publications

published papers and reports

• Hüttner, A., M. Scherer & B. Gräler (submitted): Geostatistical modeling of financial data: Estimation of large covariance matrices and imputation of missing data. Journal of Banking and Finance, (submitted).
• Lazoglou, G., B. Gräler, & C. Anagnostopoulou (2019): Simulation of extreme temperatures using a new method: TIN‐copula. 
  International Journal of Climatology, 39(13), 5201-5214.
  DOI: 10.1002/joc.6124
• Hengl, T., M. Nussbaum, M.N. Wright, G.B. Heuvelink, & B. Gräler (2018): Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables. 
  PeerJ, 6, e5518.
  DOI: 10.7717/peerj.5518.
• Stasch, C., B. Pross, B. Gräler, C. Malewski, C. Förster & S. Jirka. (2018): Coupling sensor observation services and web processing services for online geoprocessing in water dam monitoring. 
  International Journal of Digital Earth, 11(1), 64-78.
  DOI: 10.1080/17538947.2017.1319977 
• Gräler, B., Ayyad, C., & Mateu, J. (2017): Modelling count data based on weakly dependent spatial covariates using a copula approach: application to rat sightings.
  Environmental and Ecological Statistics, 24(3), 433-448.
  DOI: 10.1007/s10651-017-0379-x 
• Gräler, B., S. Fischer & A. Schumann (2016): Joint modeling of annual maximum precipitation across different duration levels.
  SFB 823 discussion paper 83/16.
• Heuvelink, G. B., Pebesma, E., & Gräler, B. (2016). Space-Time Geostatistics, In: Encyclopedia GIS, eds. Shekhar, S., Xiong, H. & Zhou, X., Springer 2016. chapter
• Gräler, B., E. Pebesma & G. Heuvelink (2016): Spatio-Temporal Interpolation using gstat, The R Journal 8(1), 204-218.
  Manuscript
• Gräler, B., A. Petroselli, S. Grimaldi, B. De Baets, & N. E. C. Verhoest (2016): An Update on Multivariate Return Periods in Hydrology,
  Proceedings of the International Association of Hydrological Sciences, 373, 175-178.
  DOI: 10.5194/piahs-373-175-2016.
• Scheider, S., B. Gräler, E. Pebesma, C. Stasch (2016):
  Modeling spatiotemporal information generation,
  International Journal of Geographical Information Science, 30(10), 1980 - 2008.
  DOI: 10.1080/13658816.2016.1151520.
• Gasch, C. K., T. Hengl, B. Gräler, H. Meyer, T. S. Magney, D. J. Brown (2015): Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D+ T: The Cook Agronomy Farm data set, Spatial Statistics, 14, 70-90.
  DOI: 10.1016/j.spasta.2015.04.001
• Kilibarda, M., T. Hengl, G. B. M. Heuvelink, B. Gräler, E. Pebesma, M. Perčec Tadić & B. Bajat (2014): Spatio-temporal interpolation of daily temperatures for global land areas at 1 km resolution,
  Journal of Geophysical Research: Atmospheres, 119, 2294-2313.
  DOI: 10.1002/2013JD020803
• Gräler, B. (2014): Modelling Skewed Spatial Random Fields through the Spatial Vine Copula.
  Spatial Statistics, Elsevier, 10, 87 - 102.
  DOI: 10.1016/j.spasta.2014.01.001
• Kauppinen, T., de Espindola, G. M., Jones, J., Sánchez, A., Gräler, B., & Bartoschek, T. (2014). Linked brazilian amazon rainforest data. Semantic Web, 5(2), 151-155.
  DOI: 10.3233/SW-130113
• Gräler, B., M. J. van den Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. De Baets, & N. E. C. Verhoest (2013): Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation, Hydrology and Earth System Sciences, 17, 1281-1296, HESS-17-1281-2013.
  DOI: 10.5194/hess-17-1281-2013
• Gräler, B., M. Rehr, L. E. Gerharz, & E. Pebesma (2013): Spatio-temporal analysis and interpolation of PM10 measurements in Europe for 2009.
  ETC/ACM Technical Paper 2013/08, March 2013. TP2012/08
• Gräler, B., L. E. Gerharz, & E. Pebesma (2012): Spatio-temporal analysis and interpolation of PM10 measurements in Europe.
  ETC/ACM Technical Paper 2011/10, January 2012. TP2011/10
• Gerharz, L. E., B. Gräler & E. Pebesma (2011): Measurement artefacts and inhomogeneity detection.
  ETC/ACM Technical Paper 2011/8, December 2011. TP2011/8
• Gerharz, L. E., B. Gräler & E. Pebesma (2011): Disaggregation of air quality data for spatio-temporal exposure modelling.
  Procedia Environmental Sciences (Vol. 7, pp. 146 - 151), Elsevier.
  DOI: 10.1016/j.proenv.2011.07.026
• Gräler, B. & E. Pebesma (2011): The pair-copula construction for spatial data: a new approach to model spatial dependency.
  Procedia Environmental Sciences (Vol. 7, pp. 206 - 211), Elsevier.
  DOI: 10.1016/j.proenv.2011.07.036
• Gräler, B., H. Kazianka & G. M. de Espindola (2010): Copulas, a novel approach to model spatial and spatio-temporal dependence.
  In K. Henneböhl, L. Vinhas, E. Pebesma, & G. Cãmara (Eds.), GIScience for Environmental Change Symposium Proceedings, ifgiprints (Vol. 40, pp. 49-54), AKA Verlag.
  Presented at the GIScience for Environmental Change, November 27, 2010, Campos do Jordão (São Paulo), Brazil. extended abstract

presented talks/courses/posters

• Gräler, B. , I.I. Klatt, M. Pontius & A. Remke (2020): Predictive Analytics to Improve Road Safety. 2020 10th International Conference on Advanced Computer Information Technologies (ACIT), IEEEXplore, Deggendorf, 2020 (accepted).
• Gräler, B., C. Doll, J. Mück, A. Remke, D. Schramm, A. de Wall & H. Wulffius (2020): CITRAM - Citizen Science for Traffic Management. EGU 2020 Sharing Geoscience Online
  DOI: 10.5194/egusphere-egu2020-19952 
• Leopold, U., B. Gräler, H. Bredel, J. A. Torres-Matallana, P. Pinheiro, M. Stefas, T. Udelhoven, J. Dries, B. Valentin, L. Gale, P. Mougnaud & M. Schlerf (2020): The Earth Observation Time Series Analysis Toolbox (EOTSA) - An R package with WPS, Web-Client and Spark integration. EGU 2020 Sharing Geoscience Online
  DOI: 10.5194/egusphere-egu2020-21974 
• Nüst, D. E.H. Jürrens, B. Gräler & S. Jirka (2020): Accessing environmental time series data in R from Sensor Observation Services with ease. EGU 2020 Sharing Geoscience Online
  DOI: 10.5194/egusphere-egu2020-19453 
• Jirka, S., E.H. Jürrens, B. Gräler, C. Hollmann, A. Kotsev, M. Gerboles, A. Borowiak& S. Schade (2020): AQSens: An Interoperable Platform Integrating Citizen Science and Authoritative Air Quality Data. EGU 2020 Sharing Geoscience Online
  DOI: egusphere-egu2020-14358 
• Pontius, M., B. Gräler, A. Remke & A. de Wall (2020): Estimating fuel consumption of cars based on movement data and its sensitivity to car and movement specific properties. EGU 2020 Sharing Geoscience Online
  DOI: 10.5194/egusphere-egu2020-9246 
• Gräler, B., C. Malewski, C. Förster & S. Jirka (2019): Integration zeitlich hochauflösender Fernerkundungsdaten in das Sensor Web.
  2. Bochumer Hydrometrie-Kolloquium, Bochum, 20. Februar 2019.
• de Wall, A., A. Remke, B. Gräler, T. Fechner & B. Bernsdorf (2019): Improving Methods and Technologies for the Large-Scale Monitoring of Flooding Situations. In Geophysical Research Abstracts (Vol. 21).
• de Wall, A., A. Remke, & B. Gräler (2019): An Cloud-native Architecture for Near-Real-Time Monitoring of Floods. In Geophysical Research Abstracts (Vol. 21).
• Gräler, B., A. de Wall & A. Remke (2019): Citizen Science for Traffic Management and Safety. In Geophysical Research Abstracts (Vol. 21).
• Radtke, M., B- Gräler, E.H. Jürrens & S. Jirka (2019): Managing Earth Observation datasets as multidimensional arrays using SciDB and open standards. In Geophysical Research Abstracts (Vol. 21).
• Gräler, B., C. Stasch, S. Jirka, C. Malewski, C. Förster & A. Remke (2018): Combining remote sensing and in-situ data for water body monitoring. In EGU General Assembly Conference Abstracts (Vol. 20, p. 14509).
• Pross, B., B. Gräler, C. Stasch, C. Malewski, C. Förster & S. Jirka (2018): A dam information and monitoring system rooted in the sensor web. In EGU General Assembly Conference Abstracts (Vol. 20, p. 17402).
• Gräler, B. (2017): Modelling Extremes with Local Spatial and Spatio-Temporal Vine Copulas. Centre de recherches mathématiques (CRM) thematic semester, workshop on "Dependence modeling tools for risk management". Montreal, Canada, 2nd – 5th October 2017.
• Gräler, B., C. Stasch, B. Pross, O. Peeters & S. Jirka (2017): Open Tools for Statistical Analysis in Spatial Data Infrastructures. UN-ECE and UN-GGIM Workshop on Integrating Geospatial and Statistical Standards, Stockholm, 6 - 8 November 2017.
• Gräler, B. workshop at Spatial Statistics Conference, Lancaster, UK, 4 July 2017.course material
• Gräler, B., S. Fischer & A. Schumann (2017). Joint modeling of annual maximum precipitation across different duration levels. In EGU General Assembly Conference Abstracts (Vol. 19).
• Fischer, S., B. Gräler & A. Schumann (2017). Spatio-temporal assessment of flood events by hierarchical Kendall-copulas. In EGU General Assembly Conference Abstracts (Vol. 19).
• Stasch, C., B. Pross, S. Jirka, S. & B. Gräler (2017): Adding Processing Functionality to the Sensor Web. In EGU General Assembly Conference Abstracts (Vol. 19, p. 15052).
• Gräler, B., S. Fischer & A. Schumann (2017): Joint modeling of annual maximum precipitation across different duration levels. In EGU General Assembly Conference Abstracts (Vol. 19, p. 2004).
• Gräler, B.(2016): Precipitation modeling via spatial vine copulas. CMStatistics 2016, Session EO009, 9 December 2016, Seville, Spain, 9-11 December 2016.
• Ayyad, C., B. Gräler, P. Aragó & J. Mateu (2016): Modelling crime data in European mediterrranean towns: a vine copula approach
  Poster at: 8th international workshop on spatio-temporal modelling - METMA VIII, Valencia, Spain, 1-3 June 2016.
• Gräler, B., A. Petroselli, S. Grimaldi, B. De Baets, & N. E. C. Verhoest: An Update on Multivariate Return Periods in Hydrology
  Talk at the 7th International Water Resources Management Conference of ICWRS, Bochum, Germany, 18-20 May, 2016.
• Pebesma, E., S. Scheider, B. Gräler, C. Stasch & M. Hinz (2016): An algebra for spatio-temporal information generation. European Geosciences Union General Assembly, Vienna, Austria.
• Gräler, B., A. Petroselli, S. Grimaldi, B. De Baets & N. Verhoest (2016): An update on multivariate return periods in hydrology. In 7th International Water Resources Management conference of ICWRS (Vol. 373, pp. 175-178). Copernicus.
• Schumann, A. & B. Gräler (2016): Vergleich der statistischen Ansätze für Starkniederschlag und Hochwasser DWA-A 531 vs DWA-M 552. Talk at the Expertengespräch zum Thema Bemessungsniederschlag, Hanover, Germany, 7th March 2016.
• Hüttner, A., M. Scherer, B. Gräler (2016): On the application of geostatistical methods to the modelling of correlated credit spreads
  Poster at: German Probability and Statistics Days 2016, Bochum, Germany, 1-4 March 2016.
• Gräler, B. (2015): Workshop zur Trajektorienanalyse. Universität Osnabrück, Fachbereich Biologie/Chemie, Abteilung Biologiedidaktik.
  Osnabrück, 23. Januar 2015.
• Gräler, B. (2015): The spatial vine copula: modelling skewed spatial random fields. Talk at the Oberseminar Finanz- und Versicherungsmathematik of LMU/TUM, Munich, Germany, 13th July 2015.
• Solnicky, R. & B. Gräler (2015): Vine copulas and synthetic flood events generation. Aon Benfield Research Conference, 22 Juni 2015, Zurich, Switzerland.
• Gräler, B. (2015): Introduction to spatial copulas. Talk at the Spatial Statistics Conference, Avignon, France, 9th - 12th June 2015.
• Gräler, B. (2015): Spatio-temporal statistics with R: an introduction to packages spacetime, gstat and spcopula. Workshop at the Spatial Statistics Conference, Avignon, France, 9th - 12th June 2015.
• Gasch, C. K., T. Hengl, B. Gräler, H. Meyer, T. Magney & D.J. Brown (2015): Geostatistical modelling with 3D+ T data: soil moisture, temperature, and electrical conductivity at the field scale. In EGU General Assembly Conference Abstracts (Vol. 17).
• Gasch, C., T. Hengl, T.S. Magney, D.J Brown. & B. Gräler (2014): Spatio-temporal interpolation of soil moisture in 3D+ T using automated sensor network data. In AGU Fall Meeting Abstracts.
• Gräler, B. (2014): Modelling spatio-temporal random fields locally with vine copulas. Invited talk at the CRM-CANSSI Workshop on New Horizons in Copula Modeling, Montreal, Canada, 15th - 18th December 2014.
• Gräler, B. (2014): Covariates in Spatio-Temporal Vine Copulas. Presentation at the Spatial Copula Workshop 2014, Münster, Germany, 22nd - 23rd September 2014. Slides
• Gräler, B. (2014): gstat package tutorial. Pre-conference Tutorial at DailyMeteo.org 2014, Belgrade, Serbia, 23-27 June 2014. Slides
• Gräler, B. (2014): Spatio-Temporal Geostatisitcs. One day course within the GEOSTAT Summer School 2014, Bergen, Norway, 15-22 June 2014. Slides on spatio-temporal geostatistics Slides on copulas
• Gräler, B. (2014): Spatial Statistics - a one hour introduction. Invited talk at TUM IGSSE Forum Raitenhaslach 2014, Burghausen, Germany, 16-18 June 2014. Slides BitBucket repository
• Gräler, B. (2013): The spcopula R-package: Modelling Spatial and Spatio-Temporal dependence with copulas. Presentation at: Spatail Statistics 2013. Columbus, Ohio, USA, 4-7 June 2013. abstract slides
• Gräler, B. (2013): Modeling Extremes with the Spatial Vine Copula
  Poster at: Spatial Statistics 2013. Columbus, Ohio, USA, 4-7 June 2013. abstract poster
• Gräler, B. (2013): An Application of Vine Copulas in the Spatio-Temporal Domain. Presentation at: Spatial Copula Day. Technische Universität München, Garching-Hochbrück, Germany, 21 February 2013
• Gräler, B. (2013): Modelling Spatial Phenomena and Joint Return Periods with Copulas using R: the spcopula Package
  Poster at: EGU 2013, HS3.3. Vienna, Austria, 7-12 April 2013. EGU2013-7443, poster
• Kauppinen, T., W.R. van Hage, & B. Gräler (29.11.2012): Interconnecting Linked Open Data and R with the SPARQL package for Linked Science.
  Workshop at: SWAT4LS, Paris, France, 28-30 November 2012.
• Gräler, B. (05.09.2012): Spatio-Temporal Geostatisitcs. One day course within the GEOSTAT Summer School 2012, Münster, Germany, 3-11 September 2012.
• Gräler, B. & E. Pebesma (2012): Modelling Dependence in Space and Time with Vine Copulas. Presentation at: Geostats 2012, Oslo, Norway, 11-15 June 2012 abstract, slides, extended abstract.
• Kauppinen, T., Gräler, B. & de Espindola, G.M.: Sharing and Analyzing Remote Sensing Observation Data for Linked Science.
  Poster at: Extended Semantic Web Conference 2012, Heraklion, Crete, Greece, 27-31 May 2012. abstract poster (A4)
• Gräler, B., S. Vandenberghe, M.J. van den Berg, S. Grimaldi, A. Petroselli, B. De Baets & N.E.C. Verhoest (2012): Multivariate Return Periods based on Vine Copulas. In EGU General Assembly Conference Abstracts (Vol. 14, p. 4097).
• Gräler, B. & C. Stasch (2012): Flexible representation of spatio-temporal random fields in the model web. In EGU General Assembly Conference Abstracts (Vol. 14, p. 4617).
• Gräler, B. (2011): Using vine copulas to explore relationships between variables determining deforestation in the Brazilian Amazon. Presentation at: GIScience for environmental change - use cases in the Brazilian Amazon. GEOINFORMATIK 2011 - GEOCHANGE, Münster, Germany, 15 - 17 June 2011. slides
• Gräler, B. (2011): Vine copulas for spatial interpolation. Presentation at: 4th Workshop on Vine Copula Distributions and Applications. Technische Universität München, Garching-Hochbrück, Germany, 11 & 12 May 2011. slides
• Gerharz, L. E., B. Gräler & E. Pebesma (2011): Disaggregation of air quality data for spatio-temporal exposure modelling.
  Poster at: Spatial Statistics 2011 - Mapping global change. Enschede, The Netherlands, 23-25 March 2011.
  DOI: 10.1016/j.proenv.2011.07.026
• Gräler, B. & E. Pebesma (2011): The pair-copula construction for spatial data: a new approach to model spatial dependency.
  Poster at: Spatial Statistics 2011 - Mapping global change. Enschede, The Netherlands, 23-25 March 2011.
  DOI: 10.1016/j.proenv.2011.07.036, poster (A4).