Volume IV-4/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W2, 23-30, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W2-23-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W2, 23-30, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W2-23-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2017

19 Oct 2017

APPLYING THIESSEN POLYGON CATCHMENT AREAS AND GRIDDED POPULATION WEIGHTS TO ESTIMATE CONFLICT-DRIVEN POPULATION CHANGES IN SOUTH SUDAN

L. Jordan L. Jordan
  • Spatial Data Center, Drew University, Madison, New Jersey 07940, USA

Keywords: Population Estimation, Internally Displaced Persons, South Sudan, Conflict, GIS

Abstract. Recent violence in South Sudan produced significant levels of conflict-driven migration undermining the accuracy and utility of both national and local level population forecasts commonly used in demographic estimates, public health metrics and food security proxies. This article explores the use of Thiessen Polygons and population grids (Gridded Population of the World, WorldPop and LandScan) as weights for estimating the catchment areas for settlement locations that serve large populations of internally displaced persons (IDP), in order to estimate the county-level in- and out-migration attributable to conflict-driven displacement between 2014-2015. Acknowledging IDP totals improves internal population estimates presented by global population databases. Unlike other forecasts, which produce spatially uniform increases in population, accounting for displaced population reveals that 15 percent of counties (n = 12) increased in population over 20 percent, and 30 percent of counties (n = 24) experienced zero or declining population growth, due to internal displacement and refugee out-migration. Adopting Thiessen Polygon catchment zones for internal migration estimation can be applied to other areas with United Nations IDP settlement data, such as Yemen, Somalia, and Nigeria.