Detecting the Destruction of Populated Sites in Northeastern Nigeria from Sentinel-2 Satellite Imagery by EfficientNet

Abstract

The Boko Haram Insurgency, a religious conflict in northeastern Nigeria, has caused around 350000 deaths and destroyed numerous populated sites in the past decade. This research used Sentinel-2 data and point data of populated sites with their status information (Functional or Destroyed) collected by Copernicus Emergency Management Service as input to train an image classification model, EfficientNet, to detect the status of the populated sites in this region. The research tested the influence of two hyperparameters (patchsize and the number of neurons in a fully connected layer) and two types of preprocessed imagery data to explore the potential of this approach for this detecting task. The results turn out the developed approach produces the highest F1-score of 0.8197 for destroyed populated sites when the model is trained with NDVI data, the patchsize is 1100m, and the number of FC neurons is 512. The results prove this approach has a high potential for long-term peace monitoring and humanitarian operations in this region.