BlackMarblePy

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.

Features

• Download daily, monthly, and yearly nighttime lights data for user-specified region of interest and time.
• Parallel downloading for faster data retrieval and automatic retry mechanism for handling network errors.
• Access NASA Black Marble as a xarray.Dataset
  • Integrated data visualization with customization options
    • Choose between various plot types, including bar charts, line graphs, and heatmaps.
    • Customize plot appearance with color palettes, axes labels, titles, and legends.
    • Save visualizations as high-resolution images for presentations or reports.
  • Perform time series analysis on nighttime lights data.
    • Calculate zonal statistics (via exactextract).
    • Plot time series of nighttime lights data.

Documentation

The BlackMarblePy library allows you to interact with and manipulate data from NASA's Black Marble, which provides global nighttime lights data. Below is a guide on how to use the key functionalities of the library.

Installation

BlackMarblePy is available on PyPI. To install, it is recommended to use virtual environment and package manager. While pip is the usual choice, we recommend using uv.

Using pip

pip install blackmarblepy

Using uv (recommended)

uv add blackmarblepy

Usage

BlackMarblePy requires a NASA Earthdata token for authenticated access to the NASA LAADS archive. To obtain a token, log in or register at Earthdata Login and generate a personal access token from your Earthdata profile.

Before downloading or extracting NASA Black Marble data, ensure the following:

• You have defined a region of interest gdf as a geopandas.GeoDataFrame, which represents the area over which data will be queried and downloaded.
• You have a valid and not expired token set (retrieved from your Earthdata profile). For convenience and security, we recommend setting your token as an BLACKMARBLE_TOKEN environment variable. If not familiar with environment variables, you may pass the token directly as the token argument.

import geopandas as gpd

from blackmarble import BlackMarble, Product

# ------------------------------------------------------------------------------
# 1. Define your region of interest
# ------------------------------------------------------------------------------
# In this example ,we load a region from a GeoJSON.
gdf = gpd.read_file("path/to/your/shapefile.geojson")

# ------------------------------------------------------------------------------
# 2. Set up the BlackMarble client
# ------------------------------------------------------------------------------
# If the environment variable `BLACKMARBLE_TOKEN` is set, it will be used automatically.
# You can also pass your token directly, but using the environment variable is recommended.
bm = BlackMarble(token="YOUR_BLACKMARBLE_TOKEN")

# ------------------------------------------------------------------------------
# 3. Download VNP46 data from NASA Earthdata
# ------------------------------------------------------------------------------
# In this example, we request the VNP46A2 product for a specific date.
# The data is returned as an xarray.Dataset.
raster_earth_day = bm.raster(
    gdf,
    product_id=Product.VNP46A2,
    date_range="2026-04-22",
)

Alternatively, you can use the procedural procedural interface to retrieve NASA Black Marble data. All data are sourced from the NASA Black Marble project, specifically from the VNP46 product suite (e.g. VNP46A4). For more detailed information and examples, please refer to the examples.

Full API Reference

For a full reference of all available functions and their parameters, please refer to the official documentation.

Contributing

We welcome contributions to improve this documentation. If you find errors, have suggestions, or want to add new content, please follow our contribution guidelines. Please see also .

Feedback and Issues

This project welcomes contributions of any kind! If you have any feedback, encounter issues, or want to suggest improvements, please open an issue.

Versioning

This project follows the YYYY.0M.MICRO CALVER scheme for versioning. If you have any questions or need more information about our versioning approach, feel free to ask.

Citation

When using BlackMarblePy, your support is much appreciated! Please consider using the following citation or download bibliography.bib:

@misc{blackmarblepy,
  title = {{BlackMarblePy: Georeferenced Rasters and Statistics of Nighttime Lights from NASA Black Marble}},
  author = {Gabriel {Stefanini Vicente} and Robert Marty},
  year = {2023},
  howpublished = {\url{https://worldbank.github.io/blackmarblepy}},
  doi = {10.5281/zenodo.10667907},
  url = {https://worldbank.github.io/blackmarblepy},
}

{cite:empty}blackmarblepy

:filter: docname in docnames
:style: plain

Related Projects

Looking for an R implementation? Check out the blackmarbler package, which provides similar functionality for working with NASA Black Marble data in R.

License

This project is licensed under the MIT License together with the World Bank IGO Rider. The Rider is purely procedural: it reserves all privileges and immunities enjoyed by the World Bank, without adding restrictions to the MIT permissions. Please review both files before using, distributing or contributing.