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https://github.com/worldbank/blackmarblepy
Georeferenced Rasters and Statistics of Nightlights from NASA Black Marble
https://github.com/worldbank/blackmarblepy
blackmarble datapartnership nasa nasa-data nasa-earth-data nightlights nighttime-lights raster-data viirs worldbank zonal-statistics
Last synced: 4 days ago
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Georeferenced Rasters and Statistics of Nightlights from NASA Black Marble
- Host: GitHub
- URL: https://github.com/worldbank/blackmarblepy
- Owner: worldbank
- License: mpl-2.0
- Created: 2023-10-26T09:17:26.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-10-07T20:46:03.000Z (about 1 month ago)
- Last Synced: 2024-10-29T19:58:02.342Z (15 days ago)
- Topics: blackmarble, datapartnership, nasa, nasa-data, nasa-earth-data, nightlights, nighttime-lights, raster-data, viirs, worldbank, zonal-statistics
- Language: Jupyter Notebook
- Homepage: https://worldbank.github.io/blackmarblepy/
- Size: 24.4 MB
- Stars: 31
- Watchers: 10
- Forks: 5
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
- Contributing: docs/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: docs/CODE_OF_CONDUCT.md
- Security: docs/SECURITY.md
Awesome Lists containing this project
README
# BlackMarblePy
[](https://opensource.org/licenses/MPL-2.0)
[](https://badge.fury.io/py/blackmarblepy)
[](https://github.com/worldbank/blackmarblepy/actions/workflows/gh-pages.yml)
[](https://github.com/worldbank/blackmarblepy/actions/workflows/tests.yml)
[](https://results.pre-commit.ci/latest/github/worldbank/blackmarblepy/main)
[](https://zenodo.org/doi/10.5281/zenodo.10667907)
[](https://colab.research.google.com/github/worldbank/blackmarblepy/blob/main/notebooks/blackmarblepy.ipynb)
[](https://pepy.tech/project/blackmarblepy)
[](https://github.com/worldbank/blackmarblepy)
**BlackMarblePy** is a Python package that provides a simple way to use nighttime lights data from NASA's Black Marble project. [Black Marble](https://blackmarble.gsfc.nasa.gov) is a [NASA Earth Science Data Systems (ESDS)](https://www.earthdata.nasa.gov) project that provides a product suite of daily, monthly and yearly global [nighttime lights](https://www.earthdata.nasa.gov/learn/backgrounders/nighttime-lights). This package automates the process of downloading all relevant tiles from the [NASA LAADS DAAC](https://www.earthdata.nasa.gov/eosdis/daacs/laads) 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](https://blackmarble.gsfc.nasa.gov) as a [xarray.Dataset](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html)
- 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 like mean and sum.
- Plot time series of nighttime lights data.
## Documentation
The [**BlackMarblePy**](https://pypi.org/project/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](https://pypi.org) as [blackmarblepy](https://pypi.org/project/blackmarblepy) and can installed using `pip`:
#### From PyPI
```shell
pip install blackmarblepy
```
#### From Source
1. Clone or download this repository to your local machine. Then, navigate to the root directory of the repository:
```shell
git clone https://github.com/worldbank/blackmarblepy.git
cd blackmarblepy
```
2. Create a virtual environment (optional but recommended):
```shell
python3 -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
```
3. Install the package with dependencies:
```shell
pip install .
```
Install the package **in editable** mode with dependencies:
```shell
pip install -e .
```
The `-e` flag stands for "editable," meaning changes to the source code will immediately affect the installed package.
#### Building Documentation Locally
To build the documentation locally, after (1) and (2) above, please follow these steps:
- Install the package with documentation dependencies:
```shell
pip install -e .[docs]
```
- Build the documentation:
```shell
sphinx-build docs _build/html -b html
```
The generated documentation will be available in the `_build/html` directory. Open the `index.html` file in a web browser to view it.
### Usage
Before downloading and extracting Black Marble data, define the [NASA LAADS archive](https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5000/VNP46A3/) `bearer` token, and define a region of interest (i.e., `gdf` as a [`geopandas.GeoDataFrame`](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.html)).
```python
from blackmarble.raster import bm_raster
# Retrieve VNP46A2 for date range into a Xarray Dataset
daily = bm_raster(
gdf,
product_id="VNP46A2",
date_range=pd.date_range("2022-01-01", "2022-03-31", freq="D"),
bearer=bearer,
)
```
For more detailed information and examples, please refer to the [examples](https://worldbank.github.io/blackmarblepy/notebooks/blackmarblepy.html).
### Full API Reference
For a full reference of all available functions and their parameters, please refer to the [official documentation](api/blackmarble.rst).
## 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](CONTRIBUTING.md).
### Feedback and Issues
If you have any feedback, encounter issues, or want to suggest improvements, please [open an issue](https://github.com/worldbank/blackmarblepy/issues).
### Versioning
[](https://calver.org)
This project follows the [CALVER](https://calver.org) (Calendar Versioning) scheme for versioning. If you have any questions or need more information about our versioning approach, feel free to ask.
### Contributors
This project follows the [all-contributors](https://allcontributors.org) specification.
Contributions of any kind are welcome!
Gabriel Stefanini Vicente
Robert Marty
## Citation
When using **BlackMarblePy**, your support is much appreciated! Please consider using the following citation or download [bibliography.bib](https://raw.githubusercontent.com/worldbank/blackmarblepy/main/docs/bibliography.bib):
```bibtex
@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`
```{bibliography}
:filter: docname in docnames
:style: plain
```
## License
This projects is licensed under the [**Mozilla Public License**](https://opensource.org/license/mpl-2-0/) - see the **LICENSE** file for details.