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Environmental Modeling and Digital Earth

Environmental Modeling and Digital Earth. Michael F. Goodchild University of California Santa Barbara.

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Environmental Modeling and Digital Earth

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  1. Environmental Modeling and Digital Earth Michael F. Goodchild University of California Santa Barbara

  2. “Imagine, for example, a young child going to a Digital Earth exhibit at a local museum. After donning a head-mounted display, she sees Earth as it appears from space. Using a data glove, she zooms in, using higher and higher levels of resolution, to see continents, then regions, countries, cities, and finally individual houses, trees, and other natural and man-made objects. Having found an area of the planet she is interested in exploring, she takes the equivalent of a ‘magic carpet ride’ through a 3-D visualization of the terrain.”

  3. “She is not limited to moving through space, but can also travel through time. After taking a virtual field-trip to Paris to visit the Louvre, she moves backward in time to learn about French history, perusing digitized maps overlaid on the surface of the Digital Earth, newsreel footage, oral history, newspapers and other primary sources. She sends some of this information to her personal e-mail address to study later. The time-line, which stretches off in the distance, can be set for days, years, centuries, or even geological epochs, for those occasions when she wants to learn more about dinosaurs.”

  4. “I have proposed something called the Digital Earth program, which is designed to build a new global climate model capable of receiving data from several different sources that are not considered compatible by today’s definition.” Al Gore, Earth in the Balance, p. 358

  5. New funding opportunities • U.S. National Science Foundation Information Technology Research (NSF-00-126): • Geoscience Modeling and Representation: Studies that enable better use of large scale data sets in the geosciences and about the Earth system and geosciences in general

  6. The Digital Earth community • www.digitalearth.gov • www.digitalearth.ca • Interagency Digital Earth Workshops • 9th mtg National Science Foundation 9/6 • Digital Earth Community Meetings • 4th mtg National Geographic Society 9/19 • International Symposia on Digital Earth • 2nd mtg Fredericton, NB, Canada, 6/24/01

  7. Perspectives on Digital Earth (1) • High-end visualization • an immersive environment • specialized hardware • massive bandwidth requirements • Spin, zoom, pan • "fly-by" technology • 4 orders of magnitude zoom • 10km to 1m

  8. Does DE scale? • 500,000,000 sq km • 5 million at 10km resolution • 500,000,000,000,000 at 1m resolution 500,000,000,000,000 500,000,000 seconds 138,888 hours 69.4 working years

  9. Transmitting Digital Earth • 1m resolution at T1 (order 10 megabits/sec) • 69.4 working years • 1m resolution at 56k • done in 12,400 years • The Internet-killer

  10. What resolution do we really need? • Whole Earth at 10km • California at 1km • Santa Barbara County at 100m • LOS (extent divided by resolution) • order 103 or 104 • ratio for computer screen • ratio for human retina

  11. The Internet can support DE • 1 refresh per second, 1 megapel images (LOS=103) • T1 rates without compression • 10+ refreshes per second with compression • sufficient for zoom, pan, flyby

  12. Research challenges • Smooth zoom • 10km to 1m resolution • consistent data structures • smooth transitions to more detailed data • color matches • projections • orthographic for the globe • projected for local detail • Georgia State: nested azimuthal projections

  13. Research challenges (2) • Visualization • renderable data • non-renderable data • iconic representation indicating presence • symbolic representation • user-centered views • reduce resolution in periphery • avatar • What about a 200MHz PC? • Ric Cicone, IScience

  14. Research challenges (3) • Consistent data structures • hierarchical schemes • triangles • easily rendered by standard graphics firmware • nest • tile the globe

  15. Discrete global grid based on the Icosahedron (20 triangles, 1:4 recursive subdivision) Ross Heikes and David Randall, Colorado State University

  16. Perspectives on Digital Earth • 2. A metaphor for organizing information • two key concepts • The geolibrary • a library that is searchable by geographic location • "what have you got about there?" • physically impossible but feasible in a digital world

  17. NRC report • "Distributed Geolibraries: Spatial Information Resources”, 1999 www.nap.edu

  18. Organizing information by location • Information with a geographic footprint • Organizational metaphors • the desktop, office, workbench • the surface of the Earth

  19. SPOT image available Date 3/10/98

  20. Research challenges • Defining footprints • fuzzy, vernacular • Mapping between georeferencing methods • the gazetteer • Search over a distributed archive • search engines • object-level metadata (OLM) • collection-level metadata (CLM)

  21. CLM of the Alexandria Digital Library

  22. Research challenges (2) • Approaches to CLM • by data type • ortho.mit.edu • by area of the globe • SRI's Digital Earth • the one stop shop • www.fgdc.gov • a new generation of search engines • identifying footprints

  23. Perspectives on Digital Earth • 3. The Mother of All Databases (MOADB) • A distributed collection of knowledge about the Earth • transparent to the user • accessible through geolibrary mechanisms • supported by consistent protocols

  24. Perspectives on Digital Earth • 4. A collection of knowledge about the Earth's dynamics • the processes that create and modify the landscape • Dynamics or statics? • most GIS data are cross-sectional time-slices • providing facts • understanding of the Earth must focus on processes

  25. A dynamic Digital Earth • Simulations of past and future conditions • A library of simulation models • applied to local conditions represented by data • A tool with enormous educational value • PCRaster demonstrations • University of Utrecht, Peter Burrough

  26. Example of diffusion modeling • Dispersion of individuals over a space in which the resistance to movement is variable, individuals need to work together to colonize new areas diffusion

  27. Research challenges • Data structures and modeling • no finite difference models on the curved surface of the planet • no square cells for cellular automata • finite element models, CA based on triangles? • triangles are not uniform in topology or geometry • object-based models

  28. Towards an infrastructure for dynamic models • Infrastructure for sharing • search • discovery • evaluation of fitness for use • acquisition • execution • Server-side or client-side execution

  29. Falling through the cracks • Text-sharing infrastructure • libraries, bookstores, books, journals, WWW, search engines • Data-sharing infrastructure • metadata schema, archives, clearinghouses, data centers • Model-sharing infrastructure • models are the highest form of sharable knowledge of the Earth system

  30. Current status • Some archives • some pre-WWW • No standards • No clearinghouses • www.ncgia.ucsb.edu/~scott

  31. Building a metadata standard • 1. A model is a transformation • characterized by metadata for inputs and outputs • 2. Write down the key elements • compare FGDC CSDGM • 3. How do humans do it? • we’ve been doing it for decades • A first-draft standard

  32. Models as reusable scripts • Universal modeling language for EM • Van Deursen, PCRaster • Object-based modeling languages • Scripts playable with universal software

  33. Model granularity • How big are the pieces? • Software as reusable components • 2,000 for ArcInfo 8 • Online EM communities • open standards

  34. Summary: four perspectives • An immersive environment • A metaphor for information organization • A distributed database transparent to the user • A representation of the planet's dynamics

  35. DE as an instance • Digital representations of large systems • Virtual Human • Virtual City • Virtual Cosmos • Organized in spatial framework • named places in the space (gazetteer) • Permit virtual exploration, experimentation

  36. What distinguishes DE? • Volume of available data • Richness of applications • Importance of dynamics

  37. Digital Earth: a mirror world • Models of the Earth • maps • descriptive text • process models • Collectively, a storehouse of knowledge about the planet • distributed • digital • captures our understanding of the world

  38. DE and the EM community • An opportunity to build an infrastructure • knowledge as a communal asset • knowledge of dynamics • Integration of education • somewhere to start

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