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Published 20 hours ago • verified publisher icon pyOpenSci

BlackMarblePy Submission

Open g4brielvs opened this issue 7 months ago • 9 comments

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

Code of Conduct & Commitment to Maintain Package

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:

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

  • [x] does not violate the Terms of Service of any service it interacts with.
  • [x] uses an OSI approved license.
  • [x] contains a README with instructions for installing the development version.
  • [x] includes documentation with examples for all functions.
  • [x] contains a tutorial with examples of its essential functions and uses.
  • [x] has a test suite.
  • [x] has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

JOSS Checks
  • [ ] The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
  • [ ] The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • [ ] The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • [ ] The package is deposited in a long-term repository with the DOI:

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

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  • [x] Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

  • [x] I have read the author guide.
  • [x] I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

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g4brielvs avatar Jul 18 '24 14:07 g4brielvs