Joss paper

[rogerkuou]

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[rogerkuou]

Hi @SarahAlidoost @vanlankveldthijs @FreekvanLeijen @meiertgrootes @fnattino, sorry for spamming during holiday season! There is no rush to react.
This is a draft JOSS paper for stmtools. I listed all of you as the author since you had direct contribution. Could you please review this when you have time?
The complied paper can be downloaded in this artifacts from this GH action.

[SarahAlidoost]

Suggested change

Interferometry Synthetic Aperture Radar (InSAR) is a crucial technology for monitoring ground surface deformation. It has essential value in various applications, such as civil-infrastructure stability [@chang2014detection; @chang2017railway], hydrocarbons extraction [@fokker2016application; @ZHANG2022102847], etc. To efficiently process and analyze these datasets, researchers has proposed the Space-Time Matrix (STM) format for InSAR datasets [@Bruna2021, @vanLeijen2021], which enanbles the intergration of the contextual information with the InSAR data to reveal the mechanisms driving deformation.

Interferometry Synthetic Aperture Radar (InSAR) is a commonly used technology for monitoring ground surface deformation in various applications, such as civil-infrastructure stability [@chang2014detection; @chang2017railway], hydrocarbons extraction [@fokker2016application; @ZHANG2022102847]. To process and analyze InSAR datasets, researchers have proposed the Space-Time Matrix (STM) format [@Bruna2021, @vanLeijen2021], which enables the integration of contextual information with data to reveal the mechanisms driving deformation.

[SarahAlidoost]

Here are explanations about my suggestions:

• I suggest rephrasing "a crucial technology", "essential value" and "To efficiently process" because they rely on relative terms that lack clarity without specific context. For example if we say "efficiently", we should explain what we mean, how efficient it is, and how it is measured.
• I also suggest removing "etc" as it does not add much to the content.
• I replaced "these datasets" with "InSAR datasets" since "these" was unclear and was not mentioned in the previous sentence.
• The rest of my suggestions are about fixing typos.

[SarahAlidoost]

Suggested change

Typiclally, modern time-series InSAR methods is able to provides millions of observation points in a single dataset. However, due the complex and ambiguous nature of InSAR observations, interpretation of these datasets is challenging. [@hanssen2001radar] Under the STM framework, contextual information such as temperature, precipitation, land-use, etc. can be integrated with InSAR data. This can enable a better understanding on the driving mechanisms of the ground deformation, resulting in more reliable and accurate interpretation of the InSAR data. [@Bruna2021, @vanLeijen2021]

Modern time-series InSAR methods provide millions of observation points in a single dataset. However, interpretation of these datasets is challenging due to the complex and ambiguous nature of InSAR observations. [@hanssen2001radar] Under STM format, contextual information such as temperature, precipitation, and land-use can be integrated with InSAR data. This facilitates a better interpretation of InSAR data, resulting in a reliable and accurate understanding of the mechanisms of ground deformation. [@Bruna2021, @vanLeijen2021]

[SarahAlidoost]

Here is the explanation of my suggestion:

• I replace "framework" with "format" because "STM format" is mentioned in the introduction.
• I rewrite the last sentence because a better interpretation of the InSAR data will lead to a better understanding of ground deformation, not the other way around.

[SarahAlidoost]

Suggested change

To implement the STM format in Python, we developed the `STMTools` package. `STMTools` is developed as an extension of `Xarray`, leveraging `Xarray`'s support for labeled multi-dimensional arrays for the Space-Time concept. `STMTools` provides a set of tools to efficiently connect the InSAR data with various contextual information, such as cadastral data, weather data, etc. The package also utilizes `Dask` for parallel computing, enabling the processing of large-scale InSAR datasets.

To utilize the STM format for InSAR data, we developed the `STMTools` package in Python-- as an extension of `Xarray`-- leveraging `Xarray`'s support for labeled multi-dimensional arrays for the Space-Time concept. `STMTools` provides a set of tools to connect InSAR data with various contextual information, such as cadastral data, and weather data. The package also utilizes `Dask` for parallel computing, enabling the efficient processing of large-scale data.

[SarahAlidoost]

Can we also add one sentence about other functionalities of the STMTools package here, for example, subsetting data, adding metadata, regulating the dimensions, ....

[SarahAlidoost]

Suggested change

	We provide a tutorial as a Jupyter notebook to demonstrate the basic functionalities of `STMTools`:
	We provided several tutorials, also available as Jupyter notebooks, to demonstrate the functionalities of `STMTools`:

[SarahAlidoost]

The links provided here, lead to documentation, not Jupyter Notebooks. If the idea is to share the tutorials as notebooks, we can add a download button on the MkDocs page so users can get the notebooks too.

[SarahAlidoost]

Suggested change

	The authors express sincere gratitude to the Dutch Research Council (Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO) for their generous funding of the `STMTools` development through the Collaboration in Innovative Technologies (CIT 2021) Call, grant NLESC.CIT.2021.006. Special thanks to SURF for providing valuable computational resources for `STMTools` testing.
	The authors express sincere gratitude to the Dutch Research Council (Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO) for their generous funding of the `STMTools` development through the Collaboration in Innovative Technologies (CIT 2021) Call, grant NLESC.CIT.2021.006. Special thanks to SURF for providing computational resources for `STMTools` testing.

[SarahAlidoost]

Regarding SURF acknowledgement, if the project has received a grant from SURF for using resources, the Acknowledgement text is mentioned in the grant agreement. Please use that text here.

[SarahAlidoost]

@rogerkuou thanks for preparing the draft. I left some comments. If something is unclear, please let me know.

[fnattino]

Hi @rogerkuou - thank you very much for drafting this and including me as co-author!
I have left few comments and suggestions, please consider only what you think improves the quality of the manuscript.

[fnattino]

General comments:

• Is it maybe too little information as an introduction for readers who are not familiar with the domain? I have left some open suggestions in the text below, which you could use to make things more explicit to not experts.
• This paragraph sounds like a good introduction to the scientific area of STMTools, but it does not say anything about the role of STMTools in this context? Since the focus of the paper is the software, for a "summary" section I would add one of few sentences on how the software tool integrates here. You could also choose to rename the section as "scientific domain" or something similar (I don't remember how rigid is the paper structure in JOSS).

Minor points:

• I think the STM can be better described as a "formalism" rather than a "format"?
• I have noticed the reference is not rendered properly in the PDF, is it maybe that the wrong separator is used?
• fixed a couple of typos

Suggested change

Interferometry Synthetic Aperture Radar (InSAR) is a crucial technology for monitoring ground surface deformation. It has essential value in various applications, such as civil-infrastructure stability [@chang2014detection; @chang2017railway], hydrocarbons extraction [@fokker2016application; @ZHANG2022102847], etc. To efficiently process and analyze these datasets, researchers has proposed the Space-Time Matrix (STM) format for InSAR datasets [@Bruna2021, @vanLeijen2021], which enanbles the intergration of the contextual information with the InSAR data to reveal the mechanisms driving deformation.

Interferometry Synthetic Aperture Radar (InSAR) is a crucial technology for monitoring ground surface deformation. It has essential value in various applications, such as civil-infrastructure stability [@chang2014detection; @chang2017railway], hydrocarbons extraction [@fokker2016application; @ZHANG2022102847], etc. InSAR observations typically come in the form of [...], which makes it challenging to [...]. Researchers have thus proposed the Space-Time Matrix (STM) formalism for InSAR datasets [@Bruna2021; @vanLeijen2021]. This framework consists in a representation of the data as [...]. The STM formalism facilitates the analysis of InSAR data in combination with space- and/or time-dependent datasets from other sources (the "contextual information"), by [...]. In the context of ground surface deformation, the framework [has been shown?] to facilitate the identification of the mechanisms driving deformation.

[fnattino]

What do you mean with "complex and ambiguous nature of InSAR observations"? If you refer to the phase-unwrapping problem maybe it is worth to mention it.

Suggested change

Typiclally, modern time-series InSAR methods is able to provides millions of observation points in a single dataset. However, due the complex and ambiguous nature of InSAR observations, interpretation of these datasets is challenging. [@hanssen2001radar] Under the STM framework, contextual information such as temperature, precipitation, land-use, etc. can be integrated with InSAR data. This can enable a better understanding on the driving mechanisms of the ground deformation, resulting in more reliable and accurate interpretation of the InSAR data. [@Bruna2021, @vanLeijen2021]

Typically, modern time-series InSAR methods is able to provide millions of observation points in a single dataset. However, due the complex and ambiguous nature of InSAR observations, interpretation of these datasets is challenging. [@hanssen2001radar] Under the STM framework, contextual information such as temperature, precipitation, land-use, etc. can be integrated with InSAR data. This can enable a better understanding on the driving mechanisms of the ground deformation, resulting in more reliable and accurate interpretation of the InSAR data. [@Bruna2021; @vanLeijen2021]

[fnattino]

• I have added a suggestion on the usage of Xarray datasets for contextual information - please change it if incorrect.
• On the use of Dask, does STMTools uses it directly or only via Xarray? If the former, please drop my suggestion on this topic.

Suggested change

To implement the STM format in Python, we developed the `STMTools` package. `STMTools` is developed as an extension of `Xarray`, leveraging `Xarray`'s support for labeled multi-dimensional arrays for the Space-Time concept. `STMTools` provides a set of tools to efficiently connect the InSAR data with various contextual information, such as cadastral data, weather data, etc. The package also utilizes `Dask` for parallel computing, enabling the processing of large-scale InSAR datasets.

To facilitate the analysis of InSAR datasets following the STM formalism in Python, we developed the `STMTools` package. `STMTools` is developed as an extension of the `Xarray` package, leveraging its support for labeled multi-dimensional arrays for the Space-Time dimensions. `STMTools` provides a set of tools to efficiently connect the InSAR data with various contextual information, such as cadastral data, weather data, etc. The Xarray `Dataset` data structure is used to group InSAR data and the contextual information under shared dimension coordinates (space and/or time). By building on Xarray, STMTools can also leverage `Dask` for parallel computing, enabling the processing of large-scale InSAR datasets.

[fnattino]

Maybe you could call this section as "Main functionalities", with a short list of the main functionalities of STMTools (each with a link to its tutorial).

[sonarqubecloud]

Quality Gate passed

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[rogerkuou]

Hi @fnattino and @SarahAlidoost , thanks for the review! In the end I updated the text integrating both of your suggestions. When you have time can you give another look? Thanks!