## 4 Discussion and Conclusion: Lessons Learned and Future Perspectives
Only long-term processes and well-established sources can deliver strong enough constrains to invert for actual deformation source geometries. Many past studies, at Piton de la Fournaise and other volcanoes worldwide, have shown that the timing of interferograms was crucial for modelling and understanding dynamic processes of subsurface magma storage and transport (e.g., examples described in Section 3.2.2). Eruption-spanning interferograms, for example, can only provide information on the overall shape of an intrusion, but not on the intrusion dynamics, i.e., the temporal progression during phases of fast subsurface magma migration [43]. We have described examples of magma ascent at Piton de la Fournaise that affect very shallow levels of the volcanic edifice (\(<\)2500 m depths) and that occur over the course of only a few hours to days (typically accompanied by a seismic crisis [38]). Therefore, even a daily SAR data sampling rate would not be sufficient to precisely constrain the dynamics of magma propagation from the (shallow) source to the surface. A (nearly) continuous interferometric data record during such highly dynamic phases of magma ascent (maybe provided by a geostationary SAR system) would probably take our understanding of shallow pre-eruptive magma propagation to a next level. However, already a daily data sampling during phases of unrest helps in detecting (maybe elastic or partially elastic) surface deformation that cannot be observed by any other means (as exemplified in Sections 3.2.1 and 3.2.2). Therefore, a key requirement for SAR interferometry to qualify for a near-real-time and fully operational volcano monitoring tool is a dense temporal SAR image acquisition rate in combination with very fast and efficient data and data product availability. We have illustrated examples observed at Piton de la Fournaise volcano that highlight the importance of dense temporal sampling for active volcano monitoring, while also various other scientific communities that are using InSAR for surface motion detection and monitoring would certainly benefit from higher temporal sampling rates (e.g., glaciology, as glaciers are moving very fast). Moving from repeat cycles of 35 days for the ENVISAT satellite to the new radar satellite generation with, for example, \(\sim\)6 days repetition cycle for S1, we are steadily progressing towards near-real-time and operational satellite-based surface deformation measurements. A great future potential of InSAR lies in the innovative utilization of SAR data collected by multiple, simultaneously operating sensors. For instance, different sensibilities and data resolutions allow for the detection and analysis of diverse processes or different features of the same process (e.g., high-resolution near-field vs. coarser-resolution far-field displacements associated with shallower and deeper processes that might be preceding the same eruption). Even if data acquired by different sensors cannot be combined to interferograms, numerical inversions can benefit from jointly using InSAR results derived from multiple sensor data as a variety of acquisition geometries and timings will provide better constraints on deformation source parameters. Future satellite systems will likely more and more work in constellations and/or support multisensor compatibilities in order to further improve temporal resolutions and to facilitate a more sophisticated definition of the 3D displacement components (EW, NS, UD). An overview of recently launched and already planned (near) future SAR satellite missions is given in Table 2.  
**Author Contributions:** Conceptualization, investigation, visualization, and writing--original draft preparation, N.R. ; data processing, visualization, and writing--review and editing, N.R. and J.-L.F. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the AGENCE NATIONAL DE LA REcherche (ANR); grant number ANR-16-CE04-004-01.