Selected Publications

Integrating R with Geographic Information Systems (GIS) extends R’s statistical capabilities with numerous geoprocessing and data handling tools available in a GIS. QGIS is one of the most popular open-source GIS, and it furthermore integrates other GIS programs such as the System for Automated Geoscientific Analyses (SAGA) GIS and the Geographic Resources Analysis Support System (GRASS) GIS within a single software environment. This and its QGIS Python API makes it a perfect candidate for console-based geoprocessing. By establishing an interface, the R package RQGIS makes it possible to use QGIS as a geoprocessing workhorse from within R. Compared to other packages building a bridge to GIS (e.g., rgrass7, RSAGA, RPyGeo), RQGIS offers a wider range of geoalgorithms, and is often easier to use due to various convenience functions. Finally, RQGIS supports the seamless integration of Python code using reticulate from within R for improved extendability.
The R Journal, 2017

Recent Publications

(2017). RQGIS: Integrating R with QGIS for Statistical Geocomputing. The R Journal.

PDF Project

(2016). Forest DRAGON-3: Decadal trends of Northeastern Forests in China from Earth Observation Synergy. In Proc.‘Dragon 3 Final Results & Dragon 4 Kick-Off Symposium’, Wuhan, PR China.

PDF

Recent posts

The year just started and I would like to start a small series of blog posts that describe my work environment: Which libraries/applications do I use to get my PhD work done and why I use exactly these. I will start by writing down my thoughts on the ‘Windows vs. Unix’ debate. I know this is a hot topic and will probably outlive humanity :wink:. However, I often have to deal with it because all people in my working environment run Windows and I always try to convince them why they could by more productive in our field of work if they would use Linux, especially if they run into troubles and ask me for help (parallelization, server access, automation, etc.). This post only aims to compare both worlds in the field of data science, science and in more detail the usage of R.

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Introduction Autofs Notes Introduction At work I usually have to connect to several servers. Some are Windows Servers, some are Linux Servers. On my local Linux machines (running Kubuntu 17.10 at the time writing this) I usually used /etc/fstab entries. However, the fstab way does not mount on boot and always needs manual re-mounting. I was told that there have been times in which automatic mounting during boot using fstab was working but I never managed to get it working although I tried several mount options like _netdev and others.

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Usually, this calculation is done by setting all predictors to their mean value, predict the response, change the desired predictor to a new value and predict the response again. These actions results in two log odds values, respectively, which are transformed into odds by exponentiating them. Finally, the odds ratio can be calculated from these two odds values.

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Projects

R package 'mlr' (Contributor)

Machine Learning in R

Forest-DRAGON 3 (2013 - 2016)

ESA-MOST Dragon 3 cooperation program

LIFE Healthy Forest

Early detection and advanced management systems to reduce forest decline caused by invasive and pathogenic agents

R package 'RQGIS' (Author)

Integrating R with QGIS

R package 'oddsratio' (Creator)

Simplified odds ratio calculation of binomial GAM/GLM models

R package 'sperrorest' (Author)

Integrating R with QGIS

Recent talks

More Talks

Teaching

M.Sc. Geoinformatics

Winter term 20172018

  • Geo 404: Applied Geoinformatics
    • R Introduction
    • Handling of raster data in R
    • Literate Programming in R
    • Big data handling & parallelization in R

B.Sc. Geography

Winter term 20162017

  • Geo 311 (3rd year B.Sc.): Geoinformatics III
    • Introduction to Python
    • Python for geoprocessing -> arcpy
    • Introduction to scientific reporting using Rmarkdown
    • Tools: R, Python, ArcGIS, arcpy

List of internships (Geoinformatics/Remote Sensing)

I maintain a list of internships undertaken in the Geoinformatics or Remote Sensing field by B.Sc. Geography & M.Sc. Geoinformatics students.
There will be no online version of this document due to possibly sensible contact data. If you want to add your intership to the list, please contact me.

Contact