Kanika Goel, N. Adam, R. Shau, Fernando Rodríguez González
{"title":"Improving the reference network in wide-area Persistent Scatterer Interferometry for non-urban areas","authors":"Kanika Goel, N. Adam, R. Shau, Fernando Rodríguez González","doi":"10.1109/IGARSS.2016.7729370","DOIUrl":null,"url":null,"abstract":"Advanced Interferometric SAR (InSAR) technique, namely, Persistent Scatterer Interferometry (PSI), allows long term deformation time series analysis with millimeter accuracy. Reference network arcs construction, arcs estimation and integration for PSs are an important step in PSI. In rural regions, low density of PSs leads to separate clusters during reference network construction. Also, in case of wide-area PSI using ERS-1/2 or Sentinel-1 data, the computational load can be very high. Due to this, the reference network processing is usually divided into overlapping blocks and merged later. This can however lead to spatial error propagation. This paper presents algorithms for improving the reference network in wide-area PSI, with a focus on non-urban areas.","PeriodicalId":179622,"journal":{"name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2016.7729370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Advanced Interferometric SAR (InSAR) technique, namely, Persistent Scatterer Interferometry (PSI), allows long term deformation time series analysis with millimeter accuracy. Reference network arcs construction, arcs estimation and integration for PSs are an important step in PSI. In rural regions, low density of PSs leads to separate clusters during reference network construction. Also, in case of wide-area PSI using ERS-1/2 or Sentinel-1 data, the computational load can be very high. Due to this, the reference network processing is usually divided into overlapping blocks and merged later. This can however lead to spatial error propagation. This paper presents algorithms for improving the reference network in wide-area PSI, with a focus on non-urban areas.