Abstract
In this article, a two-year time-series of multipolarization Sentinel-1 synthetic aperture radar (SAR) imagery is exploited to analyze the changes in the water-covered area of the Monte Cotugno (Italy) reservoir. A two-step processing chain, which includes water/land separation and waterline extraction, is proposed to accomplish this task. Experimental results, verified using independent in situ measurements, demonstrate that: first, Sentinel-1 time series can be successfully used to support the smart water management of reservoirs. In fact, the changes in the water-covered area inferred from the SAR time series agree with the seasonal behavior and they also fit anomalies; and second, multipolarization feature outperforms single-polarization ones in terms of accuracy of the extracted waterline profile.
Highlights
S MART water management (SWM) consists of using Information and Communication Technology (ICT) tools to provide automatic real-time information to assist the planning and the development of regional and/or national strategies for the management of water resources
The methodology proposed to extract waterline from synthetic aperture radar (SAR) scenes is contrasted with state-of-the-art methods and the water-area estimations are verified using independent in situ information on the Monte Cotugno reservoir available from its SWM system
Experimental results show that the DP approach outperforms SP one and the state-of-the-art method and the water area estimations well fit in situ observations being able to follow both seasonal trends and anomalies
Summary
S MART water management (SWM) consists of using Information and Communication Technology (ICT) tools to provide automatic real-time information to assist the planning and the development of regional and/or national strategies for the management of water resources. A key parameter when dealing with the real-time monitoring and management of water bodies is the extent of the water-covered area [2] The analysis of time series of satellite-based measurements can provide cost-effective and reliable information for the management of water reservoirs. A processing chain is developed to extract the waterline and estimate the extent of the water-covered area extent from dual-polarization VV-VH (vertical transmit and receive–vertical transmit and horizontal receive) Sentinel-1 SAR measurements in an unsupervised way. The methodology proposed to extract waterline from SAR scenes is contrasted with state-of-the-art methods and the water-area estimations are verified using independent in situ information on the Monte Cotugno reservoir available from its SWM system.
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