Satellite synthetic aperture radar (SAR) has established itself as a unique weather-independent remote sensing technology, capable of acquiring data day and night for monitoring tasks. With the increase in the number of SAR sensors, sustainability secured by follow-up missions, advances in SAR signal processing, and improved image quality, SAR has become a key remote sensing technology for society.

The use of radar remote sensing, particularly the interferometric SAR (InSAR) processing, enables the detection and observation of large-scale processes on the Earth’s surface and the determination of geometric changes in infrastructure. By integrating SAR data from different satellites and orbits, it is possible to derive and model spatial and temporal changes of various objects with high resolution, capturing weekly changes at a meter-scale spatial resolution with sub-centimeter accuracy.

As the importance of radar remote sensing in terms of continuous monitoring for geoscientific applications and in the field of structural health monitoring is increasing, the contributions from five outstanding working groups presented in this special issue highlight current research issues and developments in the field of monitoring with radar interferometry.

The article by Yu et al. deals with long-term surface deformation monitoring based on multitemporal radar interferometry. The study focuses on deformations observed in the coastal area of Liaohe Oilfield in China, which are attributed to prolonged oil production. Even et al. compare the quality of German and the European ground motion services for several test areas in Germany, each exhibiting different motion patterns. They validate the results with levelling and GNSS observations. The evaluation of tropospheric InSAR correction methods with insufficient correction models and data, using the example of north-west Iran, is the focus of the work by Kavehei et al. The study shows that a combination of low- and high-pass filters based only on phase measurements are better able to reduce the spatial phase variations in this case. The investigations by Chong et al. on the influence of image resolution, wavelength and land cover type on Persistent Scatterers (PS) contribute significantly to a better understanding of the density and quality of PS points and their accuracies for the results of deformation monitoring. The contribution by Luo et al. demonstrates the applicability of InSAR time-series analysis to identify kinematics of loess landslides in the Ili Valley of the western Tianshan Mountains. In the framework of this study a new inventory of creeping landslides that are highly responsive to seasonal rainfall with a time delay of less than one month is compiled.