blackmarblepy 0.2.0

Georeferenced Rasters of Nighttime Lights from NASA Black Marble data

BlackMarblePy

BlackMarblePy provides a simple and efficient way to retrieve and extract nighttime lights data from NASA's Black Marble project. Black Marble is a NASA Earth Observatory 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 archive to cover a region of interest, converting the raw files (in HDF5 format), to georeferenced rasters, and mosaicing rasters together when needed.

Features

• Download daily, monthly, and yearly nighttime lights data for user-specified region of interest and time range.
• 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 like mean and sum.
    • Plot time series of nighttime lights data.

Installation

BlackMarblePy is available on PyPI as blackmarblepy and can installed using pip:

pip install blackmarblepy

Usage

Before downloading and extracting Black Marble data, define the NASA LAADS archive bearer token, and define a region of interest (i.e., gdf as a geopandas.GeoDataFrame).

from blackmarble.raster import bm_raster

# Raster stack of daily data
date_range = pd.date_range("2022-01-01", "2022-03-31", freq="D")

# Retrieve VNP46A2 for date range into a Xarray Dataset
daily = bm_raster(
    gdf,
    product_id="VNP46A2",
    date_range=date_range,
    bearer=bearer,
)

For more detailed information and examples, please refer to the documentation.

Contributing

Contributions are welcome! If you'd like to contribute, please follow our contribution guidelines.

License

This project is open-source - see the LICENSE file for details