Characterizing Snow Dynamics in Semi-Arid Mountain Regions with Multitemporal Sentinel-1 Imagery: A Case Study in the Sierra Nevada, Spain
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsDear, Authors,
Please, find my comments and suggestions in the attached file!
Kind regards!
Comments for author File: 
Comments.pdf
Author Response
Thank you for your comments, which have helped us to improve the version of our manuscript. Please find our comments in the attached file.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for Authors- Please merge all points into one or two paragraphs in Conclusion
- Please highlight your contributions in the Sec. 1 Introduction
- In the introduction, I think the authors could add some literatures that describe the methods for extracting snowpack wet snow dynamics
- Please explain how to select the threshold for wet snow, how is the generalization? or the transferability? (ref. TGRS22-Partial domain adaptation for scene classification from remote sensing imagery)
- How about the accuracy of your method? This paper conveys extensive results while lack of evaluations
- Some references are recommended to cite:
- IGARSS22-Melting Glacier: A 37-Year (1984–2020) High-Resolution Glacier-Cover Record of MT. Kilimanjaro
- Arslan, A. N., & Akyurek, Z. (Eds.). (2021). Remote Sensing of Snow and Its Applications. MDPI.
Author Response
Thank you for your comments, which have helped us to improve the version of our manuscript. Please find our comments in the attached file.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThis paper proposed a method to monitor the snow melting dynamics using Sentinel 1 SAR images, and overall it is sound to me. However, I would recommend revising the introduction and providing additional evaluations before it is accepted.
1) Introduction section:
Line 60-64: microwave sensors are not usually considered optical, so please separate this literature review into optical and microwave, and also emphasize the microwave sensors for this work. In addition, update the literature reviews, and some newer papers that talk about continuous snow dynamics (snow cover fraction [Xiao et al 2022], snow albedo [Jia et al, 2023], and SWE [Luojus et al., 2021]) are suggested to be cited here.
The objective is well written but motivation is not clear in this section, thus I would suggest including some critical thinking to demonstrate the limitations of previous studies and clarify your innovation or what your new contributions are.
2) The evaluation section: MOD10 is used for inter-comparison, whereas MOD10 is also questioned by previous studies regarding its accuracy, so it would be great to include its variability in previous evaluations with meteorological variables to see if it is reliable as reference data.
3) any other microwave-based dataset for intercomparison? Also, suggest including some quantitative statistics rather than simple temporal variation comparison visually.
Ref.
Xiao, Xiongxin, et al. "Estimating fractional snow cover from passive microwave brightness temperature data using MODIS snow cover product over North America." The Cryosphere 15.2 (2021): 835-861.
Jia, Aolin, et al. "Improved cloudy-sky snow albedo estimates using passive microwave and VIIRS data." ISPRS Journal of Photogrammetry and Remote Sensing 196 (2023): 340-355.
Luojus, Kari, et al. "GlobSnow v3. 0 Northern Hemisphere snow water equivalent dataset." Scientific Data 8.1 (2021): 163.
Author Response
Thank you for your comments, which have helped us to improve the version of our manuscript. Please find our comments in the attached file.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors have addressed all my issues. Congrats!
