Remote sensing-based mapping of the destruction to Aleppo during the Syrian Civil War between 2011 and 2017

Abstract

Accurate assessment of damage caused by conflict can be difficult to determine from ground-based surveys, particularly in the context of violence and unsafe conditions. Earth Observation data provides a non-invasive method for rapid damage assessment over wide geographic areas. In this study we use Landsat Imagery captured between 2011 and 2017 to assess the damage in Aleppo, Syria caused by conflict during the Syrian Civil War. Extracting temporal changes in urban environments is complex and the capabilities of traditional spectral-based methodologies are limited. We examined the effectiveness of the Gray-Level Co-Occurrence Matrix (GLCM) and two texture-based metrics (correlation and homogeneity) at classifying changes in reflectance characteristics within urban environments caused by building damage and consequent changes in surface orientation. Homogeneity was a more effective texture measure than correlation (overall accuracy of 79% vs 50%). Results indicated that between 45% and 57% of Aleppo was damaged during the study period, including up to 57% of former rebel held areas and between 34% and 46% of government areas and their surrounds. We used SPOT-6 imagery for accuracy assessment. Damage to Aleppo has yet to be fully quantified and several parts of the city remain unsafe and inaccessible. The results of this study highlight the potential offered by texture analysis for mapping damage to urban areas with freely available imagery and can be readily applied to natural disasters such as earthquakes and the aftermath of extreme weather events.