Ph.D. student in the WetlandHealth4UNGoals project, specializing in quantitative optical remote sensing to monitor vegetation stress indicators and evaluate ecosystem services and wetland health in the context of global sustainability goals. His work focuses on developing remotely sensed and validated data products, including plant traits such as leaf area index, crown chlorophyll content, drought stress, and available water content.

Martin serves as the Project Manager of the SPEAR project at ZFL. Until recently he worked as ZFL's counterpart and close collaborator as Junior Professional Officer at the UN-SPIDER’s Bonn Office. In his position at ZFL, he oversees the collaboration efforts with UN-SPIDER. He is specialized in the work with geoinformation and remote sensing for natural hazards and while working with the project, he will work on his PhD thesis in the context of flood modeling and mapping with Earth observation methods in cloud computing environments.

Josephine is a Ph.D. student specialising in flood early warning systems and data-driven hydrological modelling in the White Volta basin of Ghana. Her research focuses on assessing the effectiveness and limitations of existing flood forecasting frameworks, integrating traditional knowledge, and improving institutional coordination for disaster risk reduction. As part of her work, she evaluates the accuracy of satellite and reanalysis datasets, such as CHIRPS, PERSIANN-CDR, ARC2, MERRA-2, ERA5, and CFSR, for streamflow forecasting and water resource management in data-scarce regions. She also applies machine learning models, including Long Short-Term Memory (LSTM) and Random Forest (RF), to predict short- and medium-term streamflow and assess future flood risks under CMIP6 climate scenarios. Her research bridges operational hydrology, remote sensing, and climate adaptation to support sustainable and proactive flood management strategies.

Guest researcher at the Center for Remote Sensing of Land Surfaces (ZFL), specializing in the application of remote sensing technologies to study natural hazards. His research includes modeling landslides using multi-spectral satellite data, exploring their spatial dynamics, and assessing their impact on human infrastructure, including transportation networks, buildings, and essential services. By integrating advanced geospatial techniques and data analytics, his work aims to enhance early warning systems and contribute to risk mitigation strategies for communities vulnerable to these hazards