Modeling human migration patterns during drought conditions in La Guajira, Colombia

Abstract

Modeling human mobility is key for a variety of applications such as migratory flows, epidemic modeling or traffic estimation. Recently, cell phone traces have been successfully used to model aggregated human mobility, in particular during natural disasters such as earthquakes or flooding. Climate-related environmental change brings a decline of productive agricultural land and livestock which will push rural residents to migrate. As a result, it also has the potential of causing changes in human mobility and cause migrations that have a wider and long standing impact. In this study, using anonymized and aggregated cell phone traces, we model the migrations that happened during a severe drought that happened in La Guajira, Colombia, in 2014. Our results indicate a linear reduction of the population of 10 percent during the 6 months considered for this study. Furthermore, predicting these migrations has about a 60% success rate for both the total number of people that migrate and to where they migrate. We also introduce a modification of the Radiation model in order to capture weather as one of the factors driving mobility, showing a RSS and RMSE reduction of 4.5% when compared with the standard models.