LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor
, Milan Lazecky 1, Tim J. Wright 1, Jonathan R. Weiss 1,3, John R. Elliott 1 and Andy Hooper 1
Round 1
Reviewer 1 Report
In this paper, an open-source InSAR time series analysis package (LiCSBAS) that integrates with LiCSAR is introduced and developed. LiCSBAS utilizes the LiCSAR products so that users do not need to produce interferograms from SLC data, which also enables users to easily obtain InSAR time series and velocity estimates wherever sufficient LiCSAR products are available.
The paper is well organized and the contribution is very meaningful. Before possible publication , the author could discuss more on the procedures for SAR data packed in the (LiCSBAS), which will be helpful to the researchers studying on the SAR area. In addition, the English usage could be improved. For example, before using abbreviation in the abstract and introduction, the full name of abbreviation should be detailed.
Author Response
Point 1: Before possible publication, the author could discuss more on the procedures for SAR data packed in the (LiCSBAS), which will be helpful to the researchers studying on the SAR area.
Response 1: The procedures for the SAR data are already written in Section 2.1. More details are beyond the scope of this paper and should be found in Lazecky et al. [37] as is written in the manuscript. We made no changes regarding this point.
Point 2: In addition, the English usage could be improved. For example, before using abbreviation in the abstract and introduction, the full name of abbreviation should be detailed.
Response 2: We have replaced U.S.A and UK with United states of America and United Kingdom, respectively. For other cases (i.e., ASAR, Envisat, GMTSAR, ISCE, SNAP, GIAnT, MintPy, StaMPS, and NASA), we did not change because these names have been very often used without the full name in other papers in Remote Sensing, and the full names are not common. LiCSBAS, LiCSAR, and GAMMA do not have the full name. We would like to leave this point to the editorial office.
Reviewer 2 Report
This paper presents an open source InSAR time-series analysis package for producing time-series of surface displacement using Sentinel-1 data.
The package is based on the SBAS processor and includes several features for, detecting unwrapping errors in the time-series, visualizing data spatially and temporally, validate InSAR data with GPS measurements.
The paper is well written and the topic is appropriate for the topic of the Journal. I recommend to publish the paper after adding the following figure:
I would like the authors to produce a scatter plot showing GPS projected time-series vs InSAR. Since there are many GPS covering the area each Station should be represented by a different color. Same for GPS projected VS InSAR with mask and Gacos.
Author Response
Point 1: I would like the authors to produce a scatter plot showing GPS projected time-series vs InSAR. Since there are many GPS covering the area each Station should be represented by a different color. Same for GPS projected VS InSAR with mask and Gacos.
Response 1: Thank you for your suggestion. We have made the time series plot for all GNSS stations and added as Figure S5 to the supplementary document.
Reviewer 3 Report
The paper presents an interesting tool for InSAR data processing. The work is well organised and scientifically sustained. Some better organization of the paper is need, but it can be published after minor revisions.
RC general comment: Maybe as the main focus of the paper is to show how to LiCSAR work some cases of studies should be avoided (and could be the object of a paper more focused on the application). As suggestion is to maintain the results for the whole dataset and to reduce the local case histories
At the same some more explanation of source code e.g. some input show in the GitHub code.
RC1: Please rename the name of the chapter following the Remote Sensing Standard:
2. Material and Methods
The study areas should be described in this section
3. Results (with should contain both 3 and 4 old)
RC 2: 2.2 paragraph: The results can be also exported for GIS software? e.g. in vectorial format?
RC 3: Equation 4 and its description should be moved to material and methods sections
RC 4 Line 65: Add other examples for GEP platform papers (e.g. Cignetti et al., 2016)
RC 5 Line 386 : 3. Case Study: Entire Frame: Please revise the font type
RC 6 Figure 14 b: use a non-continuous scale for the moths.
Author Response
RC general comment: Maybe as the main focus of the paper is to show how to LiCSAR work some cases of studies should be avoided (and could be the object of a paper more focused on the application). As suggestion is to maintain the results for the whole dataset and to reduce the local case histories
At the same some more explanation of source code e.g. some input show in the GitHub code.
We believe that the case study for a local area in Section 4 is essential in this paper to demonstrate that LiCSBAS can detect displacements with different temporal characteristics, including linear, periodic and episodic and therefore should not be reduced. We also think that the explanation of the source code is beyond the scope of this paper and is available on the GitHub pages. We made no changes regarding this comment.
RC1: Please rename the name of the chapter following the Remote Sensing Standard:
Material and MethodsThe study areas should be described in this section
Results (with should contain both 3 and 4 old)
We believe that it is not necessary to follow the Remote Sensing standard naming and the current Section titles are more suitable than the Remote Sensing Standard. Section 2 does not include the materials used in the case studies. Merging Section 3 and 4 would make a too large section. These sections have different points and should be separated. We made no changes regarding this comment.
RC 2: 2.2 paragraph: The results can be also exported for GIS software? e.g. in vectorial format?
Yes, the results can be easily exported to GeoTIFF, KMZ, or text format. We have added a sentence to Section 2.2.
RC 3: Equation 4 and its description should be moved to material and methods sections
This equation is used to estimate the uncertainty in the case study and only related to Section 3. Since LiCSBAS itself does not use this equation in the time series analysis, it cannot be moved to Section 2. We made no changes regarding this comment.
RC 4 Line 65: Add other examples for GEP platform papers (e.g. Cignetti et al., 2016)
Added [24].
RC 5 Line 386 : 3. Case Study: Entire Frame: Please revise the font type
Done.
RC 6 Figure 14 b: use a non-continuous scale for the moths.
Since the actual time offset data shown in Figure 14b is continuous (not discrete monthly), the continuous scale would be suitable. We made no changes regarding this comment.
