DYNAMIC GEOGRAPHIC PHENOMENA IN SPATIOTEMPORAL DATABASES

The growing availability of routine observations from
satellite imagery and other remote sensors holds
great promise for improved understanding of processes
that act in the landscape. However, geographers
ability to effectively use such spatial data is
challenged by large data volume and limitations of
conventional data models in geographic information
systems (GIS) which provide limited support for
querying and exploration of spatiotemporal data other
than simple comparisons of temporally referenced
snapshots. Current GIS representations allow
measurement of change but do not address coherent
patterns of change that reflects the working of
geographic events and processes. The work presented
here includes three self contained but related
studies: (1) development of a representational
framework that incorporates spatiotemporal properties
of geographic phenomena, (2) development of a
framework to characterize events and processes that
can be inferred from GIS databases, and (3)
development of a method to assess similarity of
events and processes based on the temporal sequences
of spatiotemporal properties.

Autorentext

John McIntosh is a GIS and database manager in environmentalconsulting. His interests include application of geotechniques toenvironmental management and remediation.May Yuan is Associate Dean of the College of Atmospheric andGeographic Sciences, Director of Center for Spatial Analysis andProfessor Of Geography, University of Oklahoma.

Klappentext

The growing availability of routine observations from satellite imagery and other remote sensors holds great promise for improved understanding of processes that act in the landscape. However, geographers' ability to effectively use such spatial data is challenged by large data volume and limitations of conventional data models in geographic information systems (GIS) which provide limited support for querying and exploration of spatiotemporal data other than simple comparisons of temporally referenced snapshots. Current GIS representations allow measurement of change but do not address coherent patterns of change that reflects the working of geographic events and processes. The work presented here includes three self contained but related studies: (1) development of a representational framework that incorporates spatiotemporal properties of geographic phenomena, (2) development of a framework to characterize events and processes that can be inferred from GIS databases, and (3) development of a method to assess similarity of events and processes based on the temporal sequences of spatiotemporal properties.