the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Jun 2024
Brief Communication: Monitoring slope acceleration and impending failure with very high spatial and temporal resolution space borne Synthetic Aperture Radars
Abstract. We demonstrate how high spatial and temporal resolution spaceborne synthetic aperture radar (SAR) imagery can be applied to improve slope deformation monitoring. We process ICEYE data acquired over the Brienz/Brinzauls slope instability in the Swiss Alps, where a catastrophic failure occurred on June 15th, 2023. The available images provided unprecedented viewing of the moving slope from satellite SAR, with revisit times ranging from less than 1 hour to a maximum of 4 days. We apply image correlation algorithms (i.e., pixel-offset analysis) on SAR backscattering to measure surface velocity before the failure event and compared the results against ground-based SAR data used for early-warning purposes. We also compare pre- and post-failure imagery to map areas invaded by debris and to compute volumetric changes associated with the down wasted materials, showing good agreement with digital surface models generated from photogrammetric drone flights. Our results demonstrate how weather independent, high resolution satellite SAR data can provide data in critical scenarios of slope deformation, suggesting that crucial information can be retrieved timely also in remote, poorly accessible regions where in-situ monitoring is not viable.
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Status: open (until 23 Jul 2024)
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RC1: 'Comment on egusphere-2024-1296', Anonymous Referee #1, 14 Jun 2024
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Manconi et al present a case study where they used high-resolution SAR images (ICEYE) to survey a fast moving landslide in the last few weeks before its failure. They measured the surface velocity and the volume of the collapsed material. Although they did not adopt innovative processing techniques, their aim is to show the potentialities of ICEYE in monitoring strongly dynamical processes, which I think is an interesting topic.
Overall comments:
The manuscript is well written and the figures are clear. The motivation of the study is clear and the results support the thesis of the authors (i.e., the potentialities of ICEYE). However, I have two major concerns, pertaining to formal and methodological aspects. First, the manuscript is not compliant with the rules of brief communications: the abstract is too long (>180 words, but maximum 100 are admitted). There are four figures and one table (max three in total admitted). Probably figs. 3 and 4 might be merged and the table moved into supplementary material. Also the number of references (>30) is greater than the maximum admitted number (20). Since it is a brief communication, which is expected to deal with cutting edge research, I think that non recent references can be omitted. For example, I count at least 9 reference older that 10 years. There are six references at lines 29-30 in the introduction related to the use of SAR in natural hazards, but probably one-two are sufficient. Plus, I have some doubts that the manuscript will be shorter than 4 pages in its final form, which is the maximum number for brief communications. If necessary, I think that the parts describing the time-series inversion and the DoD might be slightly shortened. If, on the contrary, the authors decide to convert the manuscript into a research article, I think that they should add more details to their study, for example a comparison with the results obtained with other satellites, but I do not suggest this option, since this work is already relevant in this version. The second concern pertains to the lack of an uncertainty analysis, which is fundamental considering that the main goal of the manuscript is to demonstrate the ability of ICEYE to detect fast movements. Even the comparison with the GBSAR is presented only in a qualitative fashion, without any quantitative metrics.Besides these points, I have some other minor remarks:
- Title: I would add the mention to ICEYE in the title (or in the keywords, which I cannot see).
- line 44: Even though in the literature the term robotized total station is occasionally adopted, I think that robotic is more correct English
- line 55: Can you explain in a few words the main characteristics of HIGH mode? E.g., terrain corrected or not, polarisation, etc,
- line 63: here and in the rest of the manuscript, a space is missing between numbers and units
- lines 65-66: it is not clear how you benifitted from the DSM. Later in the manuscript you state that you used the SLC, thus I suppose that you did not orthorectify the SAR images. Please, can you exaplain this point better?
- line 76: PO is adopted also to measure surface displacement (like you do in this study), which, in my opinion, is a different concept compared to the residual alignment between images
- line 79-80: You probably should exaplain that PO allows to detect sub-pixel displacement because non-expert readers might not figure out this statement. Besides, "some centimeter" sounds a little undefined
- line 82 (factor of 4): This implies that the minimum measured displacement is 1/4 of the GSD, thus 8-10 cm. Peraphs you could move here the statement at lines 79-80.
- line 84 (pixel size): You adopt different terms to indicate this quantity: pixel resolution, GSD and pixel size. I suggest to be more uniform for clarity
- line 92: This paragraphs might be hard to understand to non-expert readers. First, the least square is not an approach to extract time-series, but the method adopted to solve the equation system. I suppose you are using a temporal closure-like method. In that case, you probably could cite Charrier et al (2022) and/or Hadrhi et al (2019), if relevant and if you can add references without exceeding 20 references, or move Casu et al (2011) here. For the sake of reproducibility, you could also specify whether you adopted weights and/or regularisation terms in the equation system.
- line 93: I think you should add some uncertainty analysis to your manuscript. For example, you could detect displacements of 10 cm, but what is the estimated uncertainty and how did you evaluate it? You could also show how the uncertainty is related to the relative viewing angles between the images. How did you determine the threshold of 1.5 degrees? Besides, the time-series inversion also introduces some uncertainty. Plus, you should add error bars in the time series plots.
- line 95: this is clear example of a reference that you can omit, since the SVD is a standard statistical technique.
- lines 95-97: To what extend is your method similar to that of Casu et al (2011)? Since you did not provide any further detail, probably this statement can be omitted, leaving only the reference if necessary.
- lines 98-99: I do not agree with this statement. The time-series inversion can be applied at any time. Of course, when new images become available, the results of the inversion might change, but, in a theoretically operative situation, one could calculate the time series with the currently available images and then update the time-series at every new acquisition.
- line 101 (fig2b): I do not see a direct correspondence between the blue circle in fig 2b and the available images in fig 1c. Probably, you did not consider pairs of images with a temporal baseline lower that a given threshold (1 day?) Plus, it seems that you have plotted the markers of the velocity in correspondence of the slave image, but I think that it is more correct to plot them in the middle time, since it represents the average velocity over the period between the two acquisitions.
- line 102 (black diamonds): In fig 2b I see more black diamonds that blue circles, but they should be less, since you only used a subset of the available images. Maybe the two markers are inverted? In any case, I would expect that one marker of the sequential approach would be present for each marker of the selected approach, but there are dates where only blue or black markers are shown.
- line 103: How much more variability? You should provide some statistical metrics to compare the data and add an uncertainty analysis.
- fig 2c: I do not find a precise correspondence between the text and this figure (see comments above). Another concern pertains to the results of the time-series inversion (red triangles). In theory, there should be one result for each adopted image, but, on some dates, there are red triangles but not other markers and vice versa.
- lines 123-124: since you have to shorten the manuscript, probably this is one statement that can be omitted.
- line 169: Despite thatCitation: https://doi.org/10.5194/egusphere-2024-1296-RC1
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