{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T19:53:07Z","timestamp":1768593187653,"version":"3.49.0"},"reference-count":67,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,5,29]],"date-time":"2021-05-29T00:00:00Z","timestamp":1622246400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFC1505102 and 2018YFC1504805"],"award-info":[{"award-number":["2018YFC1505102 and 2018YFC1504805"]}]},{"name":"Natural Science Foundation of China","award":["41731066, 41874005 and 41929001"],"award-info":[{"award-number":["41731066, 41874005 and 41929001"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["300102269303 and 300102269719"],"award-info":[{"award-number":["300102269303 and 300102269719"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This work investigated the large-scale ground deformations threatening the Northern Urumqi district, China, which are connected to groundwater exploitation and the seasonal freeze\u2013thaw cycles that characterize this frozen region. Ground deformations can be well captured by satellite data using a multi-temporal interferometric synthetic aperture radar (Mt-InSAR) approach. The accuracy of the achievable ground deformation products (e.g., mean displacement time series and related ground displacement time series) critically depends on the number and quality of the selected interferograms. This paper presents a straightforward interferogram selection algorithm that can be applied to identify an optimal network of small baseline (SB) interferograms. The selected SB interferograms are then used to produce ground deformation products using the well-known small baseline subset (SBAS) Mt-InSAR algorithm. The developed interferogram selection algorithm (ISA) permits the selection of the group of SB data pairs that minimize the relative error of the mean ground deformation velocity. Experiments were carried out using a group of 102 Sentinel-1B SAR data collected from 12 April 2017 to 29 October 2020. This research study shows that the investigated farmland region is characterized by a maximum ground deformation rate of about 120 mm\/year. Periodic groundwater overexploitation, coupled with irrigation and freeze\u2013thaw phases, is also responsible for seasonal (one-year) ground displacement signals, with oscillation amplitudes up to 120 mm in the zones of maximum displacement.<\/jats:p>","DOI":"10.3390\/rs13112144","type":"journal-article","created":{"date-parts":[[2021,5,31]],"date-time":"2021-05-31T03:45:29Z","timestamp":1622432729000},"page":"2144","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Analysis of Groundwater Depletion\/Inflation and Freeze\u2013Thaw Cycles in the Northern Urumqi Region with the SBAS Technique and an Adjusted Network of Interferograms"],"prefix":"10.3390","volume":"13","author":[{"given":"Baohang","family":"Wang","sequence":"first","affiliation":[{"name":"School of Geology 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 Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7843-3565","authenticated-orcid":false,"given":"Antonio","family":"Pepe","sequence":"additional","affiliation":[{"name":"National Research Council of Italy, Institute for the Electromagnetic Sensing of the Environment (CNR-IREA), 80124 Napoli, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3299-3567","authenticated-orcid":false,"given":"Pietro","family":"Mastro","sequence":"additional","affiliation":[{"name":"School of Engineering, University of Basilicata, 85100 Potenza, Italy"}],"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 Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9181-1818","authenticated-orcid":false,"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\/0000-0001-6034-3062","authenticated-orcid":false,"given":"Wu","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengsheng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8988-8004","authenticated-orcid":false,"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geology Engineering and Geomatics, Chang\u2019an University, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1038\/364138a0","article-title":"The displacement field of the Landers earthquake mapped by radar interferometry","volume":"364","author":"Massonnet","year":"1993","journal-title":"Nature"},{"key":"ref_2","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_3","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1146\/annurev.earth.28.1.169","article-title":"Synthetic Aperture Radar Interferometry to Measure Earth\u2019s Surface Topography and Its Deformation","volume":"28","author":"Rosen","year":"2000","journal-title":"Annu. Rev. Earth Planet. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1109\/5.838084","article-title":"Synthetic aperture radar interferometry","volume":"88","author":"Rosen","year":"2002","journal-title":"Proc. IEEE"},{"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","unstructured":"Werner, C., Wegmuller, U., Strozzi, T., and Wiesmann, A. (2003, January 21\u201325). Interferometric point target analysis for deformation mapping. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Toulouse, France."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Hooper, A., Zebker, H., Segall, P., and Kampes, B. (2004). A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophys. Res. Lett., 31.","DOI":"10.1029\/2004GL021737"},{"key":"ref_8","unstructured":"Kampes, B. (2006). Radar Interferometry: Persistent Scatterer Technique, Springer."},{"key":"ref_9","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_10","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4788","DOI":"10.1109\/TGRS.2011.2167979","article-title":"The Stripmap\u2013ScanSAR SBAS Approach to Fill Gaps in Stripmap Deformation Time Series with ScanSAR Data","volume":"49","author":"Pepe","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1038\/nature04797","article-title":"Interseismic strain accumulation and the earthquake potential on the southern San Andreas fault system","volume":"441","author":"Fialko","year":"2006","journal-title":"Nature"},{"key":"ref_13","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_14","first-page":"1","article-title":"Adaptive Multilooking of Multitemporal Differential SAR Interferometric Data Stack Using Directional Statistics","volume":"99","author":"Pepe","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","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":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2016.2618766","article-title":"Modified Statistically Homogeneous Pixels\u2019 Selection with Multitemporal SAR Images","volume":"13","author":"Wang","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Shi, G., Ma, P., Lin, H., Huang, B., Zhang, B., and Liu, Y. (2020). Potential of Using Phase Correlation in Distributed Scatterer InSAR Applied to Build Scenarios. Remote Sens., 12.","DOI":"10.3390\/rs12040686"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1029\/2008GL034654","article-title":"A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches","volume":"35","author":"Hooper","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.isprsjprs.2015.10.003","article-title":"Time series analysis of InSAR data: Methods and trends","volume":"115","author":"Sunar","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Minh, D.H.T., 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_21","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.1080\/19475705.2019.1690058","article-title":"A Sentinel-1-based clustering analysis for geo-hazards mitigation at regional scale: A case study in Central Italy","volume":"10","author":"Montalti","year":"2019","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.earscirev.2019.03.009","article-title":"Monitoring volcano slope instability with Synthetic Aperture Radar: A review and new data from Pacaya (Guatemala) and Stromboli (Italy) volcanoes","volume":"192","author":"Schaefer","year":"2019","journal-title":"Earth Sci. Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.rse.2017.11.025","article-title":"Quantitative mapping of groundwater depletion at the water management scale using a combined GRACE\/InSAR approach","volume":"205","author":"Castellazzi","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_24","first-page":"F3","article-title":"InSAR measurements of surface deformation over permafrost on the North Slope of Alaska","volume":"115","author":"Liu","year":"2010","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3491","DOI":"10.1016\/j.rse.2011.08.012","article-title":"A comparison of TerraSAR-X, Radarsat-2 and ALOS-Palsar interferometry for monitoring permafrost environments, case study from Herschel Island, Canada","volume":"115","author":"Short","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1002\/2016GL070781","article-title":"Large-scale InSAR monitoring of permafrost freeze-thaw cycles on the Tibetan Plateau","volume":"44","author":"Daout","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1029\/2018JF004618","article-title":"Using Persistent Scatterer Interferometry to Map and Quantify Permafrost Thaw Subsidence: A Case Study of Eboling Mountain on the Qinghai-Tibet Plateau","volume":"123","author":"Chen","year":"2018","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/2150704X.2016.1225170","article-title":"Seasonal deformation features on Qinghai-Tibet railway observed using time-series InSAR technique with high-resolution TerraSAR-X images","volume":"8","author":"Wang","year":"2017","journal-title":"Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Dai, K., Liu, G., Li, Z., Ma, D., Wang, X., Zhang, B., Tang, J., and Li, G. (2018). Monitoring Highway Stability in Permafrost Regions with X-band Temporary Scatterers ing InSAR. Sensors, 18.","DOI":"10.3390\/s18061876"},{"key":"ref_30","first-page":"51","article-title":"Seasonal and multi-year surface displacements measured by DInSAR in a High Arctic permafrost environment","volume":"64","author":"Rudy","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Molan, Y.E., Kim, J.-W., Lu, Z., Wylie, B., and Zhu, Z. (2018). Modeling Wildfire-Induced Permafrost Deformation in an Alaskan Boreal Forest Using InSAR Observations. Remote Sens., 10.","DOI":"10.3390\/rs10030405"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wang, S., Xu, B., Shan, W., Shi, J., Li, Z., and Feng, G. (2019). Monitoring the Degradation of Island Permafrost Using Time-Series InSAR Technique: A Case Study of Heihe, China. Sensors, 19.","DOI":"10.3390\/s19061364"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Strozzi, T., Antonova, S., G\u00fcnther, F., M\u00e4tzler, E., Vieira, G., Wegm\u00fcller, U., Westermann, S., and Bartsch, A. (2018). Sentinel-1 SAR Interferometry for Surface Deformation Monitoring in Low-Land Permafrost Areas. Remote Sens., 10.","DOI":"10.3390\/rs10091360"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4403","DOI":"10.1109\/JSTARS.2018.2873219","article-title":"Active layer thickness retrieval of Qinghai-Tibet permafrost using the TerraSAR-X InSAR technique","volume":"11","author":"Wang","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"483","DOI":"10.5194\/tc-11-483-2017","article-title":"Active-layer thickness estimation from X-band SAR backscatter intensity","volume":"11","author":"Widhalm","year":"2017","journal-title":"Cryosphere"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"112007","DOI":"10.1016\/j.rse.2020.112007","article-title":"Active layer freeze-thaw and water storage dynamics in permafrost environments inferred from InSAR","volume":"248","author":"Chen","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_37","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_38","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TGRS.2011.2160644","article-title":"Repeat-Pass SAR Interferometry with Partially Coherent Targets","volume":"50","author":"Perissin","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_39","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-Filtering and Selection of Small Baseline Multi-Look DInSAR Interferograms","volume":"53","author":"Pepe","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","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_41","first-page":"1","article-title":"Adaptively Selecting Interferograms for SBAS-InSAR Based on Graph Theory and Turbulence Atmosphere","volume":"99","author":"Duan","year":"2020","journal-title":"IEEE Access"},{"key":"ref_42","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_43","doi-asserted-by":"crossref","unstructured":"Zhao, B.C., Wang, Q.B., Zhang, Q., and Zhu, W.Q. (2017). Batch filtering of multi-baseline SAR interferograms. 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), IEEE.","DOI":"10.1109\/BIGSARDATA.2017.8124922"},{"key":"ref_44","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_45","unstructured":"Vaccaro, R., and Kot, A. (1987, January 6\u20139). A Perturbation Theory for the Analysis of SVD-Based Algorithms. Proceedings of the ICASSP \u201987 IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas, TX, USA."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/0024-3795(89)90598-3","article-title":"The perturbation of consistent least squares problems","volume":"112","author":"Wei","year":"1989","journal-title":"Linear Algebra Appl."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Demmel, J.W. (1997). Applied Numerical Linear Algebra, SIAM.","DOI":"10.1137\/1.9781611971446"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0266-5611\/14\/4\/001","article-title":"Synthetic aperture radar interferometry","volume":"14","author":"Bamler","year":"1998","journal-title":"Inverse Probl."},{"key":"ref_49","unstructured":"(2021, May 05). Climatic characteristics, Available online: http:\/\/www.urumqi.gov.cn\/zjsf2\/zrdl\/185.htm."},{"key":"ref_50","first-page":"40","article-title":"Discussion on Xinjiang water utilization and agricultural sustainable development","volume":"1","author":"Aziguli","year":"2007","journal-title":"Gansu Nongye"},{"key":"ref_51","first-page":"316","article-title":"Analysis of the spatiotemporal features of land use and land degradation in the northern pied-mont area of the Tianshan Mountain","volume":"21","author":"Xu","year":"2014","journal-title":"Res. Soil Water Conserv."},{"key":"ref_52","first-page":"240","article-title":"Spatial distribution of agricultural production from perspective of water footprint: A case study of north-piedmont major agriculture production regions of Tianshan Mountains, Xinjiang","volume":"38","author":"Chen","year":"2021","journal-title":"J. Univ. Chin. Acad. Sci."},{"key":"ref_53","first-page":"242","article-title":"Spatiotemporal variations and driving forces of agricultural water consumption in Xinjiang during 1988\u20142015: Based on statistical analysis of crop water footprint","volume":"43","author":"Zhang","year":"2021","journal-title":"J. Glaciol. Geocryol."},{"key":"ref_54","unstructured":"(2021, May 05). StaMPS. Available online: http:\/\/homepages.see.leeds.ac.uk\/~earahoo\/stamps\/."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2737","DOI":"10.1364\/JOSAA.24.002737","article-title":"Phase unwrapping in three dimensions with application to InSAR time series","volume":"24","author":"Hooper","year":"2007","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1007\/s00024-011-0403-2","article-title":"A Quantitative Assessment of DInSAR Measurements of Interseismic Deformation: The Southern San Andreas Fault Case Study","volume":"169","author":"Manzo","year":"2012","journal-title":"Pure Appl. Geophys. PAGEOPH"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2193","DOI":"10.1002\/2017GL076336","article-title":"The 21 August 2017 Ischia (Italy) Earthquake Source Model Inferred from Seismological, GPS, and DInSAR Measurements","volume":"45","author":"Carlino","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"L20311","DOI":"10.1029\/2012GL053683","article-title":"How do volcanic rift zones relate to flank instability? Evidence from collapsing rifts at Etna","volume":"39","author":"Ruch","year":"2012","journal-title":"Geophys. Res. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2717","DOI":"10.1109\/TIM.2016.2600998","article-title":"Efficient Implementation of Least Squares Sine Fitting Algorithms","volume":"65","author":"Renczes","year":"2016","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"8970","DOI":"10.1002\/2016JB013765","article-title":"Application of independent component analysis to multitemporal InSAR data with volcanic case studies","volume":"121","author":"Ebmeier","year":"2016","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1878","DOI":"10.1002\/2017GL075950","article-title":"Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation from Independent Component Analysis of InSAR Time Series","volume":"45","author":"Chaussard","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1029\/2018JB016210","article-title":"Blind Signal Separation Methods for InSAR: The Potential to Automatically Detect and Monitor Signals of Volcanic Deformation","volume":"123","author":"Gaddes","year":"2018","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"10800","DOI":"10.1029\/2019GL084418","article-title":"A New Method for Isolating Elastic from Inelastic Deformation in Aquifer Systems: Application to the San Joaquin Valley, CA","volume":"46","author":"Chaussard","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_64","unstructured":"(2021, May 05). Historical weather in Urumqi. Available online: http:\/\/lishi.tianqi.com\/wulumuqi\/index.html."},{"key":"ref_65","unstructured":"(2021, May 05). Global Precipitation Measurements, Available online: https:\/\/gpm.nasa.gov\/data\/directory."},{"key":"ref_66","first-page":"1234","article-title":"The characteristics and evolution of surface deformation induced by agricultural irrigation in the Junggar Basin from the perspective of InSAR","volume":"24","author":"Wang","year":"2020","journal-title":"J. Remote Sens."},{"key":"ref_67","first-page":"751","article-title":"Study on Dynamic Change of Groundwater Depth in a Newly Reclaimed Oasis in Northwestern Marginal Zone of the Junggar Basin","volume":"28","author":"Lei","year":"2011","journal-title":"Arid Zone Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/11\/2144\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:08:56Z","timestamp":1760162936000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/11\/2144"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,29]]},"references-count":67,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["rs13112144"],"URL":"https:\/\/doi.org\/10.3390\/rs13112144","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,29]]}}}