Analyzing Night Lights for Global Development

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We introduce R and Python packages developed by the Development Impact Evaluation Department (DIME) and Data Lab at the World Bank — blackmarbler for R and blackmarblepy for Python. These packages are designed to streamline the process of accessing NASA's Black Marble, offering functions to retrieve and process the data for analysis, particularly in cases where GEE may not be suitable. The two main functions provided by these packages — bm_raster and bm_extract — enable to download and extract zonal statistics of nighttime lights data for specified regions and date ranges.

• blackmarbler for R
• blackmarblepy for Python

📊 Key Takeaways

• Explore the capabilities of NASA's Black Marble and its correction algorithms.
• Learn about the challenges and nuances in utilizing nighttime lights data.
• Access the Black Marble data from 2012 to the present and convert it into an analysis-ready format.