Jupyter Notebook for Creating Light Pollution Map from Drone Imagery

**This file disables decompresion bomb protection due to the large amount of pixels within the mosaicked drone imagery. **The first portion of this code may take an extended amount of time. Includes print statements for progress. This code takes mosaicked imagery and creates multiple light pollution maps. This method classifies pixel brightness values relative to the distribution within the study area. Instead of using absolute luminance units, each pixel is assigned to a percentile range, allowing us to highlight areas that are unusually bright compared to the rest of campus. Because the classification is relative, the results cannot be applied as universal light pollution standards, but they are highly effective for identifying local hotspots.