Max Planck Gesellschaft
Felix Cremer


PhD student in Remote Sensing
Biosphere-Atmosphere Interactions and Experimentation and
Hydrology Biosphere Climate Interactions groups

room: C*.*** (tower)
phone: +49 3641 57****
fax: +49 3641 57****
email: fcremer(at)bgc-jena.mpg.de

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Research interests | Current Research | Past Research | Publications


Research Interest:

  • Sentine-1 Time series
  • Datacubes for high resolution earth observation data

Current Research:

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Past Research:

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Publication

Peer-reviewed

2020

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. View

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. View.

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.2018.2791658.
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/rs10081277.
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/s13021-018-0093-5.

Conference Contribution

Dubois, C., Müller, M. M., Pathe, C., Jagdhuber, T., Cremer, F., Thiel, C., & Schmullius, C. (2020). Characterization of land cover seasonality in Sentinel-1 time series data. ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, 5(3). View

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