GeoSpatial and GeoTemporal Informaticsfor dynamic and complex systems

May Yuan

What is solved

• Integration of spatial and temporal data– Location and snapshot– Dimensional, typological, and typological issues

• Empirical and computational solutions– Spatiotemporal statistics / time geography– Spatial data mining– Machine learning and artificial intelligence– Cellular automata– Agent-based modeling– Evolutionary algorithms

What is almost solved?

• Refined observation networks and data assimilation– Smart sensor networks– Adaptive sensor networks– Data-model assimilation

• Refined statistical and modeling approach to account for geographic dynamics and complexity– Data stream mining– Intelligent agents– Geographically aware agents– Adaptive agents

What has failed? Include surprised failures

• Fail is a strong word. Perhaps, appears limited• Space-time composite model• Intelligent highways• Integration of sensor networks across scales (local,

regional, and global) to automatically relate phenomena and processes across scales

• Communication among heterogeneous networks– Climate– Ecology– hydrology

What is missing (discuss areas not currently on the radar)

• From space-time observations to spatiotemporal processes• Informatics framework to automate recognition of events and

processes • Analysis of events and processes

– Weather (obs > events > systems > severity)– Population (obs > migration > gentrification)

state

process

spatiotemporal data

event

measured bysensors

trigger

drive

What next? Include both high risk and needed topics

• P2P sensor networks• Informatics Theory of Geographic Dynamics and Complexity

• Ontology• Representation: flows, vector fields• Analytical and computational approaches that address multi-scalar

relationships among observations, geographic dynamics, and geographic systems

• Modeling approaches to address interactions among dynamics of different kinds across scales and domains– Climate and ecology– Politics and sociology– Climate and society

– New levels of knowledge representation– Aggregates, agglomerates, and narratives

• By telling and listening to stories, we communicate, learn, and make sense of the world by ordering events and assimilating them to find meanings and implications (Mateas and Sengers 2003).

• Narrative GIS that can tell stories• Visual means to tell stories

Narratives and sensing making