This repository contains files for my lightning talk at UC GIS Week on Nov 18, 2020
In this paper, I use spatial statistics to examine if and where extreme or non-extreme political violence has occurred in Sudan since 2005. I use about 20,000 records of point data from the Armed Conflict Location Event Database (ACLED) on Sudan from the years 2005 to 2020, with each point indicating the location of a given geopolitical event in this time period. I group these data into two different point processes: 'extreme political violence' (EPV), defined as battles, explosions/remote violence, or violence against civilians (i.e. abductions, enforced disappearances, sexual violence), and 'non-extreme political violence', defined as protests, riots, and strategic developments. I then generate 15 kernel density estimates, one for each year from 2005 to 2020, of the point data to determine if there are indeed 'hotspots' of either types of political violence (extreme, and non-extreme). Finally, for each of the 15 years, I use a Monte Carlo simulation (1000 runs) of the Ripley's K-function to compare the EPV point process distribution to the null hypothesis, which was complete spatial randomness (i.e. hotspots do not exist). I draw two conclusions: 1) EPV has decreased across Sudan since 2012, and 2) there are hotspots of political violence in eastern and southern Sudan in the post CPA period. The K-function of the EPV point process deviates from the null hypothesis (i.e. no hotspots) to a statistically significant degree.
The finding that Eastern and Southern Sudan are still hotspots for political violence in the post-CPA period could be used to bolster international support for the ongoing peace process in Sudan, which has been waning with the signing of a peace agreement in August 2020. between the Sudanese government and several rebel groups in August 2020. These findings could also be used to bring in excluded rebel groups to the negotiation table, some of whom still have grievances and unmet demands.