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Uncertainty visualisation in the Model Web

Uncertainty visualisation in the Model Web. Lydia Gerharz, Christian Autermann , Holger Hopmann , Christoph Stasch Institute for Geoinformatics ( ifgi ), University of Münster lydia.gerharz@uni-muenster.de. Overview. Introduction Uncertainty visualisation methods

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Uncertainty visualisation in the Model Web

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  1. Uncertainty visualisation in the Model Web Lydia Gerharz, Christian Autermann, HolgerHopmann, ChristophStasch Institute for Geoinformatics (ifgi), University of Münster lydia.gerharz@uni-muenster.de

  2. Overview • Introduction • Uncertaintyvisualisationmethods • UncertWeb visualisationclient • Hands-on Exercises • Vectordatavisualisation • Raster datavisualisation • Howtoprepareyourowndata • Wrap-up& Discussion

  3. Introductiontouncertaintyvisualisation

  4. Uncertaintyvisualisation Communicateuncertainties in geospatialdatato • allowmeaningfulinterpretationofmodelresultsormeasurementsfordecisionmaking • explorespatialand temporal distributionofuncertainties

  5. Uncertaintyvisualisationmethods Techniques • Adjacentmaps • Bi-variatemaps • Sequentialmaps Modes • Static • Dynamic • Interactive e.g. Animation ofrealisations

  6. Methods (i) – Focus metaphors Contourcrispness Fog Fillclarity Resolution MacEachren (1992)

  7. Methods (ii) – Adjacentmaps Value anduncertaintymapsareshownnexttoeachother Rodriguez et al. (2006) Avoids visual overload, but hard to connect two maps mentally

  8. Methods (iii) – Probabilityofexceedance Descriptivestatistics: UseIPCC (2001) terminologytodescribeprobabilityofexceedance van de Kassteele & Velders. (2006)

  9. Methods (iv) – Stochasticaldimension in a GIS Aguila software • Cumulativeprobabilitydistributionforeachpixelorobject Browse eitherthroughprobabilityorvalues (thresholds) • Cumulative/exceedanceprobability • Confidenceintervals Time seriesvisualisation Scenario view Pebesma et al. (2007)

  10. Other methods Hierarchicalspatialdatamodel Whitening Hengl (2003) Kardos et al. (2003) Confidence intervals

  11. Uncertaintyvisualisation in the Model Web Output Output Input Input Data service e.g. meteorologicalmeasurements Model service e.g. meteorologicalforecastmodel Model service e.g. airqualitymodel Final result Web-baseduncertaintyvisualisationclient

  12. Aimwithin UncertWeb Develop a tool that • enablescommunicationofuncertainties in spatio-temporal datato different usergroups • allows easy integration into model workflows following the Model Web paradigm • visualises inputs, outputs and intermediate steps • supports different uncertaintyandgeospatialencodings

  13. UncertWeb visualisationtool • Interactive, web-basedthinclient • Supports different encodings • Uncertainties: UncertML 2.0 • Raster data: NetCDF, GeoTIFF • Vectordata: Observations&Measurements (O&M) • Open Source, based on JavaScript libraries • OpenLayers (spatial, temporal, spatio-temporal data) • jStat (non-temporal, non-spatialuncertainties) • ExtJS (interactive web applicationcontrols) https://svn.52north.org/svn/geostatistics/main/uncertweb/

  14. Implementation details • Vectordata • Encodedas O&M and UncertML in XML/JSON format • Directlyreadbytheclient • Raster data • NetCDFandGeoTiffcannotbedirectlyreadbytheclient • RESTfulVisualisation Service (VISS) • Create visualisations (raster) fromcomplexsources • Web Mapping Service (WMS) • Stores createdrasters • Providestile-caching • Manyclientsavailable

  15. U-O&M encoding • Uncertainty Observation type toencode UncertML types (distribution, samples, statistics)

  16. NetCDF-U encoding • Encodeuncertaintyasdimensionorancillary_variable • refattributeto UncertML definition

  17. Architecture overview Web client SOS Raster map U-O&M as XML or JSON WMS reference VECTOR DATA WMS Stores createdraster VISS Createsvisualisation Add layer NetCDF-U WCS Stores sourcedata RASTER DATA

  18. Visualisation methods Support for: • Non-spatial & spatialdata • Temporal & Spatio-temporal data • Continuous & categoricaldata • Multivariate data • Different userbackgroundsandexperiences • Different usabilityofvisualisationmethods • Adjacentmapsfornoviceusers • Multidimensional mapsforexperts

  19. Visualisation methods – Basic plots Continuous data Categorical data

  20. Visualisation methods – Time series plots

  21. Visualisation methods – Adjacent maps Continuous data Categorical data

  22. Visualisation methods – Multidimensional approach Continuous data Categorical data

  23. Usingthetool Menu toolbar Mapnavigation Mapwindow Legend

  24. Addingnewresources 1) By Add Resourcebutton 2) By URL Parameter 2a) http://giv-uw.uni-muenster.de/vis/v2/?url=http://giv-uw.uni- muenster.de/data/netcdf/biotemp.nc&mime=application/netcdf 2b) http://giv-uw.uni-muenster.de/vis/v2/?netcdf=http://giv-uw.uni- muenster.de/data/netcdf/biotemp.nc

  25. Exercises http://giv-wikis.uni-muenster.de/agp/bin/view/Main/UncertaintyVisualisationWorkshop

  26. Wrap-up & Questionnaire http://surveys.ifgi.de/  UncertWeb Questionnaire Part B.1: Visualization Tool Further comments/questions?!

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