the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Monitoring Summertime Erosion Patterns Over an Arctic Permafrost Coast with Recent Sub-meter Resolution Microsatellite SAR Data
Abstract. Arctic coasts experience some of the highest rates of erosion in the world, particularly due to permafrost degradation resulting from the recent exacerbation of climate change. Therefore, not only have coastal defense and energy facilities been threatened, but maintenance costs for the infrastructure of cold regions have also risen. To monitor the coastal erosion pattern of the circum-Arctic, earlier studies often employ spaceborne or airborne optical multi-spectral images to depict shoreline changes, which are limited by frequent clouds and haze in Arctic regions and, thus, hamper the time-series analysis. Instead, this study aims to explore the synthetic aperture radar (SAR) images, especially the recently developed microsatellite SAR data, which provide unprecedented high-resolution at a sub-meter scale, to measure the summertime spatio-temporal dynamics of an ice-rich permafrost coast along the Beaufort Sea, Alaska. The results reveal a maximum shoreline change envelope (SCE) of 64.89 m during the three-month study period. To examine the differences between the estimations and the observations derived from the conventional Sentinel-1 data, the proposed multi-stage statistical-driven scheme is used. A statistically significant positive relationship between two depicted SCEs with the presence of heteroscedasticity is confirmed. In detail, the agreement between two SCEs increases with the magnitude of the SCE, indicating that the microsatellite SAR can depict more trivial changes in coastline positions. Founded on the results and detailed discussion on the uniqueness and limitations of current SAR sensors, the promising opportunity to utilize the blooming microsatellite SAR datasets for coastal monitoring is highlighted.
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RC1: 'Comment on egusphere-2024-1099', Anonymous Referee #1, 16 Sep 2024
The authors used sub-meter resolution microsatellite SAR data to monitor coastal erosions associated with permafrost changes. These dataset are very valuable for accurately quantifying Arctic coastal erosion. The topic is highly relevant and fits the scope of The Cryosphere. However, the structures is still underdeveloped, with some key information missing. The authors only demonstrate that the accuracy of coastline monitoring from Umbra is comparable to Sentinel-1, but the unique advantages of Umbra are not adequately highlighted. Furthermore, there is a lack of validation using field data or more reliable measurements, which weakens the overall impact of the findings. Therefore, I would not recommend the manuscript published in its current form. The major concerns are:
- Methodology
Coregistration should be considered a critical step for accurately monitoring coastal erosion over time using remote sensing time series analysis. But the authors did not address how to evaluate the accuracy of coregistration. While 3-meter TerraSAR-X images are used as a reference for coregistration, the degree to which the process relies on TerraSAR-X is not clearly explained.
While the authors describe the methods for extracting multi-temporal shorelines from both Umbra and Sentinel-1, they later state that the method is unsuitable for Umbra. This section should be revised and streamlined for clarity and consistency. Additionally, the justification for the use of the PAEK algorithm to mitigate errors should be clearly provided.
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- Result and discussion
The accuracy of coregistration, the performance of PAKE, and the unique advantages should be clearly evaluated and justified.
If possible, incorporating comparisons with field measurements or comparable high-resolution optical imagery would be beneficial.
Citation: https://doi.org/10.5194/egusphere-2024-1099-RC1 -
RC2: 'Comment on egusphere-2024-1099', Anonymous Referee #2, 17 Oct 2024
The presented study utilizes a specific SAR satellite for Arctic coastal monitoring. Data from this satellite (Umbra) have a comparably high spatial resolution and have so far not been used for this purpose. Shorelines were derived from acquisitions within a specific season and retreat quantified. The main focus is put on the comparison to retrievals from a different SAR mission with coarser spatial resolution and frequency (Sentinel-1). A previously well studied coastal stretch of 3.4 km length is covered with the data.
The introduction of the Umbra satellite is interesting, but results do not clearly provide scientific advance in the way presented. The study lacks innovation, neglects previous research, has methodological shortcomings, and does not include validation.
Specifically:
The citations in the introduction regarding permafrost state and coasts are not up to date. A good summary of the state of the art can be found in Irrgang et al. (2022).
Sub-meter SAR data have been exploited for Arctic coastal monitoring before. Analyses using data from TerraSAR-X (starring spotlight mode) with similar spatial resolution were already published (Bartsch et al. 2020). This publication is mentioned as an example for SAR application but not the use of sub-meter SAR.
A comparison scheme with Sentinel-1 is presented. The study setup does, however, not allow for such a comparison. Data are inconsistently preprocessed. Terrain corrected data from Umbra are compared to non-corrected data from Sentinel-1. This shortcoming is addressed by co-registration to data from a third sensor (TerraSAR-X) for which it is unknown whether it was terrain corrected or not. The description of these additional data is actually missing in the data section and preprocessing details are not fully provided in the method section. Was it terrain corrected? Acquisition date?
It is stated on line 95 that intra-seasonal dynamics are to be ‘depicted’ and several acquisitions are listed for Umbra as well as Sentinel-1 for a specific year. However, only the maximum retreat seems to have been derived. The results from the intra-seasonal analyses are missing.
Differences between the two datasets were found, but the actual accuracy of the retrieval is unknown due to lack of reference data. The erosion results are also not discussed with respect to previous studies. The scientific advance with respect to erosion monitoring and benefit for understanding of erosion patterns remains open.
The study area is rather special regarding coastal erosion in permafrost regions. Therefore, the validity of the conclusions for other coastal settings remains open. In case of SAR, retrieval performance is expected to differ with different coastal orientation and viewing geometry (occurrence of layover, foreshortening and radar shadow).
There are other high resolution results for the study area and the investigated period (Cassidy et al. 2024).
ReferencesÂ
Irrgang, A.M., Bendixen, M., Farquharson, L.M. et al. Drivers, dynamics and impacts of changing Arctic coasts. Nat Rev Earth Environ 3, 39–54 (2022). https://doi.org/10.1038/s43017-021-00232-1
Bartsch, A., Ley, S., Nitze, I., Pointner, G., and Vieira, G.: Feasibility study for the application of Synthetic Aperture Radar for coastal erosion rate quantification across the Arctic, Frontiers in Environmental Science, 8, 143, 2020.
Cassidy, G.; Wiseman, M.; Lange, K.; Eilers, C.; Bradley, A. Seasonal Coastal Erosion Rates Calculated from PlanetScope Imagery in Arctic Alaska. Remote Sens. 2024, 16, 2365. https://doi.org/10.3390/rs16132365Â
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Citation: https://doi.org/10.5194/egusphere-2024-1099-RC2
Status: closed
-
RC1: 'Comment on egusphere-2024-1099', Anonymous Referee #1, 16 Sep 2024
The authors used sub-meter resolution microsatellite SAR data to monitor coastal erosions associated with permafrost changes. These dataset are very valuable for accurately quantifying Arctic coastal erosion. The topic is highly relevant and fits the scope of The Cryosphere. However, the structures is still underdeveloped, with some key information missing. The authors only demonstrate that the accuracy of coastline monitoring from Umbra is comparable to Sentinel-1, but the unique advantages of Umbra are not adequately highlighted. Furthermore, there is a lack of validation using field data or more reliable measurements, which weakens the overall impact of the findings. Therefore, I would not recommend the manuscript published in its current form. The major concerns are:
- Methodology
Coregistration should be considered a critical step for accurately monitoring coastal erosion over time using remote sensing time series analysis. But the authors did not address how to evaluate the accuracy of coregistration. While 3-meter TerraSAR-X images are used as a reference for coregistration, the degree to which the process relies on TerraSAR-X is not clearly explained.
While the authors describe the methods for extracting multi-temporal shorelines from both Umbra and Sentinel-1, they later state that the method is unsuitable for Umbra. This section should be revised and streamlined for clarity and consistency. Additionally, the justification for the use of the PAEK algorithm to mitigate errors should be clearly provided.
Â
- Result and discussion
The accuracy of coregistration, the performance of PAKE, and the unique advantages should be clearly evaluated and justified.
If possible, incorporating comparisons with field measurements or comparable high-resolution optical imagery would be beneficial.
Citation: https://doi.org/10.5194/egusphere-2024-1099-RC1 -
RC2: 'Comment on egusphere-2024-1099', Anonymous Referee #2, 17 Oct 2024
The presented study utilizes a specific SAR satellite for Arctic coastal monitoring. Data from this satellite (Umbra) have a comparably high spatial resolution and have so far not been used for this purpose. Shorelines were derived from acquisitions within a specific season and retreat quantified. The main focus is put on the comparison to retrievals from a different SAR mission with coarser spatial resolution and frequency (Sentinel-1). A previously well studied coastal stretch of 3.4 km length is covered with the data.
The introduction of the Umbra satellite is interesting, but results do not clearly provide scientific advance in the way presented. The study lacks innovation, neglects previous research, has methodological shortcomings, and does not include validation.
Specifically:
The citations in the introduction regarding permafrost state and coasts are not up to date. A good summary of the state of the art can be found in Irrgang et al. (2022).
Sub-meter SAR data have been exploited for Arctic coastal monitoring before. Analyses using data from TerraSAR-X (starring spotlight mode) with similar spatial resolution were already published (Bartsch et al. 2020). This publication is mentioned as an example for SAR application but not the use of sub-meter SAR.
A comparison scheme with Sentinel-1 is presented. The study setup does, however, not allow for such a comparison. Data are inconsistently preprocessed. Terrain corrected data from Umbra are compared to non-corrected data from Sentinel-1. This shortcoming is addressed by co-registration to data from a third sensor (TerraSAR-X) for which it is unknown whether it was terrain corrected or not. The description of these additional data is actually missing in the data section and preprocessing details are not fully provided in the method section. Was it terrain corrected? Acquisition date?
It is stated on line 95 that intra-seasonal dynamics are to be ‘depicted’ and several acquisitions are listed for Umbra as well as Sentinel-1 for a specific year. However, only the maximum retreat seems to have been derived. The results from the intra-seasonal analyses are missing.
Differences between the two datasets were found, but the actual accuracy of the retrieval is unknown due to lack of reference data. The erosion results are also not discussed with respect to previous studies. The scientific advance with respect to erosion monitoring and benefit for understanding of erosion patterns remains open.
The study area is rather special regarding coastal erosion in permafrost regions. Therefore, the validity of the conclusions for other coastal settings remains open. In case of SAR, retrieval performance is expected to differ with different coastal orientation and viewing geometry (occurrence of layover, foreshortening and radar shadow).
There are other high resolution results for the study area and the investigated period (Cassidy et al. 2024).
ReferencesÂ
Irrgang, A.M., Bendixen, M., Farquharson, L.M. et al. Drivers, dynamics and impacts of changing Arctic coasts. Nat Rev Earth Environ 3, 39–54 (2022). https://doi.org/10.1038/s43017-021-00232-1
Bartsch, A., Ley, S., Nitze, I., Pointner, G., and Vieira, G.: Feasibility study for the application of Synthetic Aperture Radar for coastal erosion rate quantification across the Arctic, Frontiers in Environmental Science, 8, 143, 2020.
Cassidy, G.; Wiseman, M.; Lange, K.; Eilers, C.; Bradley, A. Seasonal Coastal Erosion Rates Calculated from PlanetScope Imagery in Arctic Alaska. Remote Sens. 2024, 16, 2365. https://doi.org/10.3390/rs16132365Â
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Citation: https://doi.org/10.5194/egusphere-2024-1099-RC2
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