Transcript Rediscovering the World through Geographic Information Systems

New GIS computer in Valley Library
3rd floor Map Collection
• Windows 2000
• 1Ghz Pentium III processor with 256Mb of memory
• zip drive and CD/DVD, no scanner or printer yet
ArcGIS 8 plus extensions
ERDAS Imagine 8.5
TIGER_CTSI
ArcView 3.2 and extensions forthcoming
Representations / Models
Longley et al., chs. 2-3
Zeiler, chs. 2-3
Why Representations or
Models?
• How do we know what we know?
• Human sight
– Visible spectrum, horizon at ~10km
visibility 100 km
• Human sound
– 50Hz to 15KHz up to 100 m
• Taste, Touch, Smell
Knowing the World
• Everything else via communication
– Speech
– Text
– Photographs
– Radio, TV
– Maps
– Internet
– Databases
Surface of the Earth?
• 500,000,000 sq km
– on average 100 sq m is sensed directly
p = 100/500,000,000,000,000 m
p = 0.0000000000002 or 2 x 10 -13 spatially
• 5 billion years
– we live through 70
p = 70/5,000,000,000
p = 0.000000014 or 1.4 x 10 -8 temporally
\ we know almost nothing of the surface
of the Earth via our senses!
Communicated Information
• decide where to go as tourists,
shoppers
• choose study areas for research
• manage parks, reserves
• choose where to live
• All such information must use a
representation
Representation in Space/Time
Representation in Space/Time
• What would more
detail show?
• Simplification
• Infinite complexity
• must reduce to
manageable volume
Where do Representations occur?
• the human mind, in memory and
reasoning
• speech
• written text
• photographs
• digital databases
• GIS !
Representations are crucial...
• for communication (metaphors,
expressions)
• going beyond the space-time limits of
our senses
• dealing with an infinitely complex world
DIGITAL Representation
• Much human communication is now
digital (email, fax, voice mail, DVD…)
• sent through a “pipe” consisting of 0s
and 1s
• stored on devices that can store only
0s and 1s
• processed as 0s and 1s
Digital
• from “digit”, finger
• character in a counting
system
• numbers 0 through 9
• 0 and 1 - binary system
• "digital"="binary"
Digital (cont.)
• how to express knowledge
exclusively in 0s and 1s?
• how to describe complexity of
world in 0s and 1s?
• the fundamental question of data
modeling for GIS
Communication via a channel
Communication via a channel
• How efficient is the
channel?
• is there information that
can't be expressed?
• text omits gesture,
pronunciation, voice
inflection
• GIS as a communication
channel?
• what information about a
place can't be expressed in
GIS?
Communication via a channel
• what if the sender and receiver can't
understand each other?
– different language
– different alphabet
– different GIS
– interoperability
GEOGRAPHIC Representation
• information about some place
– at or near the surface of the Earth
– at some time
• one of the earliest forms of shared
information
– drawings on cave walls (“good hunting
near the old tree”)
– Stick maps in the Pacific (“steer by this
star or island”)
• Printing press to Internet
Geographic Information
• “Location, location, location!”
– to map, to link based on the same place,
– to measure distances and areas
• Time
– height above sea level (slow?)
– Sea surface temperature (fast)
• Attributes
– physical or environmental
– soci-economic (e.g., population or income)
Geographic Information
The “atom” of geographic information
< location, time, attribute >
“It’s warm today in Corvallis”
< Corvallis, today, warm >
“at 44° N, 123° E at 12 noon PST the
temperature was 60°F”
Describing LOCATION
Time ok, Attributes Not Always
• “warm” is subjective
and relative
• 60°F generally
understood
• did Hugh Grant
climb a hill or a
mountain?
A Complete Representation
•
•
•
•
DIGITAL and GEOGRAPHIC
complete representation of the planet
past, present, and future
“Digital Earth”
– a “camera” pointed at a sunlit Earth
– a virtual, immersive world
Simulated image from NASA’s
STRM, Carrizo Plain, S. Calif.
Atoms of Geographic Information
• an infinite number
• two-word description of every sq km on
the planet, 10 Gb
• store one number for every sq m, 1 Pb
(trillion bytes)
www.ccsf.caltech.edu/~roy/dataquan/
• Too much for any system
• How to limit?
Limiting Detail
• aggregate, generalize, approximate
• ignore the water?!
– 2/3 of planet!
• one temperature for all of Corvallis
– one number for an entire polygon
• sample the space
– only measure at weather stations, temp.
varies slowly
• all geographic data miss detail
– all are uncertain to some degree
The Problem of Infinite Complexity
• many ways of limiting detail
• a GIS user must make choices
• GIS developers must allow for many
options
• Most important option is how we
choose to think about the world
Objects and Fields
Lakes in Minnesota?
Clouds in sky?
Fish in the sea?
Atmospheric highs in N.
hemisphere?
Objects
• Well-defined
boundaries in empty
space
• “Desktop littered w/
objects”
• World littered w/ cars,
houses, etc.
• Counts
• 49 houses in a
subdivision
Fields:
care to count every peak, valley,
ridge, slope???
Fields
worth measuring at every point on the planet
• Radiation captured by satellite
• Elevation
• Temperature
• Soil type
• Soil pH
• Rainfall
• Land cover type
• Ownership
An image of part of the lower Colorado River in the southwestern USA. The lightness of the image at any point
measures the amount of radiation captured by the satellite's imaging system. Image derived from a public domain
SPOT image, courtesy of Alexandria Digital Library, University of California, Santa Barbara.
Fields
• each variable has one
value everywhere
• variable is a function of
location
• field = a way of conceiving of
geography as a set of
variables, each having one
value at every location on the
planet
• zf = f (x,y,z,t)
One Variable as Raster, TIN
One Variable as Poly, Pt, Contour
Fields and Objects
• Both objects and fields can be
represented either in raster or in vector
form
• Objects are intuitive, part of everyday
life
– how many lakes in Minnesota?
• Fields are more associated with
science
– fronts, highs, lows, or pressure surfaces?
Ontology
• Ontology: the study of the basic
elements of description
• "what we tell about"
• Semantics
• discrete objects and fields are two
different ontologies
www.ucgis.org/emerging/
Golledge, R., 2002, The Nature of Geographic
Knowledge, Annals of the AAG, 92(1): 1-14.