Methodology

Case Study Quantitative Assessment Methods
Flowchart describing methods used in the quantitative part of the research.

The number of fires is derived from remote sensing data, which describes daily thermal anomalies indicative of fires, day or night, on a global scale. This data is produced at a 1 km spatial resolution by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Active Fire (AF) product. The data is available in a user-friendly CSV format on the Global Fire Emissions Database (GFED) https://www.globalfiredata.org/, a well-known, open-source, database of fire accounts. GFED’s analysis tool can be used to subset the data for a specific time and area of interest. For the coordinate location of the fires, data is directly subsetted and downloaded using the USGS Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) https://lpdaacsvc.cr.usgs.gov/appeears/.

The conflict data is available from the Uppsala Conflict Data Program (UCDP) https://www.pcr.uu.se/research/ucdp/ucdp-data/, a well-known, open-source program for providing standardized data on conflict events. Each conflict event in this dataset is defined as an instance of organized violence with at least one fatality. According to Sundber and Melander (2013), the conflict data are mined from news sources, governmental and non-governmental organization reports, case studies, historical archives, and other sources. The conflict data is also geo-referenced, and coordinate locations are obtained from sources such as the GEOnet Names Server database (GNS), or maps provided by various non-profit organizations. The data are then run through a series of checks for quality and consistency between data sources. The resulting conflict data provides the frequency and spatial distribution of conflict for the area of interest.

The trends of the conflict and fire data are visualized using the moving average smoothing function to get rid of small variations in the data, or noise, and to observe the patterns at large. This data is then evaluated in the context of political instability and conflict. Finally, to understand the relationship between the conflicts and the fires, statistical analysis is used.