Benjamin Jakimow

Benjamin Jakimow
Humboldt-Universität zu Berlin | HU Berlin · Department of Geography

Dr. rer. nat.

About

20
Publications
12,717
Reads
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541
Citations
Introduction
Benjamin Jakimow currently works at the Department of Geography, Humboldt-Universität zu Berlin. Benjamin does research in Geography, Geoinformatics (GIS) and Remote Sensing.
Additional affiliations
July 2015 - present
Humboldt-Universität zu Berlin
Position
  • PhD Student
April 2011 - present
Humboldt-Universität zu Berlin
Position
  • Research Associate

Publications

Publications (20)
Article
Full-text available
The increasing deforestation and fires since 2019 raises concerns about the irreversible destruction of the Brazilian Amazon. Our goal was to better understand these changes in south-west Pará across different land-tenure and farm systems and between the terms of President Rousseff, Temer, and Bolsonaro. We reconstructed deforestation and fire hist...
Poster
Full-text available
Underpinning EO-based findings with field-based evidence is often indispensable. However, especially in field work, there are countless situations where access to web-based services like Collect Earth or the Google Earth Engine (GEE) is limited or even impossible, such as in rainforests or deserts across the globe. Being able to visualize Earth obs...
Presentation
Full-text available
Presentation from the EnMAP Session at ESA's Living Planet Symposium
Conference Paper
The EnMAP-Box is a free and open source QGIS plugin. It integrates the strength of Python-based image processing and machine learning with graphical interfaces for handling hyperspectral images and spectral libraries in a GIS environment.
Article
Multi-spectral spaceborne sensors with different spatial resolutions produce Earth observation (EO) time series (TS) with global coverage. The interactive visualization and interpretation of TS is essential to better understand changes in land-use and land-cover and to extract reference information for model calibration and validation. However, ava...
Poster
Full-text available
The EnMAP-Box 3 is a toolbox for visualising and processing imaging spectroscopy data and spectral libraries, and is particularly developed to handle data from the upcoming EnMAP (Environmental Mapping and Analysis Program) mission. The integration as a python-based plug-in into the free and open source geographic information system QGIS 3 makes th...
Presentation
Full-text available
PDF slides on the presentation of the EO Time Series Viewer on ESA Earth Observation Φ-week 2018. The EO Time Series Viewer is an open source QGIS Plugin to visualise and describe multi-sensor Earth Observation time series data.
Article
Remote sensing based monitoring of deforestation in the tropics is crucial to better understand global land use change and related changes in ecosystem service provision and to inform governments and civil society on the effectiveness their forest protection policies. In Brazil, deforestation has been closely coupled to the expansion of grazing and...
Article
Full-text available
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine...
Article
Intensification of cattle ranching has the potential to reduce deforestation rates in the Brazilian Amazon by decreasing the demand for new agricultural land. Explicit spatial knowledge on where, when and how pastures are managed and intensification takes place is needed to better estimate potentials of more sustainable management. Monitoring the f...
Presentation
Full-text available
The EnMAP-Box is designed to process imaging spectroscopy data and particularly developed to handle data from the upcoming EnMAP (Environmental Mapping and Analysis Program) sensor. It serves as a platform for sharing and distributing algorithms and methods among scientists and potential end-users. Starting with version 3.0 the EnMAP-Box is designe...
Preprint
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine...
Article
Full-text available
The EnMAP-Box is a toolbox that is developed for the processing and analysis of data acquired by the German spaceborne imaging spectrometer EnMAP (Environmental Mapping and Analysis Program). It is developed with two aims in mind in order to guarantee full usage of future EnMAP data, i.e., (1) extending the EnMAP user community and (2) providing ac...
Article
Full-text available
Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution....
Article
An IDL implementation for the classification and regression analysis of remote sensing images with Random Forests is introduced. The tool, called imageRF, is platform and license independent and uses generic image file formats. It works well with default parameterization, yet all relevant parameters can be defined in intuitive GUIs. This makes it a...

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