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Research Interests:
My areas of research interest are geographic information systems (GIS),
geographic knowledge discovery, and geo-visualization. These three components
of my research are closely related and can be integrated within the
context of environmental modeling. 
Specifically, geographic information systems enable the collection,
geo-coding, storage, preprocessing, and static display of environmental
data and the construction of spatial databases. Geographic knowledge
discovery is the extraction of spatial relations or patterns not explicitly
stored in spatial databases. This is achieved through intelligent data
mining algorithms. Applied to environmental data, these algorithms can
be used to extraction relationships between variables in the environmental
system and make predictions on certain variables given others measured.
Geo-visualization involves the use of visual representations to make
spatial contexts and problems visible, often with an interactive and
animated visualization environment. It has been realized as an effective
tool to explore geographic data and communicate geographic information
to private or public audiences. In this means, it plays important roles
in both geographic knowledge discovery and presenting the patterns or
relationships extracted through geographic knowledge discovery.
Current Research:
My research examines geographic knowledge discovery (or spatial data
mining) for environmental modeling. Specifically,
my past and current research addresses the issue in the following aspects:
1) examining geographic knowledge discovery and classification from
the perspective of human cognition, 2) developing schemes for organizing
knowledge used in categorizing and mapping spatial entities with indeterminate
boundaries, such as natural resource classes, wildlife habitats, natural
hazards, among others, 3) integrating geo-visualiztion with geographic
knowledge discovery for extracting spatio-temporal patterns, 4) investigating
data mining algorithms for extracting such knowledge from spatial databases,
and 5) applying the algorithms in modeling environmental variables such
as air pollution.
Future Research:
My future research efforts will follow several directions:
1) Spatial data mining. I will continue my research efforts in spatial
data mining and geographic knowledge discovery. I will expand my research
to multi-scale data mining, data mining of long term climate data for
extreme weather event patterns, spatio-temporal data mining for modeling
contagious disease transmission and wildlife migration patterns.
2) Visualization. I will continue my research in this area and explore
effective visualization methods for spatio-temporal modeling or urban
air quality. 
3) Environmental modeling. I will expand my research applications in
soil mapping to other areas.
4) GIS applications in the Humanities. GIS methods can be used to analyze
social problems such as urban segregation, criminal justice, etc.

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