Monitoring of Surface and Water Levels of Inland Resources in Central Italy Using COSMO-SkyMed Imagery

Hydrological drought is one of the most severe consequences of climate change, leading to a reduction in available water resources. This study presents a workflow utilizing SAR data from COSMO-SkyMed STRIPMAP imagery to monitor water levels and surface extents as an alternative to traditional gauge stations. The methodology involves a radiometric algorithm to segment water surfaces by analyzing pixel backscatter differences [1]. Image quality was enhanced using histogram equalization and bilateral filtering, while classification techniques were employed to segment water, land, and border areas. The workflow was applied to Albano Lake in Italy as a first case study. Validation with manually digitized reference masks showed high accuracy, with F1 scores of 0.997 for Otsu’s method and 0.996 for k-means clustering. A stereo-SAR technique was employed for water level estimation, leveraging DATE software processes [2] and ascending and descending images acquired close in time. These images were first projected in ground range onto a plane at mean elevation. The actual elevation was then determined by iteratively refining it until the correlation between the images was maximized. Although validated on a single case study, the workflow demonstrates significant potential for broader application to diverse water bodies and SAR datasets.

This research is performed in the framework of the GRAW project, funded by the Italian Space Agency (ASI), Agreement n. 2023-1-HB.0, as part of the ASI’s program “Innovation for Downstream Preparation for Science” (I4DP_SCIENCE).

[1] Li, J.; Ma, R.; Cao, Z.; Xue, K.; Xiong, J.; Hu, M.; Feng, X. Satellite Detection of Surface Water Extent: A Review of Methodology. Water 2022, 14, 1148.

[2] Di Rita, M., Nascetti, A., & Crespi, M. (2017). Open-source tool for DSMs generation from high resolution optical satellite imagery: Development and testing of an OSSIM plug-in. International Journal of Remote Sensing, 38(7), 1788–1808.