Satellite radar interferometry (InSAR) has the capability of monitoring rails and embankments over wide areas. It has been demonstrated that the sub-centimeter-scale deformation of millions of InSAR measurements over railway infrastructure can be measured routinely using InSAR. Yet, to handle such huge data volumes and to recognize anomalies (such as localized differential deformation) in an efficient way, still limits the potential for operational use in wide areas, e.g. for monitoring a nation-wide railway network.

In this work, we develop and demonstrate a systematic InSAR methodology that can scrutinize data and automatically detect anomalies. The method is mainly based on statistical testing theory. Particularly, we use a ‘short arc’ method to focus on detecting localized differential deformation between two nearby InSAR measurement points over the railway. Our approach is applied to the entire railway network of the Netherlands, with a total route length of more than 3000 km. We used 210 Radarsat-2 descending data from three different tracks which were acquired between 2010 and 2015. A differential deformation and anomaly map are produced. This method will be further investigated for all railways in China.

This research is supported by the Young Research Scientists Support Program, in the framework of the Dragon cooperation 2013 – 2016 (Dragon 3).
Original languageEnglish
Number of pages1
Publication statusPublished - 2016
EventDragon 3 Final Results Symposium - Wuhan, China
Duration: 4 Jul 20166 Jul 2016
http://earth.esa.int/dragon-2016/

Conference

ConferenceDragon 3 Final Results Symposium
CountryChina
CityWuhan
Period4/07/166/07/16
Internet address

ID: 53750993