the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Mar 2024
Multitemporal UAV LiDAR detects seasonal heave and subsidence on palsas
Abstract. In the context of the accelerating impacts of climate change on permafrost landscapes, we use Unpiloted Aerial Vehicle (UAV) LiDAR technology to investigate seasonal terrain changes in palsas – mounds of frozen peat – since other remote sensing methods have struggled to capture the full dynamics of these landforms. We investigated two palsas (4–5 m in height) in Sweden's largest palsa mire complex, where we performed five field campaigns between September 2022 and September 2023 to track intra-annual frost heave and thaw subsidence. Our approach allowed us to create digital terrain models (DTMs) from high density point clouds (>1,000 points/m²) and analyze elevation changes over time. We found that both palsas heaved on average 0.15 m (and up to 0.30 m) from September to April and subsided back to their height from the previous year, or slightly below, over the course of the following summer. At one of the palsas, we observed notable lateral degradation over the study period in a 300 m2 area, with 0.5–2.0 m height loss, likely initiated during the preceding warm and wet summer months. Part of this degradation occurred between September 2022 and April 2023, suggesting that the degradation of these palsas is not limited to the summer months. Our study shows the substantial value of using UAV LiDAR for understanding how permafrost areas are changing. It helps in tracking the ongoing effects of climate change and highlights palsa dynamics that would not be captured by annual measurements alone.
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RC1: 'Comment on egusphere-2024-141', Jan Henrik Blöthe, 16 Apr 2024
Review of Renette et al: “Multitemporal UAV LiDAR detects seasonal heave andsubsidence on palsas”.
Manuscript Number: EGUsphere-2024-141
In their manuscript, Renette et al. investigate surface changes on two palsa features in Northern Sweden between September 2022 and September 2023. Primarily exploiting digital topography as recorded at five time stamps using a UAV mounted LiDAR module, their data show average seasonal heave of the palsa surface of ~15 cm and a subsidence of roughly the same magnitude over the following warm season. Furthermore, their data reveal lateral degradation of the palsa features, where surface changes over the monitoring period fall between 0.5 and 2 m.
The manuscript is well written and structured and contains eight figures and one table that illustrate the findings of the authors. The data as well as the analysis are sound and the findings of the study are of interest to the wider community, even though the data presented is restricted to a short monitoring period and a limited area. However, before ready for publication, the authors need to address a number of issues that I outline below, hopefully helping to improve the quality of the manuscript.
General comment
The only major issue I want to raise concerns the error assessment in the study. Surely, the authors present data sets of high quality, but at the same time the vertical differences observed are small. In Tab. 1, the authors state that the vertical accuracy of the digital terrain models presented are 0.021 and 0.028 m for the two different scanners used. In L330-332 it is stated that “changes less than these are within the margin of error”, i.e. are not to be interpreted as a reliable signal but rather to be considered as noise. This should be addressed in the study and included in the presentation of the results. When subtracting digital elevation models and creating difference maps, the individual errors should be propagated to separate reliable change information from insignificant change values. Also, it should be clearly stated, how the vertical accuracy presented in Tab. 1 was determined. In assessing the accuracy of the difference models, the “normalization” of the elevation values to the mean mire elevation should also be included and discussed (see specific comments). Finally, it would be helpful for the reader to see the full distribution of elevation change values for all time stamps in a histogram view, maybe as a supplementary figure.
Specific comments:
- L79-81: I recommend to shift this sentence to the conclusions
- L88-91: In my view, it would be good to also provide the area of the two palsa features here. This would allow the authors to quantify the areal change, as well as to describe the features more comprehensively.
- L92: all-terrain vehicle (ATV)
- L98: Please provide coordinates detailing the locations of panels b) and c) as well. Also, b) would deserve a scale bar. The resolution of the Figure could also be improved, though this is likely related to the preprint format and will be accounted for in the full publication.
- L115-116 / L122-123: If the HOBO station has been installed in September 2022, how can the data shown in the lower panel (add letters) of Figure 2 show monthly precipitation and snow depth before that date?
- L121-122: Does “Air temperature” refer to mean daily air temperature? Please specify this here and also elaborate in the text at which interval the temperature is recorded.
- L124-125: These are interesting details from an earlier study. I would encourage the authors to come back to this data in the discussion and compare their 2022-2023 area changes to those found by Olvmo et al. before. Again, this would involve delineating the exact position of the palsas in the data presented here, which in my view would increase the quality of the work. It would also help to show the outlines of the palsa features in Figures 5 to 7.
- L147: flight missions?
- L152: superscript m2
- L185-187: Why did the authors decide to use the minimum elevation here? Would the high point density also allow to use the 25th percentile of the distribution to determine the elevation of a cell to not be relying on individual points that also might deviate from the surface?
- L191-195: But the mire elevation cannot be considered constant, as the authors also describe in L273-277. Given the small overall differences between the DTMs produced for the different time-stamps, how can the authors make sure that these are not produced by the normalization process to a fluctuating mire surface elevation?
- L198-199: Please elaborate in more detail how this height difference was calculated and how the vertical accuracy might influence the interpretation. Is the maximum difference provided here based on a single pixel? How confident are the authors that this provides a robust signal?
- L199-202: It would be interesting to place these 300 m2 in the context of the full extent of the feature. What is the percentage change?
- L206: In the figure, c) does not show a DTM, but a difference map. Furthermore, providing outlines of the palsas here would help interpreting the figures, especially for panels c) and f).
- L211-212: A lot of full stops here
- L220: Also in this figure, it would be nice to show the outlines of the palsas to help the reader interpreting the elevation difference shown here. Furthermore, masking the snow covered area in April 2023 here would in my view be advisable to avoid misinterpretation of the figure.
- L236: Again, please elaborate how these values were calculated. Is the difference in mean height calculated on the entire distribution of the values, or just using a subset on the palsa surface?
- L238-242: Did the authors analyse whether the individual differences of the intermediate time steps are comparable to the changes determined from subtracting the start and end models?
- L244-245: In this figure, it would be interesting to see error bars for the values of relative height changes.
- L268-273: Is there any data that supports the assumption of a thinner active layer in the top-positions of the palsa compared to their surroundings?
- L308-311: This aspect should be discussed in more detail here. While I agree that the elevation changes on both palsas are very similar (L241-242, Fig. 8), the behaviour over the summer is different. Is this a robust signal and what is the interpretation of the authors?
- L319: A lot of commas here
Citation: https://doi.org/10.5194/egusphere-2024-141-RC1 - AC1: 'Reply on RC1', Cas Renette, 12 Jul 2024
-
RC2: 'Comment on egusphere-2024-141', Martha Ledger, 30 May 2024
General comments:
This work investigates seasonal palsa heave and thaw at two sites in Sweden using UAV LiDAR. Repeated measurements are obtained within the space of a year, enabling more detailed understanding of inter-seasonal dynamics. Whilst the time series is short and specific to a small area, it is nonetheless valuable as a case study for understanding palsa heave/thaw dynamics more broadly in a such an ecologically and climatically sensitive zone. The methods are detailed and there is good thorough consideration of methods available for monitoring palsa surface dynamics in the discussion. The value of repeated UAV LiDAR for capturing detailed seasonal dynamics of palsa thaw and heave is very clear from this work.
The paper is well written. However, I think the opening paragraph in particular is the weakest part of the writing because it is trying to address too many points with too little detail. I recommend splitting this paragraph into two (e.g. 1: The ecological and climatic importance of permafrost, and 2: threats to permafrost environments).
Given the limited spatial and temporal scope of the paper, some further work is needed to contextualise the findings at these sites with other literature from the region. I note that comparisons are already made with site-specific studies using LiDAR but in Alaska and Canada. Within Scandinavia, methodological comparisons are made with other studies (e.g. use of InSAR vs LiDAR) but the findings of these studies could also be incorporated to better understand trends at this site and the region. Whilst InSAR is broadly agreed to underestimate rates, there is confidence in the direction of vertical trends, which can still make for valuable contextual information. I recommend taking a look at the very recently published paper from Valman et al. (2024) [https://doi.org/10.5194/tc-18-1773-2024], which looks at the subsidence of the same site of Vissátvuopmi (and across the same palsa mire complex more broadly) except using InSAR from 2017-2021. It could provide a site history and context of subsidence trends prior to your study embarking in 2022 (may be useful at lines 258-267).
Hopefully my suggestions in the general and specific comments will help to improve the clarity of some points and increase the impact of the paper. I hope the authors will find them helpful.
Specific comments:
L21: replace “helps in” with “facilitates”
L45: it would be useful to include a definition of ‘lateral erosion’ and ‘vertical subsidence’ and differentiate between the two here.
L79-81: I would reserve stating findings until the discussion/conclusion.
L92: I am not familiar with what an ATV is. Please define.
L116: Please define HOBO weather station.
L152: change ‘m2’ to ‘m2’
L206: “palsas palsa” repeated twice in caption
L212: two full stops here – please remove one.
L228: could you clarify what you mean by “deepening” here? I presume this is referring to snow depth?
L276-277: Glad to see that you have taken this into account – I would be intrigued to find out more about how you corrected for this effect? Elevational changes in the mire could be partially independent of the palsa elevational changes because ‘mire breathing’ may reflect water table level change (if water table rises above ground level) rather than ground surface level change at some points during the seasonal cycle. I am not sure if this is the case at the sites you have investigated. In any case, some site context may be useful here to establish whether water tables typically rise above mire surface level here and how you would have corrected for this. If so, it's possible this could have further implications for lateral erosion rates? You may prefer to address this in the methods.
L279: replace “been” with “used”.
L289-307: you could also consider higher winter precipitation rates contributing to greater thaw over the following summer season, especially with warmer winter temperatures so that rain falls instead of snow. This could compromise snow depth over the winter and therefore increase the length of the following thaw period. It’s possible that this can be seen from the weather station data in Figure 2, where it looks like there is lower average snow depth and greater winter precipitation rates in the winter season 2022/2023.
L319: two commas, remove one.
L366: insert “of” between “degradation palsas”
Citation: https://doi.org/10.5194/egusphere-2024-141-RC2 - AC2: 'Reply on RC2', Cas Renette, 12 Jul 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-141', Jan Henrik Blöthe, 16 Apr 2024
Review of Renette et al: “Multitemporal UAV LiDAR detects seasonal heave andsubsidence on palsas”.
Manuscript Number: EGUsphere-2024-141
In their manuscript, Renette et al. investigate surface changes on two palsa features in Northern Sweden between September 2022 and September 2023. Primarily exploiting digital topography as recorded at five time stamps using a UAV mounted LiDAR module, their data show average seasonal heave of the palsa surface of ~15 cm and a subsidence of roughly the same magnitude over the following warm season. Furthermore, their data reveal lateral degradation of the palsa features, where surface changes over the monitoring period fall between 0.5 and 2 m.
The manuscript is well written and structured and contains eight figures and one table that illustrate the findings of the authors. The data as well as the analysis are sound and the findings of the study are of interest to the wider community, even though the data presented is restricted to a short monitoring period and a limited area. However, before ready for publication, the authors need to address a number of issues that I outline below, hopefully helping to improve the quality of the manuscript.
General comment
The only major issue I want to raise concerns the error assessment in the study. Surely, the authors present data sets of high quality, but at the same time the vertical differences observed are small. In Tab. 1, the authors state that the vertical accuracy of the digital terrain models presented are 0.021 and 0.028 m for the two different scanners used. In L330-332 it is stated that “changes less than these are within the margin of error”, i.e. are not to be interpreted as a reliable signal but rather to be considered as noise. This should be addressed in the study and included in the presentation of the results. When subtracting digital elevation models and creating difference maps, the individual errors should be propagated to separate reliable change information from insignificant change values. Also, it should be clearly stated, how the vertical accuracy presented in Tab. 1 was determined. In assessing the accuracy of the difference models, the “normalization” of the elevation values to the mean mire elevation should also be included and discussed (see specific comments). Finally, it would be helpful for the reader to see the full distribution of elevation change values for all time stamps in a histogram view, maybe as a supplementary figure.
Specific comments:
- L79-81: I recommend to shift this sentence to the conclusions
- L88-91: In my view, it would be good to also provide the area of the two palsa features here. This would allow the authors to quantify the areal change, as well as to describe the features more comprehensively.
- L92: all-terrain vehicle (ATV)
- L98: Please provide coordinates detailing the locations of panels b) and c) as well. Also, b) would deserve a scale bar. The resolution of the Figure could also be improved, though this is likely related to the preprint format and will be accounted for in the full publication.
- L115-116 / L122-123: If the HOBO station has been installed in September 2022, how can the data shown in the lower panel (add letters) of Figure 2 show monthly precipitation and snow depth before that date?
- L121-122: Does “Air temperature” refer to mean daily air temperature? Please specify this here and also elaborate in the text at which interval the temperature is recorded.
- L124-125: These are interesting details from an earlier study. I would encourage the authors to come back to this data in the discussion and compare their 2022-2023 area changes to those found by Olvmo et al. before. Again, this would involve delineating the exact position of the palsas in the data presented here, which in my view would increase the quality of the work. It would also help to show the outlines of the palsa features in Figures 5 to 7.
- L147: flight missions?
- L152: superscript m2
- L185-187: Why did the authors decide to use the minimum elevation here? Would the high point density also allow to use the 25th percentile of the distribution to determine the elevation of a cell to not be relying on individual points that also might deviate from the surface?
- L191-195: But the mire elevation cannot be considered constant, as the authors also describe in L273-277. Given the small overall differences between the DTMs produced for the different time-stamps, how can the authors make sure that these are not produced by the normalization process to a fluctuating mire surface elevation?
- L198-199: Please elaborate in more detail how this height difference was calculated and how the vertical accuracy might influence the interpretation. Is the maximum difference provided here based on a single pixel? How confident are the authors that this provides a robust signal?
- L199-202: It would be interesting to place these 300 m2 in the context of the full extent of the feature. What is the percentage change?
- L206: In the figure, c) does not show a DTM, but a difference map. Furthermore, providing outlines of the palsas here would help interpreting the figures, especially for panels c) and f).
- L211-212: A lot of full stops here
- L220: Also in this figure, it would be nice to show the outlines of the palsas to help the reader interpreting the elevation difference shown here. Furthermore, masking the snow covered area in April 2023 here would in my view be advisable to avoid misinterpretation of the figure.
- L236: Again, please elaborate how these values were calculated. Is the difference in mean height calculated on the entire distribution of the values, or just using a subset on the palsa surface?
- L238-242: Did the authors analyse whether the individual differences of the intermediate time steps are comparable to the changes determined from subtracting the start and end models?
- L244-245: In this figure, it would be interesting to see error bars for the values of relative height changes.
- L268-273: Is there any data that supports the assumption of a thinner active layer in the top-positions of the palsa compared to their surroundings?
- L308-311: This aspect should be discussed in more detail here. While I agree that the elevation changes on both palsas are very similar (L241-242, Fig. 8), the behaviour over the summer is different. Is this a robust signal and what is the interpretation of the authors?
- L319: A lot of commas here
Citation: https://doi.org/10.5194/egusphere-2024-141-RC1 - AC1: 'Reply on RC1', Cas Renette, 12 Jul 2024
-
RC2: 'Comment on egusphere-2024-141', Martha Ledger, 30 May 2024
General comments:
This work investigates seasonal palsa heave and thaw at two sites in Sweden using UAV LiDAR. Repeated measurements are obtained within the space of a year, enabling more detailed understanding of inter-seasonal dynamics. Whilst the time series is short and specific to a small area, it is nonetheless valuable as a case study for understanding palsa heave/thaw dynamics more broadly in a such an ecologically and climatically sensitive zone. The methods are detailed and there is good thorough consideration of methods available for monitoring palsa surface dynamics in the discussion. The value of repeated UAV LiDAR for capturing detailed seasonal dynamics of palsa thaw and heave is very clear from this work.
The paper is well written. However, I think the opening paragraph in particular is the weakest part of the writing because it is trying to address too many points with too little detail. I recommend splitting this paragraph into two (e.g. 1: The ecological and climatic importance of permafrost, and 2: threats to permafrost environments).
Given the limited spatial and temporal scope of the paper, some further work is needed to contextualise the findings at these sites with other literature from the region. I note that comparisons are already made with site-specific studies using LiDAR but in Alaska and Canada. Within Scandinavia, methodological comparisons are made with other studies (e.g. use of InSAR vs LiDAR) but the findings of these studies could also be incorporated to better understand trends at this site and the region. Whilst InSAR is broadly agreed to underestimate rates, there is confidence in the direction of vertical trends, which can still make for valuable contextual information. I recommend taking a look at the very recently published paper from Valman et al. (2024) [https://doi.org/10.5194/tc-18-1773-2024], which looks at the subsidence of the same site of Vissátvuopmi (and across the same palsa mire complex more broadly) except using InSAR from 2017-2021. It could provide a site history and context of subsidence trends prior to your study embarking in 2022 (may be useful at lines 258-267).
Hopefully my suggestions in the general and specific comments will help to improve the clarity of some points and increase the impact of the paper. I hope the authors will find them helpful.
Specific comments:
L21: replace “helps in” with “facilitates”
L45: it would be useful to include a definition of ‘lateral erosion’ and ‘vertical subsidence’ and differentiate between the two here.
L79-81: I would reserve stating findings until the discussion/conclusion.
L92: I am not familiar with what an ATV is. Please define.
L116: Please define HOBO weather station.
L152: change ‘m2’ to ‘m2’
L206: “palsas palsa” repeated twice in caption
L212: two full stops here – please remove one.
L228: could you clarify what you mean by “deepening” here? I presume this is referring to snow depth?
L276-277: Glad to see that you have taken this into account – I would be intrigued to find out more about how you corrected for this effect? Elevational changes in the mire could be partially independent of the palsa elevational changes because ‘mire breathing’ may reflect water table level change (if water table rises above ground level) rather than ground surface level change at some points during the seasonal cycle. I am not sure if this is the case at the sites you have investigated. In any case, some site context may be useful here to establish whether water tables typically rise above mire surface level here and how you would have corrected for this. If so, it's possible this could have further implications for lateral erosion rates? You may prefer to address this in the methods.
L279: replace “been” with “used”.
L289-307: you could also consider higher winter precipitation rates contributing to greater thaw over the following summer season, especially with warmer winter temperatures so that rain falls instead of snow. This could compromise snow depth over the winter and therefore increase the length of the following thaw period. It’s possible that this can be seen from the weather station data in Figure 2, where it looks like there is lower average snow depth and greater winter precipitation rates in the winter season 2022/2023.
L319: two commas, remove one.
L366: insert “of” between “degradation palsas”
Citation: https://doi.org/10.5194/egusphere-2024-141-RC2 - AC2: 'Reply on RC2', Cas Renette, 12 Jul 2024
Data sets
Dataset for: 'Multitemporal UAV LiDAR detects seasonal heave and subsidence on palsas' (Renette et al., 2024, submitted to The Cryosphere) V1.0 Cas Renette https://zenodo.org/records/10497094
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