An Overview of Earth Observation Resources and Services for Landslide Detection in Humanitarian Contexts

Landslides cause numerous fatalities and extensive infrastructure damage every year, resulting in human and economic losses. Climate change and its cascading impacts are increasing both the frequency and magnitude of landslides, rockfalls, and debris flows. Humanitarian organisations, such as Médecins Sans Frontières (MSF), play a crucial role in disaster response, where timely, reliable, and up-to-date information is essential for effective hazard and damage assessments, as well as for coordinating rescue operations and humanitarian aid. 

Earth observation (EO) data and technologies have demonstrated strong potential for supporting emergency response and disaster risk management following landslide events. However, despite continuous methodological advances in academic research, EO-based approaches are rarely tested under real operational conditions, such as direct support to humanitarian organisations during ongoing emergencies. In addition, many existing solutions do not adequately address the specific user requirements and information needs that arise at different stages of the disaster cycle. This study therefore aims to generate targeted EO-based landslide information tailored to the operational needs of humanitarian aid. The landslides triggered by Tropical Cyclone Freddy in Malawi in 2023 are used as an illustrative example to demonstrate typical information needs and constraints during real emergency situations. 

We test and evaluate a range of landslide mapping tools and methods based on optical and radar satellite data, focusing on the detection, delivery, accuracy, and communication of landslide information for humanitarian applications. The approaches are assessed under typical emergency constraints, including processing time, limited data availability, unstable connectivity, and unsafe field conditions. Suitable methods are identified and customised in close alignment with MSF’s operational requirements. To enhance usability and impact, EO-derived results are combined with principles of risk communication, supporting humanitarian staff in interpreting and applying landslide information during response operations. Thus, this work contributes to bridging the gap between scientific EO research and practical humanitarian applications.