Combining automatic and manual image analysis in a web-mapping application for collaborative conflict damage assessment

Knoth C, Slimani S, Appel M, Pebesma E

Abstract

Remote sensing is increasingly being used by non-profit organizations and international initiatives to localizeand document combat impacts such as conflict damage. Most of the practical applications rely on labor-intensiveand time-consuming manual image analysis. Even when using crowdsourcing or volunteer networks, theworkload can quickly become challenging when larger areas have to be monitored over longer time periods. Inthis paper, we propose an approach that combines automatic change detection methods with collaborativemapping in a web application for conflict damage assessment in Darfur, Sudan. Settlement areas are automaticallydetected and searched for destructed dwelling structures by geographic object-based image analysis(GEOBIA). The web application prioritizes these areas based on the detected degree of destruction to guidehuman analysts to the most important locations. In a user experiment with 30 participants we evaluated theperformance of volunteers with and without the automatic prioritization and investigated their mapping sequences.Participants who were guided by the prioritization detected 70.7% more target objects than participantsmapping without guidance, who invested parts of their mapping time in examining locations that showlittle to no destruction.