Dr. rer. nat. Benjamin Jakimow
- Name
- Dr. rer. nat. Benjamin Jakimow
- benjamin.jakimow (at) geo.hu-berlin.de
| Status | Researcher |  |
| benjamin.jakimow@geo.hu-berlin.de | ||
| Office location | Rudower Chaussee 16, Room 2'211 | |
| Phone | +49 (0)30 2093-6846 | |
| Fax | +49 (0)30 2093-6877 | |
| Postal address | Unter den Linden 6, 10099 Berlin, Germany |
About me
I am a Diplom-Geographer with a background in remote sensing, informatics and agricultural sciences. My research focusses on land-use intensification in the Brazilian Amazon and how we can describe it by means of remote sensing.
Curriculum Vitae
|
since 07/2015 |
Doctoral Researcher. Geomatics Lab, HU-Berlin, Germany. |
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since 04/2011 |
Research Assistant. Geomatics Lab, HU-Berlin, Germany.
|
| 2010 |
German Armed Forces
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| 2009 | Internship ARC-GREENLAB GmbH, Berlin, Germany. |
| 2008 - 2009 |
Erasmus Student. Lunds University, Sweden.
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| 2008 | Internship German Aerospace Center (DLR), Berlin, Germany. |
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2004 - 2011 |
Study of Physical Geography. HU-Berlin, Germany.
|
| 2000 - 2004 |
German Armed Forces
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Please find my full CV on https://www.linkedin.com/in/benjamin-jakimow/
Publications
Jakimow, B., van der Linden, S., Thiel, F., Frantz, D., & Hostert, P. (2020). Visualizing and labeling dense multi-sensor earth observation time series: The EO Time Series Viewer. Environmental Modelling & Software, 125. doi: 10.1016/j.envsoft.2020.104631
Jakimow, B., Griffiths, P., van der Linden, S., & Hostert, P. (2018). Mapping pasture management in the Brazilian Amazon from dense Landsat time series. Remote Sensing of Environment, 205, 453-468. doi: 10.1016/j.rse.2017.10.009
Griffiths, P., Jakimow, B., & Hostert, P. (2018). Reconstructing long term annual deforestation dynamics in Pará and Mato Grosso using the Landsat archive. Remote Sensing of Environment, 216, 497-513. doi: 10.1016/j.rse.2018.07.010
Hostert, P., Griffiths, P., Jakimow, B., Waske, B., & Hagensieker, R. (2017). Schlussbericht SENSE-CARBON - Nutzung von Sentinel Daten zu Kohlenstoffquantifizierung und REDD+Monitoring. Berlin. doi: 10.2314/GBV:1010726803
Hagensieker, R., Roscher, R., Rosentreter, J., Jakimow, B., & Waske, B. (2017). Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data. International Journal of Applied Earth Observation and Geoinformation, 63(Supplement C), 244-256. doi: 10.1016/j.jag.2017.07.019
van der Linden, S., Rabe, A., Held, M., Jakimow, B., Leitão, P., Okujeni, A., . . . Hostert, P. (2015). The EnMAP-Box—A Toolbox and Application Programming Interface for EnMAP Data Processing. Remote Sensing, 7(9), 11249. doi: 10.3390/rs70911249
Okujeni, A., van der Linden, S., Jakimow, B., Rabe, A., Verrelst, J., & Hostert, P. (2014). A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover. Remote Sensing, 6(7), 6324. doi: 10.3390/rs6076324
Waske, B., van der Linden, S., Oldenburg, C., Jakimow, B., Rabe, A., & Hostert, P. (2012). imageRF – A user-oriented implementation for remote sensing image analysis with Random Forests. Environmental Modelling & Software, 35, 192-193. doi: 10.1016/j.envsoft.2012.01.014
Data & Software
EO Time Series Viewer - A QGIS Plugin to visualize remote sensing time series data. https://plugins.qgis.org/plugins/timeseriesviewerplugin/
EnMAP-Box: The EnMAP Box is a freely available, platform-independent software designed to process hyperspectral remote sensing data, and particularly developed to handle data from the EnMAP sensor. It is distributed as Free and Open Source Software (FOSS). https://bitbucket.org/hu-geomatics/enmap-box
Virtual Raster Builder. https://plugins.qgis.org/plugins/vrtbuilderplugin/
Bit Flag Renderer. https://plugins.qgis.org/plugins/BitFlagRenderer/