{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T01:14:13Z","timestamp":1770340453420,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2014,4,15]],"date-time":"2014-04-15T00:00:00Z","timestamp":1397520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Point-like targets are useful in providing surface deformation with the time series of synthetic aperture radar (SAR) images using the multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology. However, the spatial density of point-like targets is low, especially in non-urban areas. In this paper, a hierarchical MTInSAR method is proposed to increase the spatial density of deformation measurements by tracking both the point-like targets and the distributed targets with the temporal steadiness of radar backscattering. To efficiently reduce error propagation, the deformation rates on point-like targets with lower amplitude dispersion index values are first estimated using a least squared estimator and a region growing method. Afterwards, the distributed targets are identified using the amplitude dispersion index and a Pearson correlation coefficient through a multi-level processing strategy. Meanwhile, the deformation rates on distributed targets are estimated during the multi-level processing. The proposed MTInSAR method has been tested for subsidence detection over a suburban area located in Tianjin, China using 40 high-resolution TerraSAR-X images acquired between 2009 and 2010, and validated using the ground-based leveling measurements. The experiment results indicate that the spatial density of deformation measurements can be increased by about 250% and that subsidence accuracy can reach to the millimeter level by using the hierarchical MTInSAR method.<\/jats:p>","DOI":"10.3390\/rs6043349","type":"journal-article","created":{"date-parts":[[2014,4,15]],"date-time":"2014-04-15T13:23:16Z","timestamp":1397568196000},"page":"3349-3368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Hierarchical Multi-Temporal InSAR Method for Increasing the Spatial Density of Deformation Measurements"],"prefix":"10.3390","volume":"6","author":[{"given":"Tao","family":"Li","sequence":"first","affiliation":[{"name":"Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China"}]},{"given":"Guoxiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China"}]},{"given":"Hui","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Space and Earth Information Science, The Chinese University of Hong Kong,  Hong Kong 999077, China"}]},{"given":"Hongguo","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China"}]},{"given":"Bing","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Geospatial Information Engineering, Southwest Jiaotong University, Chengdu 610031, China"}]},{"given":"Qingli","family":"Luo","sequence":"additional","affiliation":[{"name":"Center of Remote Sensing, Tianjin University, Tianjin 300100, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,4,15]]},"reference":[{"key":"ref_1","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. 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