Michael F Goodchild University of California Santa Barbara Scientific tradition The lone investigator looking for simple truths Newtons gravitation Mendeleevs periodic table Maxwells electromagnetism ID: 587446
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Slide1
Integrating Space-Time Analysis
Michael F. Goodchild
University of California
Santa BarbaraSlide2
Scientific traditionThe lone investigator looking for simple truths
Newton’s gravitation
Mendeleev’s periodic table
Maxwell’s electromagnetismSchroedinger’s quantum theoryScience by teamworkJames Watson and Francis CrickRosalind Franklin’s observationsSlide3
Science as teamworkAll of the simple discoveries have been made
Discoveries about complex systems need teams
powerful data acquisition systems
and sophisticated toolsespecially when those systems are embedded in geographic space and timeScience must engage with policyscience does not end in the pages of refereed journalspackaging science for general consumptionSlide4
From spatial to spatiotemporalEarly map-based GIS
2D and static
matching the availability of data
matching our conceptual abilitiesoverlay, the “GIS spike”Slide5
Time is of the essencePolicy and public interest are driven by change (Frank)
Everything that happens happens somewhere in space
and time
(Wegener)Every major issue has a time scaleclimate change (decades)climate tipping points (years)economic meltdown (months)infectious diseases (weeks)disasters (days)Slide6
Studying complex problemsIn space and time
u
sing
sophisticated tools and voluminous dataDomain-specific or domain-neutral?is it possible to design generic tools that can be applied to any space-time dataspatial interpolation using Kriging or IDWor should tools be to some extent specific to the domain?
and how specific?
“physics-based” or theory-based tools
spatial interpolation incorporating orographic effectsSlide7
How to design these tools?The Waterfall process?
define the application domain
sample it with use cases
define the necessary functionalitydesign optimal data modelsIs the domain all of spatiotemporal analysis and modeling?from social to environmental
if not, what defines those domains?
concepts of process
types of dataSlide8Slide9
A short history of GIS data modeling
Canada Geographic Information System (1965)
all inputs area-class maps
US Bureau of the Census (1972)reporting zones as polygon coveragesTopological Data Structures meeting (1977)ODYSSEY, ARC/INFOIntergraph’s TIGRISOne data model, multiple applications
economies of scale in software developmentSlide10
GIS todayMany more data types
Object-oriented paradigm
Data are increasingly 3D, dynamic
Is there still the potential for a unified approachwith its massive scale economies?What divisions exist within the spatiotemporal domain?can we repeat the process of the 1970s?Slide11
1. Tracking
Movement of features in space and time
GPS
RFIDother technologiesSlide12
CASA UCL, http://www.casa.ucl.ac.uk/capableproject/maps/home.aspSlide13
Light-level geolocation (Stutchbury
et al.
, Science 2/13/09)
Purple Martin
Wood ThrushSlide14
Tracks inferred from Flickr postings (http://www.cs.cornell.edu/~crandall/papers/mapping09www.pdf)Slide15
FunctionalityHägerstrand’s conceptual framework
new advances in theory
Track interpolation
between infrequent samplesInferences about activityTrack convergenceShih-Lung Shaw’s ArcScene extensionTheory guiding research questionsSlide16
2. SnapshotsBarry Smith’s SNAP ontology
Time-series of remotely sensed images
Video
Change detectionSpatiotemporal interpolationLongitudinal consistencySlide17
Rondonia, Brazil, 1975, 1986, 1992Slide18Slide19Slide20
3. Polygon coveragesGail Langran,
Time in Geographic Information Systems
, 1992
National Historic GISreconciling change in reporting zonesz(i,t) = f[z(
i
,
t
-1),
z
(
j
,
t
),…]
Serge Rey’s STARS – Space-Time Analysis of Regional SystemsSlide21
Comparative spatial analysis of the development of the Chinese and US economies through time, 1978-1998
Xinyue Ye, Bowling Green State UniversitySlide22
4. Cellular automataA fixed raster of cells
A set of states for each cell
A set of rules that determine state transitions through time
PCRasterSlide23
Keith Clarke, UC Santa Barbara
CA model of development based on transition probabilities as functions of slope, access to transportation, zoning, and states of neighboring cellsSlide24
5. Agent-based modelsDiscrete agents as geographic features
Moving, changing state
Rules governing states, behaviorSlide25Slide26Slide27
6. Events and transactionsThe domain of the historian
events in space and time
linked spatially
campaigns of armieshierarchically relatedthe battle and the warthe meeting and the electioncan GIS support historical scholarship?and update the historical atlasSlide28
7. Multidimensional dataEnvironmental data intensively sampled in time
with fixed
and sparse spatial support
Atmospheric science, oil and gas, groundwaterFauerbach, Edsall, Barnes, MacEachren
animationSlide29
One domain or seven?All seven need the multidisciplinary tools of GIS
to interpret, assess, and visualize results
to package results for public
consumptionAll seven need to be informed by domain-specific theoryAll need to run faster than realityan issue with time-critical applicationse.g. evacuation modelsmay necessitate custom software
e.g. parallel processingSlide30
Tasks for the research community
What are the research questions?
what are the use cases?
some domains may be driven by data availability rather than research needsWhat are the functions?at what level of granularity?standardized for discoveryelusive even for traditional GISWhat are the data models?
the focus of much of the research to date