scholarly journals Water Level measurement using COSMO-SkyMed Synthetic Aperture Radar

2020 ◽  
Author(s):  
Filippo Biondi ◽  
Angelica Tarpanelli ◽  
Pia Addabbo ◽  
Carmine Clemente ◽  
Danilo Orlando
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Synthetic Aperture ◽  
Level Measurement ◽  
Aperture Radar

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

2014 ◽  
Vol 150 ◽  
pp. 66-81 ◽  
Author(s):  
Jin-Woo Kim ◽  
Zhong Lu ◽  
John W. Jones ◽  
C.K. Shum ◽  
Hyongki Lee ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Freshwater Marsh ◽  
Synthetic Aperture ◽  
Radar Backscatter ◽  
L Band ◽  
Aperture Radar

scholarly journals Long-Term Water Surface Area Monitoring and Derived Water Level Using Synthetic Aperture Radar (SAR) at Altevatn, a Medium-Sized Arctic Lake

2019 ◽  
Vol 11 (23) ◽  
pp. 2780 ◽  
Author(s):  
Hannah Vickers ◽  
Eirik Malnes ◽  
Kjell-Arild Høgda
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Lake Water ◽  
Clustering Algorithm ◽  
Independent Solution ◽  
Microwave Remote Sensing ◽  
Synthetic Aperture ◽  
Arctic Lake ◽  
Water Cover ◽  
Aperture Radar

Monitoring water storage in lakes and reservoirs is critical to water resource management, especially in a changing climate. Satellite microwave remote sensing offers a weather and light-independent solution for mapping water cover over large scales. We have used 13 years of synthetic aperture radar (SAR) data from three different sensors (Sentinel-1, RADARSAT-2, and Envisat advanced synthetic aperture radar (ASAR)) to develop a method for mapping surface water cover and thereby estimating the lake water extent (LWE). The method uses the unsupervised K-means clustering algorithm together with specific post-processing techniques to create binary maps of the water area. We have specifically tested and validated the method at Altevatn, a medium-sized arctic lake in Northern Norway, by using in-situ measurements of the water level. The multi-sensor SAR LWE time series were used in conjunction with the water level measurements to derive the lake hypsometry while at the same time quantifying the accuracy of our method. For Altevatn lake we estimated LWE with a root mean squared error (RMSE) of 0.89 km2 or 1.4% of the mean LWE, while the inferred lake water level (LWL) was associated with an RMSE of 0.40 m, or 2.5% of the maximum annual variation. We foresee that there is potential to further develop the algorithm by generalizing its use to other lakes worldwide and automating the process such that near real-time monitoring of LWE may be possible.

scholarly journals Evaluation of the Performances of Radar and Lidar Altimetry Missions for Water Level Retrievals in Mountainous Environment: The Case of the Swiss Lakes

2021 ◽  
Vol 13 (11) ◽  
pp. 2196
Author(s):  
Frédéric Frappart ◽  
Fabien Blarel ◽  
Ibrahim Fayad ◽  
Muriel Bergé-Nguyen ◽  
Jean-François Crétaux ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Open Loop ◽  
Water Levels ◽  
Synthetic Aperture ◽  
Low Resolution ◽  
Radar Altimetry ◽  
Constant Bias ◽  
Aperture Radar

Radar altimetry is now commonly used to provide long-term monitoring of inland water levels in complement to or for replacing disappearing in situ networks of gauge stations. Recent improvements in tracking and acquisition modes improved the quality the water retrievals. The newly implemented Open Loop mode is likely to increase the number of monitored water bodies owing to the use of an a priori elevation, especially in hilly and mountainous areas. The novelty of this study is to provide a comprehensive evaluation of the performances of the past and current radar altimetry missions according to their acquisition (Low Resolution Mode or Synthetic Aperture Radar) and tracking (close or open loop) modes, and acquisition frequency (Ku or Ka) in a mountainous area where tracking losses of the signal are likely to occur, as well as of the recently launched ICESat-2 and GEDI lidar missions. To do so, we evaluate the quality of water level retrievals from most radar altimetry missions launched after 1995 over eight lakes in Switzerland, using the recently developed ALtimetry Time Series software, to compare the performances of the new tracking and acquisition modes and also the impact of the frequency used. The combination of the Open Loop tracking mode with the Synthetic Aperture Radar acquisition mode on SENTINEL-3A and B missions outperforms the classical Low Resolution Mode of the other missions with a lake observability greater than 95%, an almost constant bias of (−0.17 ± 0.04) m, a RMSE generally lower than 0.07 m and a R most of the times higher than 0.85 when compared to in situ gauge records. To increase the number of lakes that can be monitored and the temporal sampling of the water level retrievals, data acquired by lidar altimetry missions were also considered. Very accurate results were also obtained with ICESat-2 data with RMSE lower than 0.06 and R higher than 0.95 when compared to in situ water levels. An almost constant bias (0.42 ± 0.03) m was also observed. More contrasted results were obtained using GEDI. As these data were available on a shorter time period, more analyses are necessary to determine their potential for retrieving water levels.

scholarly journals Pixel Tracking to Estimate Rivers Water Flow Elevation Using Cosmo-SkyMed Synthetic Aperture Radar Data

2019 ◽  
Vol 11 (21) ◽  
pp. 2574 ◽  
Author(s):  
Filippo Biondi ◽  
Angelica Tarpanelli ◽  
Pia Addabbo ◽  
Carmine Clemente ◽  
Danilo Orlando
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Water Flow ◽  
River Flow ◽  
Processing Technique ◽  
Synthetic Aperture ◽  
Signal Processing Technique ◽  
Synthetic Aperture Radar Data ◽  
Flow Monitoring ◽  
Aperture Radar

The lack of availability of historical and reliable river water level information is an issue that can be overcome through the exploitation of modern satellite remote sensing systems. This research has the objective of contributing in solving the information-gap problem of river flow monitoring through a synthetic aperture radar (SAR) signal processing technique that has the capability to perform water flow elevation estimation. This paper proposes the application of a new method for the design of a robust procedure to track over the time double-bounce reflections from bridges crossing rivers to measure the gap space existing between the river surface and bridges. Specifically, the difference in position between the single and double bounce is suitably measured over the time. Simulated and satellite temporal series of SAR data from COSMO-SkyMed data are compared to the ground measurements recorded for three gauges sites over the Po and Tiber Rivers, Italy. The obtained performance indices confirm the effectiveness of the method in the estimation of water level also in narrow or ungauged rivers.

scholarly journals A Pathway to the Automated Global Assessment of Water Level in Reservoirs with Synthetic Aperture Radar (SAR)

2020 ◽  
Vol 12 (8) ◽  
pp. 1353 ◽  
Author(s):  
Edward Park ◽  
Eder Merino ◽  
Quinn W. Lewis ◽  
Eric O. Lindsey ◽  
Xiankun Yang
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Radar Data ◽  
Water Levels ◽  
Synthetic Aperture ◽  
Reservoir Water ◽  
Synthetic Aperture Radar Data ◽  
Wide Range ◽  
Elevation Model ◽  
Aperture Radar

Global measurements of reservoir water levels are crucial for understanding Earth’s hydrological dynamics, especially in the context of global industrialization and climate change. Although radar altimetry has been used to measure the water level of some reservoirs with high accuracy, it is not yet feasible unless the water body is sufficiently large or directly located at the satellite’s nadir. This study proposes a gauging method applicable to a wide range of reservoirs using Sentinel–1 Synthetic Aperture Radar data and a digital elevation model (DEM). The method is straightforward to implement and involves estimating the mean slope–corrected elevation of points along the reservoir shoreline. We test the model on six case studies and show that the estimated water levels are accurate to around 10% error on average of independently verified values. This study represents a substantial step toward the global gauging of lakes and reservoirs of all sizes and in any location where a DEM is available.

scholarly journals Ground Deformation Analysis Using InSAR and Backpropagation Prediction with Influencing Factors in Erhai Region, China

2019 ◽  
Vol 11 (10) ◽  
pp. 2853 ◽  
Author(s):  
Yuyi Wang ◽  
Yahui Guo ◽  
Shunqiang Hu ◽  
Yong Li ◽  
Jingzhe Wang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Influencing Factors ◽  
Ground Deformation ◽  
Synthetic Aperture ◽  
Continuous Increase ◽  
Building Area ◽  
Mean Square Errors ◽  
Cumulative Precipitation ◽  
Aperture Radar

The long continuity of Interferometric Synthetic Aperture Radar (InSAR) can provide high space and resolution data for ground deformation investigations. The ground deformation in this paper appeared in the city’s development, although it is close to the Erhai region, which is different from a water-deficient city. Therefore, the analysis and prediction of ground deformation using a new method is required. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) images from 2015 to 2018 were used to study the characteristics of ground deformation in the Erhai region using the Small Baseline Subset Interferometric SAR (SBAS-InSAR) technique. The results were cross-validated using ascending and descending direction images to ensure the accuracy. In addition, the results showed that there was little ground deformation in the northern part of the Erhai region, while there was obvious ground deformation in the southern part. Four influencing factors—including the building area, water level, cumulative precipitation, and cumulative temperature of the southern Erhai region—were used together to predict the cumulative ground deformation using back-propagation (BP). The R of all the involved data was 0.966, and the root mean square errors (RMSEs) between the simulated values using BP and the true measured values were 3.063, 1.003, and 1.119, respectively. The results showed that BP has great potential in predicting the change tendency of ground deformation with high precision. The main reason for ground deformation is the continuous increase of building area; the water level followed. The cumulative precipitation and cumulative temperature are the reasons for the seasonal ground deformation. Some countermeasures and suggestions are given to face the challenge of serious ground deformation.

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