Many areas in the world are susceptible to sinkholes and the associated risk of a sudden collapse of the surface. About 13% of the world’s land surface is covered by carbonate rocks which are sensitive to erosion by running water, leading to cavities and potentially sinkholes. In urban areas, sinkhole risks are a direct threat to human lives. Detecting sinkholes is notoriously difficult, as techniques such as ground-penetrating radar (GPR), electrical resistivity tomography (ERT), seismic methods, and microgravity, usually have a very localized range, and are difficult to deploy between buildings. Yet, recently it has been demonstrated that the detection of small depressions using radar interferometry can be indicative for imminent sinkhole collapse site identification. In an earlier study, we have demonstrated that a sinkhole occurring in the south of the Netherlands appeared to be observable as gradual deformation years before the actual collapse. Building on this experience, we designed a warning system to detect locations where the spatio-temporal behavior of the surface, or objects on the surface, has the characteristic fingerprint of a subsurface cavity, or an imminent sinkhole. We apply a robust method of hypothesis testing based on time series of TerraSAR-X and Radarsat-2 SAR data. We report on the characteristics of the method, the ways to deal with false alarms, and the potential for operational deployment.
|Number of pages||1|
|Publication status||Published - 2015|
|Event||Mapping Urban Areas from Space - ESA – ESRIN, Frascati, Italy|
Duration: 4 Nov 2015 → 5 Nov 2015
|Conference||Mapping Urban Areas from Space|
|Abbreviated title||MUAS 2015|
|Period||4/11/15 → 5/11/15|