dc.contributor.author | Shamshiri, Roghayeh | |
dc.contributor.author | Nahavandchi, Hossein | |
dc.contributor.author | Motagh, Mahdi | |
dc.contributor.author | Andy, Hooper | |
dc.date.accessioned | 2018-07-12T08:56:27Z | |
dc.date.available | 2018-07-12T08:56:27Z | |
dc.date.created | 2018-05-23T15:06:55Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Remote Sensing. 2018, 10 (5), . | nb_NO |
dc.identifier.issn | 2072-4292 | |
dc.identifier.uri | http://hdl.handle.net/11250/2505210 | |
dc.description.abstract | Combining persistent scatterers (PS) and distributed scatterers (DS) is important for effective displacement monitoring using time-series of SAR data. However, for large stacks of synthetic aperture radar (SAR) data, the DS analysis using existing algorithms becomes a time-consuming process. Moreover, the whole procedure of DS selection should be repeated as soon as a new SAR acquisition is made, which is challenging considering the short repeat-observation of missions such as Sentinel-1. SqueeSAR is an approach for extracting signals from DS, which first applies a spatiotemporal filter on images and optimizes DS, then incorporates information from both optimized DS and PS points into interferometric SAR (InSAR) time-series analysis. In this study, we followed SqueeSAR and implemented a new approach for DS analysis using two-sample t-test to efficiently identify neighboring pixels with similar behaviour. We evaluated the performance of our approach on 50 Sentinel-1 images acquired over Trondheim in Norway between January 2015 and December 2016. A cross check on the number of the identified neighboring pixels using the Kolmogorov–Smirnov (KS) test, which is employed in the SqueeSAR approach, and the t-test shows that their results are strongly correlated. However, in comparison to KS-test, the t-test is less computationally intensive (98% faster). Moreover, the results obtained by applying the tests under different SAR stack sizes from 40 to 10 show that the t-test is less sensitive to the number of images. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | MDPI | nb_NO |
dc.relation.uri | http://www.mdpi.com/2072-4292/10/5/794/htm | |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS) | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.source.pagenumber | 14 | nb_NO |
dc.source.volume | 10 | nb_NO |
dc.source.journal | Remote Sensing | nb_NO |
dc.source.issue | 5 | nb_NO |
dc.identifier.doi | 10.3390/rs10050794 | |
dc.identifier.cristin | 1586274 | |
dc.description.localcode | (c) 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | nb_NO |
cristin.unitcode | 194,64,91,0 | |
cristin.unitname | Institutt for bygg- og miljøteknikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |