Building Landscape Visualizations for Instructionat the University of Arizona

By Aaryn Olsson and

Dr. Robert MacArthur

Building Landscape Visualizations for Instruction

Abstract: Higher education courses in certain disciplines use GIS extensively, but rarely is GIS used in large, general

education courses because the learning curve for the software is too steep. Visualization provides an instructional avenue

into spatial data modeling by providing students with powerful visual tools.

Acknowledgments:

• Eric Pfirman at Arizona Regional Image Archive for his help processing raw satellite data for our consumption and, of course, for giving us the AML… Without his help and the work of others at ARIA, these tools could not have been developed.

– http://aria.arizona.edu/

• College of Agriculture, without which, we would not exist.

Background

• Recent learning theories place a high value on visualization, simulations, and virtual reality.

• Learners like to control where and how they learn and visualization makes complicated technology relatively simple for the non-technical to use.

• The emergence of technologies that merge visualization with GIS and other database technology have extended the notion of building “information environments” that are open to the non-technical.

Visualizations Fall into 2 Basic Categories

1. Image-based– Hybrid data/photography (text, words)– High level of verisimilitude– Easy to manipulate effects (morphing)– Image analysis, nearest neighborhood, etc.– High storage demand– lack of 3D

Image-based Exampleshowing image filtering effects

Visualization Categories (cont.)

2. Object-based– Not as realistic… yet– Can use object-oriented tools

• inheritance, replication, attribute sharing

• can build object queries

– Ideal for modeling– Easier to store (no object redundancy)

Object-based Example showing campus model generated from an orthophoto

Example of Contrast Between Image- and Object-based Visualization

Image-based (lower panel in next slide) has higher “realism,” but object based (upper panel) is a true model and can be “walked through” and easily integrated with other data, such as hydrology, runoff, cuts and fills, etc.

Example of Contrast between Image- and Object-based Visualizations

Image-based visualizations can be used to create a simulated 3D

model

Panoramas

• Panoramas give students a realistic 360-degree view of a scene.

• LivePicture’s Photovista was used to easily stitch digital photos seamlessly.

Object-based visualization offers better data integration and hierarchical data

management with...

… increasingly complex queries based on object attributes

This contrast is similar to the distinction between raster and vector GIS; however,

the best visualizations use objects, imagery products, and GIS data freely.

Virtual Reality Modeling Language (VRML) facilitates this integration.

VRML is an ISO/IEC standard for creating 3D models for distribution over the web

For more info, see http://www.web3d.org/Specifications/VRML97/

Example:Satellite image turned into a true 3D

VRML object and integrated with GIS

VRML is the basis for 2 projects:

The Virtual U of A Campus project &The Virtual Santa Rita Experimental Range

Virtual Campus

• An online arena for students in the School of Art to preview their own sculptures in a section of campus– 2D, image-based techniques

• cut-and-paste image processing

• panoramas

– 3D, object-based model• generated from GIS

Before and after “Enquirer”-style image-processing

Erratic Sculpture

Campus Panoramas

• http://ag.arizona.edu/agnet/icac/

Virtual Campus Screen Capture

Digital Photo

Virtual Santa Rita Experimental Range

• Created from GIS using Arc/Info, ArcView with 3D Analyst, LizardTech’s MrSID, and custom-designed VRML with Javascript-driven Heads-Up Display

• Data covered:– Soil

– Pastures

– Rangesites

– Roads

– Vegetation Transects

– Rainfall history

Methods

• Satellite imagery and elevation data were used to generate a base for the model. Image processing was done in Adobe Photoshop and DEM to VRML conversion was done with author-built tools.

• Point data was dumped from DBF to ASCII using Arc/Info and imported into VRML using author-built tools. Reusable prototypes were created for each of the point data structures.– Raingauges (blue cylinders)

– Transects (yellow spheres)

Raingauges and Rainfall History in the VRML model

• Each instance inherits a name and an HTML anchor from its prototype

– Name becomes visible within a certain proximity

– Clickable - rainfall history is available for each raingauge on the range if that object is clicked

Raingauge #37

Methods (cont.)

We used ArcView’s 3D Analyst to overlay the polygon and line coverages on our DEM and exported it to VRML.

3D Analyst created seamless coverages, but the ability to control resolution and objectify different classes of the same overlay was lacking. As a result, the polygon and line coverages are not backed by data (static, unintelligible image).

We look forward to the extension of 3D Analyst to address these concerns.

Example of Pasture Coverage Overlaying Satellite Imagery

Example of Soils transparently overlaying the model

References

• Hodges, Mark, "Seeing Data in Depth", Computer Graphics World, May, 2000, p. 43 – 49.

• Mesher, "Designing Interactivities for Internet Learning", Syllabus, March, 1999, p. 16 – 20.

• Messmer, "E-comm Yet to Embrace Virtual Reality", Network World, May8, 2000, p.87.

• Polichar, Valerie E., Bagwell, Christine, "Pedagogical Principles of Learning in the Online Environment", Syllabus, May, 2000, p.52 – p. 56.

• Stolic, Mladen, "Digital Photography: Unleash the Power of 3-D GIS, GeoWorld, May, 2000, p. 30 – 37.

Useful tools

• Plugins: – Cosmoplayer - http://www.cosmoplayer.com

– Cortona - http://www.parallelgraphics.com/cortona/

– LivePicture - http://www.livepicture.com

– Photovista - http://www.livepicture.com

• VRML Tutorial:– http://www.vapourtech.com/vrmlguide/

Organizations/Useful websites• GeoVRML

– http://www.geovrml.org

• Web3D Consortium– http://www.web3d.org/

• Synthetic Environments Data Representation Information Project - The SEDRIS project is sponsored primarily by the

Defense Modeling and Simulation Office (DMSO), with engineering management support from the U.S. Army Simulation, Training and Instrumentation Command (STRICOM). Additional sponsorship and participation is provided by other government agencies, as well as industry partners.

– http://www.sedris.org

Contact Information

Aaryn Olsson - aaryn@ag.arizona.edu

Robert MacArthur - robmac@ag.arizona.edu

Forbes Bldg, Rm 218

University of Arizona

Tucson, AZ 85712

(520) 621-2489

Links from this paper

http://ag.arizona.edu/agnet/srer/vrml - Virtual SRERhttp://ag.arizona.edu/agnet/icac - Virtual Campushttp://ag.arizona.edu/agnet/esri2000/ - This Paperhttp://ag.arizona.edu/SRER/english_comp http://ag.arizona.edu/~robmac/web3d.htm