Visualizing Uncertainty: Focus on Geo-Spatial Data

Alex Pang <pang@cse.ucsc.edu> University of California, Santa Cruz

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Motivation

• Not just pretty pictures • Goal: produce visualizations that show

both data + confidence

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Some Applications

• Weather forecasting, ocean modeling • Engineering design and manufacturing • Bioinformatics, functional genomics • Multisensor data fusion, data mining

• anything with measurement/modeling errors

Uncertainty glyphs can encode uncertainty in vector direction and magnitude

Regular arrow glyphs give false sense accurate vector heading and magnitude.

Glyphs

Modification to contour algorithm to give indication of uncertainty using dashed lines. Solid lines indicate regions higher certainty in the underlying data.

Contour Lines

+ 

Mean salinity Sdev salinity

Direct Volume Rendering

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2D Transfer Functions

Salinity data 2D transfer function

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Uncertainty Representation

• Scalar § standard deviation, confidence level, …

• 2-tuple § min-max, inter-quartile range, …

• Distribution § set of possible values, pdf, signal, …

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What if …

• there is a distribution at each location? § A set of numbers for each variable,

whether scalar or vector

• Richer representation for uncertainty • And what if the distributions are not

easily described by parametric statistics?

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Geo-spatial Examples

• Land cover classification based on satellite imagery and ground truth measurements generated by conditional simulation

• 3D time varying ocean circulation model with multiple realizations per variable

• Ensemble weather forecasts

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Key idea:

• Need to extend arithmetic and logic operations to distribution data

• Take advantage of basic operators from statistics, information theory, signal processing, etc.

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Pseudo-color

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Contour lines

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Isosurface

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Streamlines

Sensor-Based Geo-Spatial Visualization with Uncertainty

Suresh K Lodha Amin P. Charaniya, SrikumarRamalingam Sanjit Jhala, Nikolai Faaland

Department of Computer Science University of California Santa Cruz

Real-Time Kinematic GPS Tracking 

We have set up a RTK differential GPS system with the base station located at the Baskin School of Engineering that provides carrier phase differential corrections to the rover units in real­time. Communication is accomplished using low­bandwidth wireless UHF radio links.

Real-Time Mobile Situational Visualization 

We model the position and velocity uncertainty and visualize them using easy­to­recognize shapes. This work is in collaboration with Pramod Varshney  and his colleagues at Syracuse University.

Massive Scalable Geographic Information System 

Hierarchical interactive zooming into Santa Cruz starting from the earth to Santa Cruz County to ½ foot resolution imagery of UCSC Campus in VGIS. This work is in collaboration with Bill Ribarsky and Nick Faust at Georgia Institute of Technology.

20/27

Visualization of Heterogeneous Spatial Data 

Synchronous Visualization of LiDAR data, Digital Elevation Models, Aerial imagery, AutoCAD drawings, Street maps and Schematic Diagrams registered in the same coordinate system.

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Image-Based Modeling and Multi- Sensor Data Fusion 

We are engaged in several interesting image processing and data fusion projects including 3D reconstruction of data from 2D images, video mosaicing, and hierarchical registration of these data sets within our global geospatial visualization system.

Line Features Preservation and Simplification Algorithms for Terrains and Annotations 

Does hierarchical visualization of terrains destroy important line features such as coastlines and street maps? Our feature preserving and simplifying algorithms compress terrains and provide hierarchical details of streets as you zoom in.

Hierarchical Geo-Spatial Registration 

A new hierarchical approach for geo­spatial registration and adaptive enhancement of the resolution of 3D urban models based on newly obtained information.

Virtual Geographic Information System 

The final mosaiced image from 8 images taken near East Field House, UCSC. Seamless images are created from a sequence of spatially overlapping images for insertion within a 3D GIS environment.

Heterogeneous Spatial Data Analysis We are analysing and visualizing the uncertainty associated with heterogeneous spatial datasets like aerial images, LiDAR & DEM data. Features such as corners, edges are identified in the spatial datasets for uncertainty analysis and creation of geospatial intelligence.

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Web Site

www.soe.ucsc.edu/research/avis/unvis.html

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UCSC Faculty

• Suresh Lodha (CS) • Roberto Manduchi (CE) • Alex Pang (CS) • Hai Tao (CE) • Allen Van Gelder (CS) • Jane Wilhelms (CS)

Dive pattern of elephant seals equipped with GPS sensor and dead reckoning tracker.