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Public agencies and corporate
landholders are developing and maintaining major environmental
databases for computerized mapping and analysis. The cost of such
databases increases rapidly with increasing level of spatial detail.
Objective and efficient methods are needed for determining patterns
of spatial variation from such databases, and for making pattern
comparisons between databases having different levels of detail.
This project undertakes development and operationalizing of relevant
quantitative/statistical methodology, with focus on application
to water resources and ecology of landscapes.
Comparison
of patterns emerging from data at different levels of detail will
promote cost-efficiency in selection of appropriate spatial resolution
for particular management purposes. Indicating likely zones of
greater spatial uncertainty will encourage targeted acquisition
of more detailed data that will improove return on investment
in information. There will be better basis for districting watersheds
and landscapes to reduce costs of monitoring and detecting need
for remediation. There will also be increased ability to detect
areas of disagreement between alternative hydrologic computer
models used in management of water resources, which will lead
to more precise modeling and calibration of models.
Principal Investigator:
G.P. Patil
Co-Principal Investigator: W.L. Myers
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