About
Christian is with the team “Modeling and geostatistical analysis” at the German Aerospace Center (DLR). He worked on several topics related to renewable energy, earthquake risk assessment, and methods for remote sensing data processing. His current research interests include techniques of multimodal remote sensing, machine learning, and pattern recognition, specifically applied to the field of natural hazard risk research.
Dr. Christian Geiss, DLR-EOC
Recent News
book: Remote Sensing and GIS for Ecologists
The book "remote sensing and GIS for ecologists - using Open Source software" edited by the EAGLE lecturer Martin Wegmann is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the...
MSc opportunities: remote sensing in ecology and conservation
Biodiversity analysis and conservation decision relies on adequate and meaningful data that are available on a long-term and global basis. Such environmental information need adequate spatial and temporal resolution and remote sensing data does provide a wide range...
MSc handed in on impact of remote sensing for biodiversity monitoring
Anna Stephanie handed in her MSc thesis on “Impact of remote sensing characteristics for biodiversity monitoring”. Very impressive study on multi-scale, multi-model and multi-variable analysis of mangroves in Myanmar. She was supervised by Martin Wegmann. While...
MSc handed in on object-oriented classification of historical maps for ecosystem services
Yrneh Ulloa handed in her MSc “Land change in the Main catchment with an Object Based approach using eCognition” within GCE which dealt with classifying landcover in historical maps (1810+) automatically using object oriented approaches. She was supervised by Martin...
MSc: Analysis of Airborne LiDAR Data for Deriving Terrain and Surface Models
The M.Sc thesis by Raja Ram Aryal has been handed in (supervision of Dr. Hooman Latifi and Prof. Michael Hahn). The thesis focused on a comparative study on the variations of an adaptive TIN ground filtering algorithm to extract DTM from discrete LiDAR point cloud...
MSc: predicting forest understory canopy cover
The M.Sc thesis by Bastian Schumann focused on a LiDAR-based approach to combine structural metrics and forest habitat information for causal and predictive models of under-story canopy cover. The data base used consisted of a bi-temporal LiDAR dataset as well as two...
Explore species-environment interaction
Analyzing species-environment interaction is feasible using various data and method. An increasing technology is the tracking of animals and especially its linkage to remote sensing, as covered in AniMove.org. However, with this technology new challenges have to be...
MSc by Asja Bernd: “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data”
The MSc thesis by Asja Bernd titled “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data” is handed in. Very interesting results on global grassland fragmentation. Read the abstract:Around the world, grassland and savannah...
MSc on deforestation in Myanmar and its drivers
The MSc by Andrea Hess “Deforestation in Myanmar – what can we say about causes?” has been handed in. It has been supervised by Peter Leimgruber (Smithsonian Conservation Biology Institute) and Martin Wegmann. Deforestation in the tropics is a global issue. Tropical...
Deployment of a multi-classifier approach to improve land cover classification accuracy
This study will examine whether the application of hybrid classifiers increases the classification accuracy in comparison to a single classifier. A combination between parametric and non-parametric classifiers will be applied and their performance will be assessed....