Performance analysis of recent SAR satellite missions for multi-temporal SAR interferometry.

Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, presence of atmospheric artifacts, and visibility problems related to the ground elevation. Nowadays, several satellite missions are available, providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit times. High-resolution X-Band SAR sensors, such as the COSMO-SkyMed constellation, acquire data with spatial resolution reaching metric values, and revisit time up to a few days, leading to an increase in the density of usable targets, as well as to an improved detection of non linear movements. Medium resolution C-band SAR data have been thoroughly exploited in the last two decades, thanks to the ERS-1/2 and ENVISAT-ASAR missions, and Radarsat-1/2. A new interesting opportunity is provided by the Sentinel-1 mission, which has a spatial resolution comparable to previous ESA C-band missions, and a revisit time reduced to 12 and 6 days, by considering, respectively, one or two satellites. It is envisioned that, by offering regular, global scale coverage, improved temporal resolution and freely available imagery, Sentinel-1 will guarantee an increasing use of MTI for ground displacement investigations. The present work discusses opportunities of MTI applications to ground instability monitoring by assessing the performance of the different available satellite missions, according to acquisition parameters such as wavelength, spatial resolution, revisit time and orbital tube size. This performance analysis allows to foresee the quality of displacement maps estimated through MTI according to mission characteristics, and thus to support SAR data selection. In particular, a comparative analysis is carried out, aimed at addressing specific advantages of different satellite missions in L-, C- and X-band. For instance, high resolution data increase the density of coherent targets, thus improving the monitoring of local scale events. Short (X-band) wavelengths improve the sensitivity to displacements. Short revisit times allow collecting large data stacks in short times, and improve the temporal sampling, thus increasing the chances to catch pre-failure signals (high-rate, nonlinear signals). The precision of the displacement rate detection depends on the number of images and on the phase noise, while the precision of the residual height error estimation depends also on the orbital tube size. Sentinel-1 will provide data for the next years with short revisit time, and it is thus likely to provide reliable displacement estimations at large scale, and in quite limited observation time spans. However, due to its narrow orbital tube size, it has a limited height precision, which leads to poor geo-location quality. An example of multi-sensor ground instability investigation is also presented concerning the site of Marina di Lesina, in Southern Italy, where several SAR datasets are available acquired from ERS, ENVISAT, Radarsat-2, COSMO-SkyMed and Sentinel-1, covering more than 20 years with varying ground resolutions, frequency bands and repeat times. The site is affected by sinkholes and uplifting caused by the interaction between the water coming from an artificial canal and the underground soil where gypsum with residual anhydride is present. The data at C-band and medium resolution from ERS and ENVISAT are able to catch the large scale uplift pattern, since the available observation time span is suitable to provide the required velocity precision. Radarsat-2 data improve the spatial density of detected targets, while, as foreseen by the model, Sentinel-1 improves the C-band performance, by providing, in a limited time span, precise estimation of the displacement rates. Finally, as expected, high resolution data from COSMO-SkyMed lead to a considerable increase of the PS spatial density, which allows to improve the delineation of the spatial deformation pattern. High resolution / short revisit time data are also very promising for detecting small precursory terrain movements related to the sinkholes.