BRAIN initiative notes

To visualize the nighttime lights of Eastern Europe, with a focus on times before and after the ongoing Russia-Ukraine conflict, I updated [...]my geoSatView R code originally built to view forest fires in the west coast of the United States to use satellite data from VNP46A1 and other datasets collected from the Suomi NPP VIIRS satellite.

I then created higher-quality movies in MATLAB by using the VNP46A2 Black Marble dataset collected by the same satellite, which has reduced cloud and other artifacts due to additional data processing. This allowed me to quantitate a permanent reduction in nighttime lights within Ukraine (in line with my initial hypothesis) and identify a multi-stage reduction of nighttime lights in Kiev's outer neighborhoods/metropolitan area that was greater than that seen in the city core/center. This highlights the utility of public satellite data to quickly test hypotheses and visualize large-scale changes.

I will go over how the Black Marble dataset is collected and processed along with how I created the movies and the advantages/disadvantages of each data source.

Using this platform and codebase, in follow-up posts I will look at 2021 Texas power crisis during the winter storms, vegetation changes in deforested areas or after conservation efforts, and other events.