Team

I am leading the PIX Group (Process-knowledge Integrating DataExploration) at DLR Institute for Data Science. My team focuses on exploiting the potential of consumer drones for forestry applications, specifically retrieving forest structural parameters using UAV imagery.

I received my engineering degree in geodesy and geoinformatics from KIT and INSA Strasbourg in 2011, and completed my Ph.D. from KIT in 2015 specializing in interferometric synthetic aperture radar (SAR) and image analysis. My background includes extensive work with SAR time series processing and modeling for forest monitoring, building on experience at the Federal Institute for Geosciences and Natural Resources, Friedrich Schiller University of Jena and on a research stay at the University of Rom “La Sapienza”.

Through this work, we contribute to a refined understanding of forest structure, providing critical data for improved modeling of hydrological processes, climate impacts, and sustainable forest management practices.

I am an associate professor at the University of Liège (ULiège, Belgium), where I lead the Earth Observation and Ecosystem Modelling (EOSystM) lab. My research focuses on understanding the interactions between the water and carbon cycles, particularly the impact of drought on forest ecosystem functioning. My team exploits new-generation satellite data streams, including active and passive microwave, hyperspectral, thermal infrared, LiDAR, and sun-induced chlorophyll fluorescence (SIF) data, to explore ecosystem dynamics and resilience to climate change.

I completed a PhD in bioscience engineering at UCLouvain (Belgium) and a postdoc at the Institute of Bio- and Geosciences, Research Center Jülich (Germany). I was also a visiting scientist at MIT and at NASA Goddard Space Flight Center.

My research integrates dynamic vegetation and radiative transfer models to study forest ecosystem functioning from spaceborne SIF data, and to derive vegetation water content and wildfire risk from vegetation optical depth (VOD). Through this work, I aim to advance our understanding of ecosystem processes and their response to environmental change.

I am a postdoctoral researcher at the Center for Ecological Research and Forestry Applications (CREAF; Cerdanyola del Vallès, Catalunya, Spain). My experience relies on the application of satellite passive microwave sensors to monitor water in soils and vegetation using soil moisture (SM) and vegetation optical depth (VOD) data. During my career I have developed fire risk assessment tools based on SMOS SM information, new metrics to assess crop yield from SMAP VOD, and new multi-frequency datasets of live fuel moisture content (LFMC) based on a novel multi-sensor (i.e., radar, lidar and radiometer) approach that disentangles the water component from the VOD signal. This research was mainly developed during my two-years work at the Microwaves and Radar Institute of the German Aerospace Center (DLR, Germany) in collaboration with the VOD4Forest team and with the MIT. Now, at CREAF, my goal is to contribute to bridge the gap between the microwave remote sensing and the ecophysiology research communities with novel estimates of water content and water potential in forests.

Dr. Thomas Jagdhuber is leading the radar signatures group at the German Aerospace Agency (DLR).His research focuses on harnessing the power of active and passive microwave remote sensing to study hydrological, ecological, and agricultural processes. By developing innovative methods to integrate data from diverse sensors, he enables precise monitoring of soil moisture, vegetation health, and cryosphere changes, under all-weather conditions. His methodological work on polarimetric decomposition techniques earned him the DLR Science Award in 2014.

A frequent visiting scientist at MIT, he has contributed significantly to NASA’s SMAP and SMAP/Sentinel-1 missions, collaborating on global water cycle research. In addition to his scientific work, Thomas is a passionate educator, serving as a lecturer at the Universities of Jena and Augsburg.

Currently, he is pursuing his habilitation at the University of Augsburg, investigating the responses of the Soil-Plant-Atmosphere System to climate change and human impacts. Through his work, Thomas Jagdhuber bridges the gap between theoretical innovation and practical solutions for a sustainable future.

Florian is a research scientist and PhD student at the University of Augsburg (UniA) and the Microwaves and Radar Institute (HR), German Aerospace Center (DLR). He is also part of the Land-Atmosphere Feedback Initiative (LAFI) project (https://www.lafi-dfg.de), founded by the German Research Foundation (DFG). In addition, he is co-founder and co-organizer of the VOD4Forest format. He is currently working on active and passive radiative transfer models to estimate vegetation optical depth (VOD) and plant water content in the canopy with a focus on agriculture and forest ecosystems using microwave remote sensing data. He is also working on the downscaling of satellite-based land surface temperature (LST) using deep learning. Basically, he is interested in understanding the soil-plant-atmosphere system holistically. In 2023, Florian graduated from the University of Jena (Germany) with an M.Sc. degree in geoinformatics with a focus on remote sensing.

Anke Fluhrer received the B.S. degree in geography from the Julius-Maximilians-University Würzburg, Würzburg, Germany, in 2014, and the M.S. degree in physical geography from the Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany, in 2018.

Since then, she is a Research Associate with the prospect of a Ph.D. at the Microwaves and Radar Institute (HR), German Aerospace Center (DLR), Weßling, Germany. Her research interests include terrestrial remote sensing, satellite image processing, geoinformation, and data assimilation.

I have a Master’s degree in Geomatics with a specialization in geo-data from the University of Liège. I am currently a teaching assistant for topography and remote sensing courses at the University of Liège, while pursuing a PhD focusing on forest inventories using remote sensing technologies and deep learning algorithms. More specifically, my research investigates how deep learning algorithms can fully exploit the information provided by remote sensing sensors to detect individual trees and extract their characteristics, in order to produce accurate forest inventories and support the monitoring and modeling of forest ecosystem dynamics.

I am a researcher at the German Aerospace Center (DLR), Institute for Data Science, with a background in remote sensing and geography. My work focuses on developing UAV- and Structure from Motion (SfM)-based workflows for environmental and infrastructure monitoring. Using very high-resolution drone imagery and point cloud analysis, I develop methods to automatically derive forest structural parameters such as stem diameters, crown dimensions, canopy gaps, and downed deadwood.

I hold a Master’s degree in Geoinformatics from the University of Jena, Germany. My research interests lie at the intersection of remote sensing, machine learning, and ecology, with a particular focus on how drone-based data can be used for forest monitoring and conservation. 

I am a PhD candidate at the German Aerospace Center (DLR) Institute of Data Science in Jena, as part of the PIX group (Process-knowledge Integrating DataExploration). I received my M.Sc. degree in Geoinformatics and Remote Sensing from the Friedrich Schiller University Jena. My research is centered on the application of unoccupied aerial vehicles (UAVs) for forestry and environmental monitoring. I specialize in optimizing UAV flight designs and using Structure from Motion (SfM) techniques to derive detailed 3D data for forest inventory tasks, such as mapping coarse wood debris and monitoring logging activities as well as coastal monitoring. My experience also includes analyzing SAR time series for monitoring land surface dynamics like evapotranspiration and forest ecosystems. Furthermore, I am interested in integrating low-cost sensor technology approaches for knowledge transfer and data collection in remote environments. Through my work, I aim to develop and apply remote sensing methodologies to provide practical data for sustainable resource management and a better understanding of infrastructure and environmental change. 

I am currently completing my Master’s degree in Geoinformatics at the Friedrich-Schiller-University Jena, Germany, where I also received my Bachelor’s degree in Geography with a focus on geoinformatics and remote sensing.

My bachelor thesis at the German Aerospace Center (DLR) Institute for Data Science examined vertical forest structure metrics using three-dimensional UAV data. I have since then worked as a student assistant at the DLR Institute for Data Science.

My previous workplaces and internships include the Max-Planck Institute of Biogeochemistry and the Thuringian State Office for the Environment, Mining and Nature Conservation. 

Through my research in drone-based remote sensing, I aim to contribute to a better understanding of ecosystem dynamics and finding sustainable solutions for forest conservation.

I am a PhD candidate at the German Aerospace Center (DLR) and the University of Augsburg. I hold an M.Sc. in Geoinformatics (2025) and work on UAV-based remote sensing with a focus on multi-sensor data integration. My research combines data from radar, hyperspectral, multispectral, LiDAR, and thermal sensors to better characterize soil and land-surface processes. Within the DFG Research Unit Land-Atmosphere Feedback Initiative (LAFI), I design and coordinate UAV flight campaigns and work on integrating multi-sensor datasets collected over agricultural systems. I am particularly interested in combining the strengths of different sensors to improve the reliability of environmental data. Alongside my research, I also work with thermal UAV systems in applied contexts such as wildlife monitoring, including fawn rescue. My background in remote sensing was further shaped during a one-year research stay at the University of Tasmania, where I focused on vegetation classification.