31 August 2020, Geneva, Switzerland - Over the summer, UNOSAT introduced an Artificial Intelligence (AI) based method in its operational emergency mapping service. By reducing the process to a fraction of the time normally needed.

"This fully automated processing method is a game changer for humanitarian rapid mapping operations and a  great tool for national disaster management authorities”, Einar Bjørgo, Director, UNOSAT.

Thanks to its extensive experience in rapid mapping, UNOSAT has collected a vast library of historical flood datasets, which are extremely useful to develop machine learning-based methods. By using AI, satellite based analysis and related mapping are completed in considerably less time and the process is almost fully automated. This not only informs the decision-making process to help optimize the disaster response, it also has the potential to significantly reduce loss of life and mitigate structural damage, particularly in the context of humanitarian operations, thus supporting both national authorities and international emergency management organizations for the benefit of local populations. 

“The use of AI for flood detection enables the analysis and processing of large quantities of images in a short time span, which allows for better analysis and wider geographic coverage” Samir Belabbes, UNOSAT

During the past year, UNOSAT’s team, in collaboration with Wuhan University and UN Global Pulse, trained machines extensively to process satellite images and detect water much more rapidly in comparison to semi-automatic methods. With this new approach, radar images from the European Space Agency (ESA) [1] are automatically downloaded, orthorectified and processed by UNOSAT’s AI model to output disaster maps, with limited need for human intervention.

In recent months, UNOSAT’s Rapid Mapping Service has been monitoring the situation related to seasonal rains and potential floods in the Asia-Pacific region with a particular focus on countries potentially affected by the southwest monsoon season that runs from June to September 2020. In this context, we ran the AI algorithm for the first time in July 2020 for operations in Bangladesh.

UNOCHA, in close coordination with other UN entities and the Bangladesh authorities, contacted UNOSAT on 13th July 2020 to assess the needs after monsoon rains flooded a large part of the country, in particular along the Brahmaputa river and in the northeastern parts of the country in the Sylher district. To respond to this activation UNOSAT decided to trigger the International Charter: Space and Major Disasters, and applied both automated and semi-automated analysis methods.

Take a look at the webmap for this activation.