Citation:

Smith, E R., L. T. Tran, AND R. V. O'Neill. INTEGRATION OF SPATIAL DATA: EVALUATION OF METHODS BASED ON DATA ISSUES AND ASSESSMENT QUESTIONS. Presented at US EPA 23rd Annual National Conference on Managing Environmental Quality Systems, Tampa, FL, April 13-16, 2004.

Impact/Purpose:

Provide regional-scale, spatially explicit information on the extent and distribution of both stressors and sensitive resources.

Develop and evaluate techniques to integrate information on exposure and effects so that relative risk can be assessed and management actions can be prioritized.

Predict consequences of potential environmental changes under alternative future scenarios.

Effectively communicate economic and quality of life trade-offs associated with alternative environmental policies.

Develop techniques to prioritize areas for ecological restoration.

Identify information gaps and recommend actions to improve monitoring and focus research.

There are two task objectives that reflect the work done by LCB in support of the ReVA Program objectives:

Provide information management, spatial analysis support, and data and information accessibility for the ReVA Program

Provide program management support, technology transfer, and outreach.

Description:

EPA's Regional Vulnerability Assessment (ReVA) Program has focused initially on the synthesis of existing data. We have used the same set of spatial data and synthesized these data using a total of 11 existing and newly developed integration methods. These methods were evaluated in terms of 1) how well each individual method performs given different data issues that are encountered with existing data, and 2) how effectively each method addresses different types of assessment questions.

Specific data issues that are addressed in our evaluation of integration methods include:

Discontinuity -How are the methods affected by variables that (in raw form) are counts, such as number of aquatic species, versus having only continuous data?

Imbalance -What effect does having too many variables of a particular type ( e.g. representative of terrestrial conditions versus aquatic) have on the integration results from individual methods?

Skewness -What effect does having variables with highly skewed distributions have on integration results? Many statistical methods are valid only for symmetrically distributed data or require transformation of the data.
Interdependency -How are the methods affected by including variables that are highly correlated with one another?

Prioritization of risk management actions involves balancing many different factors that can be addressed through a series of assessment questions. ReVA's evaluation of integration methods considers which methods are most suitable to address questions such as:

What is the overall environmental condition of the region?
What is the relative condition of locations within a region?
Where are the most vulnerable (i.e. both high stressor levels and high numbers of resources) locations in a region?
How will conditions and vulnerabilities change in the future?
How applicable are risk management options to other locations in the region?

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