- Since 07/2015
Scientific assistant/PhD student at the institute of geography, FSU Jena, chair in remote sensing - 2007-2014
Diploma studies of mathematics at the University Leipzig
Dipl.- Math. Felix Cremer
wissenschaftlicher Mitarbeiter
Curriculum vitae
Research Interests
- Image Processing
- Speckle Filter
- Synthetic Aperture Radar (SAR) Processing
- Time Series Analysis of Spatial Data
Projects
- Sentinel4REDDExterner Link
Utilisation of Sentinel-1/2 Data for the Delineation of REDD+ Products - HyperSense (DLR)
Publications
- Publications
2020
DUBOIS, C., MUELLER, M. M., PATHE, C., JAGDHUBER, T., CREMER, F., THIEL, C., & SCHMULLIUS, C. (2020). Characterization of land cover seasonality in Sneintle-1 time series data. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 5(3). ViewExterner Link
THIEL, C., MÜLLER, M. M., BERGER, C., CREMER, F., DUBOIS, C., HESE, S.,BAADE, J., KLAN, F. & PATHE, C. (2020). Monitoring Selective Logging in a Pine-Dominated Forest in Central Germany with Repeated Drone Flights Utilizing A Low Cost RTK Quadcopter. Drones, 4(2), 11. ViewExterner Link
CREMER, F., URBAZAEV, M., CORTES, J., TRUCKENBRODT, J., SCHMULLIUS, C. & C. THIEL (2020): Potential of Reccurrence Metrics from Sentinel-1 Time Series for Deforestation Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. ViewExterner Link.
2018
CREMER, F., URBAZAEV, M., BERGER, C., MAHECHA, M., SCHMULLIUS, C. & C. THIEL (2018): An Image Transform Based on Temporal Decomposition. IEEE Geoscience and Remote Sensing Letters, PP(99):1-5. doi:10.1109/LGRS.2018.2791658Externer Link.
URBAZAEV, M., CREMER, F., MIGLIAVACCA, M., REICHSTEIN, M., SCHMULLIUS, C. & C. THIEL (2018). Potential of Multi-Temporal ALOS-2 PALSAR-2 ScanSAR Data for Vegetation Height Estimation in Tropical Forests of Mexico. Remote Sensing, 10(8), 1277. doi:10.3390/rs10081277Externer Link.
URBAZAEV, M., THIEL, C., CREMER, F., DUBAYA, R., MIGLIAVACCA, M., REICHSTEIN, M. & C. SCHMULLIUS (2018). Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico. Carbon Balance and Management, 13(1):5. doi:10.1186/s13021-018-0093-5Externer Link.