The refugee population is growing rapidly. Recent estimates from the United Nations indicate that nearly 68 million people fled their homes in 2016, up from 64 million in the previous year. Often located near war zones, the largest camps hold more than 200,000 people. When essential services such as food, clean water and sanitation are in short supply, malnutrition and sickness can take hold. Financial and material support is limited, though, and a camp's infrastructure is often overtaxed. Because of their limited funding, NGOs have become adept at planning and resource allocation. Information on population size and trends for a given camp helps the NGOs to optimise the return on their spending. Producing good data, however, is not easy. Aircraft - including unmanned aerial vehicles (UAVs or 'drones') -and satellites can capture aerial images of the camps, but manually extracting reliable population data from these photos can be painfully slow and expensive. Medecins Sans Frontieres (MSF), an NGO supporting refugee camps, teamed up with experts at the University of Salzburg's Department of Geoinformatics (Z_G/S) to find a solution. Z_GIS conducts research into the use of satellite imagery with advanced image processing techniques to monitor populations. One of its key objectives is developing automated approaches to extract population information from satellite images of refugee camps.
展开▼
