InSAR-DEM Block Adjustment Model for Upcoming BIOMASS Mission: Considering Atmospheric Effects
, Haiqiang Fu 1,*, Jianjun Zhu 1, Huacan Hu 1, Yi Li 1, Zhiwei Liu 1, Afang Wan 2 and Feng Wang 2Round 1
Reviewer 1 Report
Comments and Suggestions for Authors
The authors propose a block adjustment model considering atmospheric effects to separate systematic errors and atmospheric delay errors and then use the SA-MRWCA to detect atmospheric effects. The effectiveness of the method is tested using inland and costal datasets and they show an improvement in the quality of the data after correction. I suggest accepting the manuscript after the authors address minor suggestions as indicated below:
· Does the selection criteria of the GCPs and TPs have an influence on the outputs/method. A few comments regarding this can be provided.
· Comments on the computational complexity and processing time can be provided in the paper.
Comments on the Quality of English Language
Consider going through and correcting for minor grammatical errors in the entire paper, example: line 59, “One of the most effective methods”.
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper proposes a block adjustment model considering atmospheric effects for the large-scale topography mapping of the upcoming BIOMASS mission. The paper is well-written and easy to read. The proposed framework is presented clearly while the process is validated adequately, and the computed results are convincing. The primary concerns are as follows.
(1) The RHVCE is a weighting method that can resist gross errors or be seen as an approach to improve conventional least squares parameter estimation. It is recommended that the logic be revised as follows: Model parameters are estimated using least squares while simultaneously considering the adoption of a new weighting method.
(2) The BIOMASS mission will have fully polarimetric observation capability. Why cannot the MRWCA be directly used for wavelet correlation analysis of dual-polarization data to correct atmospheric effects? Please analyze the applicability of the MRWCA and the SA-MRWCA.
(3) Why are the chip grids of GCPs and TPs in Table 2 different?
(4) Is it necessary to conduct a t-test on the model parameters of block adjustment in the DEM calibration? If necessary, please emphasize its importance in the paper.
(5) Does the temporal mismatch issue of data such as ALOS-1, ICESat-2, and DEM products affect the experimental results?
Minor concerns:
(1) Please pay attention to the descriptions of DEM in Figure 7, Figure 10, and L493. For example, the "DEMs" of L493 should be "DEM".
(2) Please pay attention to L478, Not "calibration DEM", but "DEM calibration". Please check carefully.
(3) Please check the descriptions of the DEM in Figure 12, L302, L307, and L512.
(4) L404, change "path111" and "path113" to "path 111" and "path 113" to improve readability.
(5) The serial numbers of Figure 4 and Figure 5 are reversed.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsSuggestions:
Improve Visuals; Enhance the quality and specifics of the figures to effectively showcase the enhancements and alterations made by the model in showcasing comparisons before and, after.
In Depth Exploration of Constraints; Provide an exploration of the constraints associated with utilizing L band data as a substitute for P band data emphasizing inconsistencies and the impact, on the findings put forth.
More about future work.
Comments on the Quality of English LanguageMinor editing of English language required
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
