René Westerholt, M.Sc.
Spatial autocorrelation is a key concept to any geographical analysis. Its presence indicates deviations from random behaviour in space. Thereby, positive spatial autocorrelation indicates a tendency towards clustering, whereas negative autocorrelation provides a hint towards regularity or repulsion effects. It is spatial autocorrelation that gives us reason to believe in some systematic spatial process beyond random effects. However, spatial autocorrelation can also be seen as a source of irritation. When not being modelled explicitly, its presence can exploit type I and type II errors and infringes requirements in non-spatial statistical analyses.
Over the past decades, a large number of indicators and corresponding specializations have been discovered and investigated. However, in the meantime, new kinds of datasets have become available. Just ten years ago we were primarily facing monothematic datasets that were acquired by strict sampling protocols. Nowadays, in contrast, we are facing vast numbers of georeferenced user-generated contents. Popular examples are online social networks such as Twitter or Facebook. These allow us to investigate everyday social activities on an unprecedented scale and level of detail. Furthermore, many of the corresponding messages from such services are georeferenced. Hence, we may never before have had similarly good opportunities for sociological as well as social geographical research.
However, these datasets are differing from their traditional counterparts. They typically reflect a variety of phenomena in mutually superimposed form. This mere fact leads to problems such as dealing with a mixture of different scales, difficult semantic processing and differing perceptions of phenomena by different individuals. Therefore, assessing spatial autocorrelation from such datasets is an enormously challenging task. The exploration and investigation of new methods for the quantification of spatial autocorrelation from user-generated datasets is thus the primary focus of my research.
We’ve recently finalised the programme of a workshop on “spatial urban analytics with user-generated geographic information”. The event is conjoined with the 2017 International Conference at the Royal Geographical Society in London and is co-chaired by René Westerholt (GIScience Heidelberg). We received methodological as well as empirical contributions, which reflects the breadth of the complex [...]
On Friday, our member René Westerholt held a talk at the Annual Meeting of the American Association of Geographers (AAG) in Boston. The talk which is entitled “Topological and scale-related issues in Twitter analyses through superimposed forms of spatial heterogeneity” was part of a special session on geographic data science organised by Alex Singleton from [...]
Our team member René Westerholt recently held a joint session with Dr Guibo Sun from Hong Kong University. The session on “spatial urban analytics” was part of the Geography colloquium at Harvard University. Both talks were dealing with methodological issues. Thereby, René emphasised on technical issues in the spatial analysis of social media data. Dr [...]
- since January 2013: Doctoral Candidate, GIScience Research Group, Institute of Geography, Faculty of Chemistry and Earth Sciences, Heidelberg University
- 10/2013-12/2013 Visiting Fellow, Center for Geographic Analysis, Harvard University, Cambridge, MA (USA)
- since June 2011: Software Developer (mobile and web-based GIS applications), Botanical Garden, University of Osnabrück
- 06/2011-02/2012: Research Assistant, Steinbeis Center for Applied Geoinformatics and Environmental Research
- 03/2010-04/2011: Software Developer (web-based routing application), Martin Luther University of Halle-Wittenberg
- 10/2010-12/2012 Graduate Studies of Geoinformatics (M.Sc.), Institute for Geoinformatics and Remote Sensing, Department of Mathematics and Computer Science, University of Osnabrück
- 10/2007-09/2010 Undergraduate Studies of Geoinformatics (B.Sc.), Institute for Geoinformatics and Remote Sensing, Department of Mathematics and Computer Science, University of Osnabrück
Peer-Reviewed Journal Articles:
Bluemke, M., Resch, B., Lechner, C., Westerholt, R. and Kolb, JP. (accepted): Toward an integration of GIS tools into survey research as exemplified in psychology: Current applications, challenges, and future avenues. Survey Research Methods, volume and issue pending, pp. pending. DOI: pending.
Borgmann, P., Westerholt, R., Oevermann, S. and Zachgo, S. (2017): Webbasierte und mobile Datenerfassung im Projekt "Netzwerk zum Schutz gefährdeter Wildpflanzen in Deutschland (WIPs-De)". Natur und Landschaft, 92 (2), 69 - 75. DOI: 10.17433/2.2017.50153439.69-75.
Li, M., Westerholt, R., Fan, H. and Zipf, A. (2016): Assessing spatiotemporal predictability of LBSN: A case study of three Foursquare datasets. GeoInformatica, volume and issue pending. DOI: 10.1007/s10707-016-0279-5.
Westerholt, R., Steiger, E., Resch, B. and Zipf, A. (2016): Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis. PLOS ONE, 11 (9), e0162360. DOI: 10.1371/journal.pone.0162360.
Steiger, E., Westerholt, R., Resch, B. and Zipf, A. (2015): Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data. Computers, Environment and Urban Systems, 54, 255 - 265. DOI: 10.1016/j.compenvurbsys.2015.09.007.
Westerholt, R., Resch, B. and Zipf, A. (2015): A local scale-sensitive indicator of spatial autocorrelation for assessing high- and low-value clusters in multi-scale datasets. International Journal of Geographical Information Science, 29 (5), 868-887. DOI: 10.1080/13658816.2014.1002499.
You can find a preprint ("as accepted") here.
Westerholt, R. and Resch, B. (2014): Asynchronous Geospatial Processing: An Event-Driven Push-Based Architecture for the OGC Web Processing Service. Transactions in GIS, 19 (3), 455-479. DOI: 10.1111/tgis.12104.
Steiger, E., Westerholt, R. and Zipf, A. (2016): Research on social media feeds – A GIScience perspective. In: Capineri, C, Haklay, M, Huang, H, Antoniou, V, Kettunen, J, Ostermann, F and Purves, R. (eds.): European Handbook of Crowdsourced Geographic Information, London: Ubiquity Press, 237-254. DOI: 10.5334/bax.r.
Westerholt, R. (2017): Topological and scale-related issues in Twitter analyses through superimposed forms of spatial heterogeneity. Annual Meeting of the American Association of Geographers 2017, Boston, MA.
Borgmann, P. and Westerholt, R. (2015): Citizen Science im Botanischen Artenschutz. Dialogforum Citizen Science, German Federal Environmental Foundation, Osnabrück, Germany.
Reimer, A. and Westerholt, R. (2014): Schematization for the analysis of geolocated microblog messages. In: Proceedings of AutoCarto 2014, International Symposium on Automated Cartography, Pittsburgh, PA.
Westerholt, R., Borgmann, P. and Zimmer, B. (2012): WebMapping-basierte Erfassung pﬂanzengenetischer Ressourcen in der Botanik. In: Löwner, M.-O., Hillen, F. and Wohlfahrt, R. (eds.): Geoinformatik 2012 „Mobilität und Umwelt“. Aachen: Shaker-Verlag, 411 - 414.
Borgmann, P., Westerholt, R., Zimmer, B. and Zachgo, S. (2012): Einsatz eines Geoportals in der Saatguterfassung. In: Lohwasser, U., Zachgo, S. und Börner, A. (ed.): Saatguterhaltung und Nutzbarmachung von Kulturpﬂanzen und heimischen Wildarten. Nürtingen: Gesellschaft für Pﬂanzenbauwissenschaften e.V., Berichte der Gesellschaft für Pﬂanzenbauwissenschaften, volume 6, 17 - 19.
Borgmann, P., Westerholt, R., Oevermann, S. and Zachgo, S. (2014): WEL-Webmapping. In: Poschlod, P., Borgmann, P., Listl, D., Reisch, C. and Zachgo, S. (eds.): Handbuch Genbank WEL. Regensburg: HOPPEA Denkschriften der Regensburgischen Botanischen Gesellschaft, 133 - 140.
Awards / Honors
|03/2014:||Young Researchers Award 2013, North-German Society for Geoinformatics|
|10/2013:||International Mobility Grant Funding, German Universities Excellence Initiative II|
|01/2013:||PhD Scholarship, State of Baden-Württemberg|
|SS 2017:||Introduction to computer science for geographers (Seminar + Lab)|
|SS 2017:||Introduction to GIS (Lab; conception and supervision of tutors)|
|WS 2016/17:||Introduction to the spatial analysis of human-geographic data (Lecture)|
|WS 2016/17:||Spatiostatistical exploration of human-geographic data (Lab)|
|SS 2016:||Fundamentals of computer science for geographers (Seminar + Lab)|
|SS 2016:||Introduction to GIS (Lab; conception and supervision of tutors)|
|WS 2015/16:||Spatial associations in human geography (Lecture)|
|10/2016:||Mining the “big noise:“ Challenges and opportunities of social media analysis, Mapping, Sensing, and Crowdsourcing Geographic Information, Royal Geographical Society, London, UK|
|10/2016:||Spatial [sic] Analysis of Twitter Data, WISC Seminar Series, Warwick Institute for the Science of Cities, University of Warwick, Coventry, UK|
|06/2015:||Mixed-Scale Spatial Autocorrelation, Forum GI, Institute for Geoinformatics and Remote Sensing, Osnabrück University, Germany|
|11/2013:||Multi-Scale Event Detection on Twitter Tweets, Geography Colloquium, Center for Geographic Analysis, Harvard University, Cambridge, USA|
- Transactions in GIS, John Wiley & Sons
- Knowledge and Information Systems, Springer
- International Journal of Digital Earth, Taylor & Francis
- Royal Geographical Society, Fellow
- GfGI, Member