":"Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75275, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4859-4365","authenticated-orcid":false,"given":"Chuanjin","family":"Liu","sequence":"additional","affiliation":[{"name":"The Second Monitoring and Application Center, China Earthquake Administration, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxia","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography and Oceanography, Minjiang University, Fuzhou 350108, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.rse.2012.05.025","article-title":"Large-area landslide detection and monitoring with ALOS\/PALSAR imagery data over Northern California and Southern Oregon, USA","volume":"124","author":"Zhao","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Lu, Z., and Dzurisin, D. (2014). InSAR Imaging of Aleutian Volcanoes: Monitoring a Volcanic Arc from Space, Springer.","DOI":"10.1007\/978-3-642-00348-6"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Wang, B., Zhao, C., Zhang, Q., and Peng, M. (2019). Sequential InSAR Time Series Deformation Monitoring of Land Subsidence and Rebound in Xi\u2019an, China. Remote Sens., 11.","DOI":"10.3390\/rs11232854"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/LGRS.2004.842375","article-title":"Accurate estimation of correlation in InSAR observations","volume":"2","author":"Zebker","year":"2005","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_5","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":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"L23611","DOI":"10.1029\/2004GL021737","article-title":"A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers","volume":"31","author":"Hooper","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_7","unstructured":"Kampes, B. (2006). Radar Interferometry: Persistent Scatterer Technique, Springer."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1109\/TGRS.2011.2124465","article-title":"A new algorithm for processing interferometric data-stacks: SqueeSAR","volume":"49","author":"Ferretti","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"HO TONG MINH, D., Hanssen, R., and Rocca, F. (2020). Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives. Remote Sens., 12.","DOI":"10.3390\/rs12091364"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4035","DOI":"10.1029\/1998GL900033","article-title":"Radar interferogram filtering for geophysical applications","volume":"25","author":"Goldstein","year":"1998","journal-title":"Geophys. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1109\/LGRS.2010.2083631","article-title":"Adaptive InSAR stack multilooking exploiting amplitude statistics: A comparison between different techniques and practical results","volume":"8","author":"Parizzi","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3436","DOI":"10.1109\/TGRS.2008.2001756","article-title":"On the exploitation of target statistics for SAR interferometry applications","volume":"46","author":"Guarnieri","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2050","DOI":"10.1109\/TGRS.2014.2352853","article-title":"CAESAR: An approach based on covariance matrix decomposition to improve multibaseline\u2013multitemporal interferometric SAR processing","volume":"53","author":"Fornaro","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5637","DOI":"10.1109\/TGRS.2017.2711037","article-title":"Sequential estimator: Toward efficient InSAR time series analysis","volume":"55","author":"Ansari","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3914","DOI":"10.1109\/JSTARS.2021.3070750","article-title":"An adaptive phase optimization algorithm for distributed scatterer phase history retrieval","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4394","DOI":"10.1109\/TGRS.2015.2396875","article-title":"Improved EMCF-SBAS processing chain based on advanced techniques for the noise-filter and selection of small baseline multi-look DInSAR interferograms","volume":"53","author":"Pepe","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1109\/TGRS.2006.872907","article-title":"MST-based stepwise connection strategies for multipass radar data, with application to coregistration and equalization","volume":"44","author":"Refice","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1080\/2150704X.2019.1650981","article-title":"Semi-automatic selection of optimum image pairs based on the interferometric coherence for time series SAR interferometry","volume":"10","author":"Wu","year":"2019","journal-title":"Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wang, B., Zhang, Q., Pepe, A., Mastro, P., Zhao, C., Lu, Z., and Zhang, J. (2021). Analysis of groundwater depletion\/inflation and freeze\u2013thaw cycles in the Northern Urumqi region with the SBAS technique and an adjusted network of interferograms. Remote Sens., 13.","DOI":"10.3390\/rs13112144"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"112898","DOI":"10.1109\/ACCESS.2020.3002990","article-title":"Adaptively Selecting Interferograms for SBAS-InSAR Based on Graph Theory and Turbulence Atmosphere","volume":"8","author":"Duan","year":"2020","journal-title":"IEEE Access"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1080\/2150704X.2013.823673","article-title":"DInSAR estimation of land motion using intermittent coherence with application to the South Derbyshire and Leicestershire coalfields","volume":"4","author":"Sowter","year":"2013","journal-title":"Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Falabella, F., Serio, C., Zeni, G., and Pepe, A. (2020). On the use of weighted least-squares approaches for differential interferometric SAR analyses: The weighted adaptive variable-length (WAVE) technique. Sensors, 20.","DOI":"10.3390\/s20041103"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.rse.2017.05.016","article-title":"The relationship between intermittent coherence and precision of ISBAS InSAR ground motion velocities: ERS-1\/2 case studies in the UK","volume":"202","author":"Cigna","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"111941","DOI":"10.1016\/j.rse.2020.111941","article-title":"Disruptive influences of residual noise, network configuration and data gaps on InSAR-derived land motion rates using the SBAS technique","volume":"247","author":"Bui","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Pepe, A. (2021). Multi-Temporal Small Baseline Interferometric SAR Algorithms: Error Budget and Theoretical Performance. Remote Sens., 13.","DOI":"10.3390\/rs13040557"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1080\/2150704X.2020.1864055","article-title":"Update two-dimensional SAR offset tracking deformation time series with complex sequential least squares estimation","volume":"12","author":"Wang","year":"2021","journal-title":"Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1109\/LGRS.2019.2938330","article-title":"Sequential estimation of dynamic deformation parameters for SBAS-InSAR","volume":"17","author":"Wang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"7297","DOI":"10.1109\/JSTARS.2021.3096996","article-title":"Long-Term Continuously Updated Deformation Time Series from Multisensor InSAR in Xi\u2019an, China From 2007 to 2021","volume":"14","author":"Wang","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2437","DOI":"10.1109\/JSTARS.2022.3159666","article-title":"Near Real-Time InSAR Deformation Time Series Estimation With Modified Kalman Filter and Sequential Least Squares","volume":"15","author":"Wang","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","first-page":"3125574","article-title":"Dynamic Estimation of Multi-Dimensional Deformation Time Series from InSAR Based on Kalman Filter and Strain Model","volume":"60","author":"Liu","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","first-page":"102812","article-title":"A new algorithm for landslide dynamic monitoring with high temporal resolution by Kalman filter integration of multiplatform time-series InSAR processing","volume":"110","author":"Cai","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1838","DOI":"10.1109\/LGRS.2015.2430752","article-title":"Mathematical framework for phase-triangulation algorithms in distributed-scatterer interferometry","volume":"12","author":"Cao","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.isprsjprs.2018.12.008","article-title":"Mapping the Yellow River Delta land subsidence with multitemporal SAR interferometry by exploiting both persistent and distributed scatterers","volume":"148","author":"Zhang","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1080\/2150704X.2017.1392633","article-title":"An improved SAR interferogram denoising method based on principal component analysis and the Goldstein filter","volume":"9","author":"Wang","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1364\/JOSAA.18.000338","article-title":"Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization","volume":"18","author":"Chen","year":"2001","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1109\/TGRS.2018.2853706","article-title":"Toward mitigating stratified tropospheric delays in multitemporal InSAR: A quadtree aided joint model","volume":"57","author":"Liang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","first-page":"3069239","article-title":"Improved DEM reconstruction method based on multibaseline InSAR","volume":"19","author":"Zhang","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_39","unstructured":"Zhang, Q., Zhang, J., Yue, D.J., Zhao, C.Y., Gao, Y.P., Huang, G.W., and Qu, W. (2011). Advanced Theory and Application of Surveying Data, Surveying and Mapping Press. (In Chinese)."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1061\/(ASCE)SU.1943-5428.0000081","article-title":"Basic concepts of optimization and design of geodetic networks","volume":"138","author":"Asgari","year":"2012","journal-title":"J. Surv. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1109\/TGRS.2006.873207","article-title":"On the Extension of the Minimum Cost Flow Algorithm for Phase Unwrapping of Multitemporal Differential SAR Interferograms","volume":"44","author":"Pepe","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"112400","DOI":"10.1016\/j.rse.2021.112400","article-title":"InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California","volume":"258","author":"Kang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1767","DOI":"10.1007\/s10346-022-01860-4","article-title":"Two-dimensional deformation monitoring of karst landslides in Zongling, China, with multi-platform distributed scatterer InSAR technique","volume":"19","author":"Chen","year":"2022","journal-title":"Landslides"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"e2019GL086142","DOI":"10.1029\/2019GL086142","article-title":"Deformation of the Baige landslide, Tibet, China, revealed through the integration of cross-platform ALOS\/PALSAR-1 and ALOS\/PALSAR-2 SAR observations","volume":"47","author":"Liu","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"112253","DOI":"10.1016\/j.rse.2020.112253","article-title":"Displacement history and potential triggering factors of Baige landslides, China revealed by optical imagery time series","volume":"254","author":"Ding","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"105880","DOI":"10.1016\/j.enggeo.2020.105880","article-title":"Pre-and post-failure spatial-temporal deformation pattern of the Baige landslide retrieved from multiple radar and optical satellite images","volume":"279","author":"Xiong","year":"2020","journal-title":"Eng. Geol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.1109\/TGRS.2020.3003421","article-title":"Study of systematic bias in measuring surface deformation with SAR interferometry","volume":"59","author":"Ansari","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","first-page":"9100505","article-title":"Comments on \u201cStudy of Systematic Bias in Measuring Surface Deformation With SAR Interferometry\u201d","volume":"60","author":"Casu","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"113022","DOI":"10.1016\/j.rse.2022.113022","article-title":"Characterizing and correcting phase biases in short-term, multilooked interferograms","volume":"275","author":"Maghsoudi","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3216083","DOI":"10.1109\/TGRS.2022.3216083","article-title":"On the Phase Nonclosure of Multilook SAR Interferogram Triplets","volume":"60","author":"Falabella","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1109\/TGRS.2014.2336237","article-title":"Fast statistically homogeneous pixel selection for covariance matrix estimation for multitemporal InSAR","volume":"53","author":"Jiang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1165","DOI":"10.1111\/j.1365-246X.2007.03415.x","article-title":"Multi-interferogram method for measuring interseismic deformation: Denali Fault, Alaska","volume":"170","author":"Biggs","year":"2007","journal-title":"Geophys. J. Int."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1029\/97RG03139","article-title":"Radar interferometry and its application to changes in the Earth\u2019s surface","volume":"36","author":"Massonnet","year":"1998","journal-title":"Rev. Geophys."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2097\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:16:52Z","timestamp":1760123812000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2097"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,16]]},"references-count":53,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082097"],"URL":"https:\/\/doi.org\/10.3390\/rs15082097","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,16]]}}}