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Due to the current situation, the offices are currently not staffed. However, the department is reachable via email.


research colloquium WiTe 20/21

15:30 - via Zoom

  Christian Schulz
(TU Berlin)
  TreeSatAI - Anwendung von Deep Learning Techniken für das Vegetationsmonitoring?  
  Femke van Geffen (awi)  
  Vegetation dynamics in central Yalutia, Siberia - Changes in distribution and dynamics over the last 20 years  
  Tobias Gränzig (TU Berlin)
  Mapping the vegetation fractional cover of the invasive shrub Ulex europaeus with multi-temporal Sentinel-2 imagery utilizing UAV orthoimages  
  Jeanette Blumröder (HNE Eberswalde), Arlena Brosinsky (Uni Potsdam)  
  Strategien zur Entwicklung von pyrophoben und klimawandelresilienten Wäldern auf Waldbrandflächen (Projekt Pyrophob)  
  Tanja Sanders, Katja Öhmichen (Thünen Institut)  
  Fernerkundung in der Ressortforschung (I) – nationales Monitoring von Wäldern und Waldschäden am Thünen-Institut (Projekte: FirSt 2.0 und fnews)  
  Alexander Marx, NN
(TU Berlin)  
  Produktentwicklung zur skalenübergreifenden kontinuierlichen Vitalitäts- und Waldschadensanalyse mittels multisensoraler Fernerkundungsdaten und künstlicher Intelligenz – FirSt 2.0  
  Michael Förster, Tobias Gränzig
(TU Berlin)  
  A short update on the available hardware and field campaign logistics at the Geoinformation Lab
  Stefan Erasmi (Thünen Institut)  
  Fernerkundung in der Ressortforschung (II) – nationales Monitoring von Indikatoren der Agrarlandschaft am Thünen-Institut  

Start of the project FirST 2.0

The chair of Geoinformation in Environmental Planning  is part of the new joint project “FirSt 2.0 - SaaS product development for cross-scale continuous vitality and forest damage analysis using multi sensor Earth observation data and artificial intelligence” funded by the Federal Ministry of Transport and Digital Infrastructure (BMVi) for the period 2020-2023. The lead of the project is the LUP GmbH. The further project partners are: LiveEOOroratech, the Landesforst Mecklenburg-Vorpommern, the Nationalpark Bayerischer Wald, the Thünen-Institut für Waldökosysteme, the Landesbetrieb Wald und Holz Nordrhein-Westfalen and the Waldbesitzerverband Niedersachsen


Start of the TreeSatAI research project


The chair of Geoinformation in Environmental Planning  is leading the new joint project “TreeSatAI - Artificial Intelligence with Earth observation and multi-source geodata for infrastructure, nature conservation and forest monitoring” funded by the Federal Ministry of Education and Research for the period 2020-2022. The project partners are: Remote Sensing Image Analysis Group of TU Berlin, LiveEO, LUP, DFKI and Vision Impulse.



First International Conference on Urban Water Interfaces

22-24 September 2020, Berlin

Click here for further informations.



New publications


Fersch, B., Francke, T., Heistermann, M., Schrön, M., Döpper, V., Jakobi, J., Baroni, G., Blume, T., Bogena, H., Budach, C., Gränzig, T., Förster, M., Güntner, A., Hendricks Franssen, H., Kasner, M., Köhli, M., Kleinschmit, B., Kunstmann, H., Patil, A., Rasche, D., Scheiffele, L., Schmidt, U., Szulc-Seyfried, S., Weimar, J., Zacharias, S., Zreda, M., Heber, B., Kiese, R., Mares, V., Mollenhauer, H., Völksch, I. and Oswald, S. (2020). A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany. Earth System Science Data, 2289-2309.

Holtgrave, A., Röder, N., Ackermann, A., Erasmi, S. and Kleinschmit, B. (2020). Comparing Sentinel-1 and -2 Data and Indices for Agricultural Land Use Monitoring. remote sensing, 1-27.

Vulova, S., Meier, F., Fenner, D., Nouri, H. and Kleinschmit, B. (2020). Summer Nights in Berlin, Germany: Modeling Air Temperature Spatially With Remote Sensing, Crowdsourced Weather Data, and Machine Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 1-15.

Fenske, K., Feilhauer, H., Förster, M., Stellmes, M. and Waske, B. (2020). Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series. International Journal of Applied Earth Observation and Geoinformation, 1-13.

Döpper, V., Gränzig, T., Kleinschmit, B. and Förster, M. (2020). Challenges in UAS-Based TIR Imagery Processing: Image Alignment and Uncertainty Quantification.. remote sensing




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