Monitoring Lake Ice in Northern Alaska with Backscattering and Interferometric Approaches Using Sentinel-1 Sar Data

Wakabayashi, Hiroyuki; Motohashi, Kazushige; Maezawa, Naotake

doi:10.1109/igarss.2019.8900371

Cited by 4 publications

(1 citation statement)

References 5 publications

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“…Mangilli et al [17] propose a novel retracking approach to extract lake ice thickness from Ku-band radar altimetric data with acceptable accuracy. Differential Interferometric SAR (D-InSAR) has also been investigated for the analysis of lake ice thickness (e.g., [18]) but it has not been widely used. Recently, Siles et al [7] used this technique to estimate lake ice thickness changes and deformation, showing its potential for supporting freshwater ice studies.…”

Section: Introductionmentioning

confidence: 99%

Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study

Siles

Leconte

2023

Hydrology

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Reservoir ice can have an important impact on the watershed scale and influence hydraulic operations. On the other hand, hydropower generation can also impact the ice regime. In this study, multi-source satellite and ERA5-land data are used to evaluate ice conditions. Specifically, ice-controlling variables (temperature, water levels), ice regime (cover/deformation, thickness) and their interrelations are assessed for a 5-year period from 2017 to 2021. The methodology is applied to the Manicouagan reservoir, one of the largest hydropower reservoirs in Quebec, Canada. The satellite-based land surface temperatures (LSTs) suggest that winter 2021 was the hottest one. Overall, MODIS and Landsat LSTs agree with the ERA5-land temperatures. Ice backscatter from Sentinel-1 indicates that, in general, the reservoir is completely covered by ice from January to March. A correlation of 0.6 and 0.8 is observed between C- and Ku-band Synthetic Aperture Radar (SAR) signal and ice thickness, respectively. Important ice changes inferred from Differential Interferometric SAR (D-InSAR) occur approximately at the position where the largest ERA5-land ice thickness differences are observed. Winter water levels are also evaluated using satellite altimetric data to verify their influence on the ice dynamics. They show a decreasing tendency as the winter advances.

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Section: Introductionmentioning

confidence: 99%

Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study

Siles

Leconte

2023

Hydrology

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Retrieval of Lake Ice Characteristics from SAR Imagery

Siles

Leconte

Peters

2022

Canadian Journal of Remote Sensing

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Comparison of Lake Ice Extraction Methods Based on MODIS Images

et al. 2022

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As an important part of the cryosphere, lake ice is a sensitive indicator of climate change. Remote sensing technology can quickly and accurately monitor the process of its formation and decay, among which Moderate Resolution Imaging Spectroradiometer (MODIS) images are the most widely used data in the remote sensing monitoring of lake ice. The reasonable selection of monitoring methods is of great significance to grasp the dynamic process and response to climate change of lake ice. In this study, five commonly used remote sensing monitoring methods of lake ice based on MODIS MOD09GA data, including the single band threshold method (SBT), reflectance difference threshold method (RDT), normalized difference snow index method (NDSI), modified normalized difference snow index method (MNDSI) and lake ice index method (LII), were selected to compare their accuracies in extracting lake ice extent by combining them with four evaluation metrics of accuracy, precision, recall and mean intersection over union (MIoU). In addition, the ability of the high-precision LII method for extracting long time series lake ice phenology and its applicability to multiple types of lakes were verified. The results showed that compared with the NDSI method, the other four methods more easily distinguished between lake ice and lake water by setting thresholds. The SBT method and the RDT method had better extraction effects in the freezing process and the melting process, respectively. Compared with the NDSI and MNDSI methods, the LII method showed a significant improvement in lake ice extraction over the entire freeze–thaw cycle, with the smallest mean monitoring error of 1.53% for the percentage of lake ice area in different periods. Meanwhile, the LII method can be used to determine long term lake ice phenology dates and had good performance in extracting lake ice for different types of lakes on the Qinghai–Tibet Plateau with the optimal threshold interval of 0.05~0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.

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Monitoring Lake Ice in Northern Alaska with Backscattering and Interferometric Approaches Using Sentinel-1 Sar Data

Cited by 4 publications

References 5 publications

Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study

Reservoir Ice Conditions from Multi-Sensor Remote Sensing and ERA5-Land: The Manicouagan Hydroelectric Reservoir Case Study

Retrieval of Lake Ice Characteristics from SAR Imagery

Comparison of Lake Ice Extraction Methods Based on MODIS Images

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