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Ensuring the safety and operational efficiency of hydraulic infrastructures is paramount, considering the widespread consequences that damages can inflict on people, communities, and the environment. To mitigate risks and prevent significant losses, continuous surveillance is vital. While some damages might appear minor, they can jeopardize the complete operational reliability of dams, leading to substantial economic losses, especially in energy production and related activities. The rapid growth in 20th-century infrastructure development globally has made security monitoring a necessity for numerous civil structures. Rigorous inspection programs, particularly for reservoir dams, are essential for safeguarding citizens and their properties. However, individually monitoring each dam is often impractical due to the associated costs and time constraints, potentially posing safety risks. Fortunately, satellite-based differential radar interferometry (DInSAR) offers an effective and cost-efficient remote sensing solution. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques, particularly utilizing Persistent Scatterers, have proven successful in monitoring various infrastructures, natural phenomena, and geological activities. MT-InSAR provides precise measurements without the need for fieldwork, utilizing historical SAR image archives dating back to the 1990s. Technological advancements, such as the Sentinel-1 C-band with a six-day revisit time until the end of 2021, have enhanced monitoring capabilities. Additionally, commercial radar images in the X-band and the development of multi-interferometric InSAR techniques have opened new avenues for monitoring. This study showcases the adaptation and application of MT-InSAR for monitoring dams and large ponds constructed with loose materials. By assessing vertical displacements and consolidation rates, the technique identifies potential issues, aiding in further field investigations. Case studies involving dams and large reservoirs in Andalusia illustrate the effectiveness of satellite radar interferometry in monitoring their structural stability from space as a routine practice. [ABSTRACT FROM AUTHOR]

[Display omitted] • UAV data accurately predicted SOC concentrations (RMSE < 2.44 %) • Radar data characterized spatial patterns of flood frequency in coastal areas. • The effect of flood frequency on SOC was highest at pioneer and seaward communities. • AGB showed a larger explanatory power than flood frequency in SOC predictions. • UAV-SAR fusion unveils site-specific fine-scale patterns of SOC in coastal meadows. Coastal wetlands are considered important stores of blue carbon, containing some of the largest stores of pedologic and biotic carbon per unit area on the planet. These ecosystems are however highly sensitive to Climate Change and changes in the management practices. It is of utmost importance to address relevant ecosystem scales in order to fully understand carbon dynamics in coastal wetlands. In this regard, Unoccupied Aerial Vehicles (UAVs) can provide spatial scales detailed enough to address the fine scale patters of topsoil organic carbon accumulation in coastal wetlands. This study demonstrates the use of multispectral and photogrammetric data derived from UAVs to accurately map plant communities and topsoil organic carbon concentration in coastal wetlands. The overall accuracies from the classification of plant communities ranged from 88% to 97% whereas RMSE for topsoil organic carbon concentration ranged from 2.44% to 0.74%. By combining both models, site-specific variations in topsoil carbon concentrations among plant communities were unveiled. Open pioneer communities consistently showed the lowest topsoil organic carbon concentration, while the concentrations vary considerably across plant communities characterized by denser vegetation coverage. Furthermore, Sentinel-1 radar data was used to assess the spatial patterns of flood frequency. GAMs were used to combine flood frequency with the plant communities and topsoil organic carbon models, as well as an aboveground biomass (AGB) model from a previous study. GAMs revealed a stronger effect than flood frequency on topsoil organic carbon. Regarding flooding, increased flood frequency generally led decreased topsoil organic concentrations across communities and sites. However, the relative contribution of flood frequency to topsoil organic carbon concentration in Baltic coastal wetlands depends strongly on the location of the wetland and the nature of the floods. Higher flood frequencies could lead to increased topsoil organic carbon in wetlands subject to the input of estuarine sediments. Lastly, the integration of remote sensing platforms constitutes an effective tool for revealing spatial heterogeneity of carbon storage in coastal wetlands. [ABSTRACT FROM AUTHOR]