BlackMarblePy Submission

[g4brielvs]

Submitting Author: Gabriel Stefanini Vicente (@g4brielvs) All current maintainers: @g4brielvs, @ramarty Package Name: BlackMarblePy One-Line Description of Package: Georeferenced Rasters and Statistics of Nightlights from NASA Black Marble Repository Link: https://github.com/worldbank/blackmarblepy Version submitted: v2024.8.1 EiC: @cmarmo Editor: @yeelauren Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD JOSS DOI: TBD Version accepted: TBD Date accepted (month/day/year): TBD

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Description

BlackMarblePy is a Python package that provides a simple way to use nighttime lights data from NASA’s Black Marble project. Black Marble is a NASA Earth Science Data Systems (ESDS) project that provides a product suite of daily, monthly and yearly global nighttime lights. This package automates the process of downloading all relevant tiles from the NASA LAADS DAAC to cover a region of interest, converting the raw files (in HDF5 format), to georeferenced rasters, and mosaicking rasters together when needed.

Scope

• Please indicate which category or categories. Check out our package scope page to learn more about our scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • [x] Data retrieval
  • [ ] Data extraction
  • [x] Data processing/munging
  • [ ] Data deposition
  • [ ] Data validation and testing
  • [ ] Data visualization[^1]
  • [ ] Workflow automation
  • [ ] Citation management and bibliometrics
  • [ ] Scientific software wrappers
  • [ ] Database interoperability

Domain Specific

• [x] Geospatial
• [ ] Education

Community Partnerships

• For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

  • Who is the target audience and what are scientific applications of this package? The target audience for BlackMarblePy includes researchers, scientists, and analysts working in the fields of urban studies, environmental science, and socio-economic research. The package facilitates access to NASA's Black Marble nighttime lights data, enabling applications such as monitoring urban growth, assessing the impact of natural disasters, and studying human activities' influence on the environment.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ? While there are other Python packages that provide access to satellite imagery and remote sensing data, BlackMarblePy is specifically tailored for NASA's Black Marble nighttime lights data. It offers a more streamlined and efficient way to retrieve, process, and analyze this particular dataset, providing functionalities and tools optimized for nighttime lights research.

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

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The review template can be found here.

[cmarmo]

Hi @g4brielvs , thank you for submitting BlackMarblePy to pyOpenSci. I'm Chiara, currently serving as Editor In Chief. I just want to let you know that I'm going to perform the first checks on the package ASAP, hopefully by the end of the month. Thanks for your patience!

[g4brielvs]

Hi Chira (@cmarmo)! Thank you for your message and for taking the time to review BlackMarblePy. I appreciate the update and look forward to any feedback you may have.

[cmarmo]

Editor in Chief checks

Hi @g4brielvs ! Thank you for submitting your package for pyOpenSci review. Sorry for taking so much time to come back to you.

Below are the basic checks that your package needs to pass to begin our review. If some of these are missing, we will ask you to work on them before the review process begins.

Please check our Python packaging guide for more information on the elements below.

• [x] Installation The package can be installed from a community repository such as PyPI (preferred), and/or a community channel on conda (e.g. conda-forge, bioconda).
  • [x] The package imports properly into a standard Python environment import package.
• [x] Fit The package meets criteria for fit and overlap.
• [x] Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
  • [x] User-facing documentation that overviews how to install and start using the package.
  • [x] Short tutorials that help a user understand how to use the package and what it can do for them.
  • [x] API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
• [x] Core GitHub repository Files
  • [x] README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
  • [x] Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
  • [x] Code of Conduct The package has a CODE_OF_CONDUCT.md file.
  • [x] License The package has an OSI approved license. NOTE: We prefer that you have development instructions in your documentation too.
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• [x] Package overlap The package doesn't entirely overlap with the functionality of other packages that have already been submitted to pyOpenSci.
• [ ] Archive (JOSS only, may be post-review): The repository DOI resolves correctly.
• [ ] Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

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• [x] Initial onboarding survey was filled out We appreciate each maintainer of the package filling out this survey individually. :raised_hands: Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. :raised_hands:

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Editor comments

Below my comments about the unchecked boxes up there, and some others related to more general questions.

• While the examples in the documentation are valuable answers to some of the questions in the submission form, the audience of the package and the possible scientific applications haven't been detailed. Also a comparison with other similar packages (if any) is missing. Do you mind adding some details about that in the submission form or as a follow-up discussion in the issue?
• The documentation contains an API section but I couldn't easily find it because its title is "blackmarble package" rather than eg "blackmarble API" or "blackmarble package API", do you mind making the section title more explicit?
• The Code of conduct has been added via a github template? The file itself is missing, then the link in the CONTRIBUTING.md gives a "404 not found".
• While looking for the API chapter in the documentation sources, I realized that you are using google analytics to monitor the documentation. Please note that google analytics needs cookie consent for European General Data Protection Regulation and specific configuration for California Consumer Privacy Act. Before starting the review do you mind adding a cookie consent banner or switching to another service GDPR and CCPA compliant (eg plausible https://plausible.io/)?
• I couldn't find your pre-review survey... perhaps something went wrong during its submission. Do you mind refilling it? This helps us track submission and improve our peer review process.

[g4brielvs]

@cmarmo Thank you so much for reviewing BlackMarblePy. The issues raised on your comments have been addressed. Please let us know if you have any additional feedback or there is anything I can do to help.

[cmarmo]

Thank you @g4brielvs ! I believe we are ready to seek for an editor. I wonder if you can tag this last version and update the "submitted version" in the description, so your last modifications are transparent for the reviewers. Thank you so much!

[g4brielvs]

Thank you @g4brielvs ! I believe we are ready to seek for an editor. I wonder if you can tag this last version and update the "submitted version" in the description, so your last modifications are transparent for the reviewers. Thank you so much!

@cmarmo Thanks so much! And absolutely. I just created the v2024.08.1 release. Please let us know if there is anything we can do to help.

[cmarmo]

Hello @g4brielvs, I am glad to announce that @yeelauren kindly accepted to serve as editor for the BlackMarblePy submission. Thank you so much Lauren!

I'm letting Lauren introduce herself here and wishing to you all a happy review process! :tada:

[g4brielvs]

Thank you for the update @cmarmo @lwasser! Welcome, @yeelauren, and thank you for taking on the role of editor for the BlackMarblePy submission. I’m looking forward to working with you throughout the review process. If there’s anything you need from me or any way I can assist, please don’t hesitate to reach out.