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Master's thesis using Google Earth Engine and D3 with World Development Indicators and Landsat satellite data.
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README.md

Vegetation and Socioeconomic Shifts in sub-Saharan Africa

preview.png Presentation Video: https://www.youtube.com/watch?v=f0jNYwPMeYE

Vegetation indices derived from satellite flyover data tend to correlate with GDP, particularly in agrarian economies. This analysis explores the linkages between agricultural policymaking, land usage patterns/vegetation shifts, and economic output in sub-Saharan Africa. By aggregating thousands of sequential satellite measurements taken by Landsat 5, 7, and 8 between 1990 and present-day, this study constructs a normalized difference vegetation index (NDVI) using Google Earth Engine servers. Agricultural classification and geospatial masking are specified by the author.

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