**5. Conclusions**

Managing former industrial lands is essential for urban planning and limiting the urbanization of new lands. In this article, we presented SARSAR, a new Earth observation service that has been developed to support the Walloon authorities' daily work by helping them update the RDS inventory in a more responsive, efficient and cost-effective manner.

The SARSAR service exploits Sentinel-1 and Sentinel-2 images, with their high spatial and temporal resolution and open data policy, and the cloud computing environment offered by Terrascope to generate and deliver a change report every two months directly to the Walloon authorities, who can integrate it into their managemen<sup>t</sup> system. This saves time and effort compared to the current methods of updating the inventory (visual analysis of orthophotos and systematic field visits), enabling personnel to prioritize their work and focus on the RDSs showing evidence of significant changes. This service, which first performs a set of routines to extract and prepare the input data, is composed of two main processes: one for the flagging of the sites that are likely to have changed and one in charge of the classification of the changes.

The performance assessment provided satisfactory results, with an overall accuracy of around 80% for the change detection and in the range 70–90% for the change classification (depending on the class considered). The results highlight the relevance of using Sentinel-1 data, as well as a selection of Sentinel-2 indices, especially the NDVI for vegetation monitoring, and show the complementarity of the two processes in identifying both abrupt and gradual changes.

The results presented in this paper highlight opportunities not only for brownfield monitoring in other regions but also for multiple application domains and a larger user community, from land managemen<sup>t</sup> and planning strategies, to agricultural and forestry areas monitoring, through disaster response mapping.

**Author Contributions:** Conceptualization, S.P., M.S., X.N. and E.H.; methodology, S.P., M.S., C.W., G.S., X.N. and E.H.; software, M.S., C.W. and G.S.; validation, S.P. and M.S.; formal analysis, S.P. and M.S.; investigation, S.P. and M.S.; resources; data curation, S.P., M.S., C.W. and G.S.; writing—original draft preparation, S.P.; writing—review and editing, S.P., M.S., C.W. and E.H.; visualization, S.P. and M.S.; supervision, X.N. and E.H.; project administration, S.P., M.S., X.N. and E.H.; funding acquisition, M.S., X.N. and E.H. All authors have read and agreed to the published version of the manuscript.

**Funding:** The research presented in this paper is funded by BELSPO (Belgian Science Policy Office) in the frame of the STEREO III programme—project SR/00/372.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors would like to thank the European Union's Earth Observation Programme Copernicus and VITO for the provision of the Sentinel images through Terrascope and for the virtual research environments. The authors would like to thank Airbus and BELSPO for the provision of the Pléiades images, and the Service Public de Wallonie for the orthophotos. The authors would also like to thank BELSPO and their STEREO program (Support To Exploitation and Research in Earth Observation). Finally, the authors would like to thank the members of the Remote sensing and geodata unit (ISSeP), in particular Odile Close and Benjamin Beaumont, for their support and paper review.

**Conflicts of Interest:** The authors declare no conflict of interest.
