You are here:
INTEGRATION OF SPATIAL DATA: METHODS EVALUATION WITH REGARD TO DATA ISSUES AND ASSESSMENT QUESTIONS
Citation:
O'Connell, M., E R. Smith, R. V. O'Neill, L. T. Tran, AND N. W. Locantore. INTEGRATION OF SPATIAL DATA: METHODS EVALUATION WITH REGARD TO DATA ISSUES AND ASSESSMENT QUESTIONS. Presented at EPA 22nd Annual National Conference on Managing Environmental Quality Systems, New Orleans, LA, April 14-17, 2003.
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 is developing and demonstrating approaches to assess current and future environmental vulnerabilities at a regional scale. An initial effort within this research program has been to develop and evaluate methods to synthesize existing spatial data on resource condition and sensitivity, and estimated stressor distributions to facilitate decision-making on alternative environmental policies or risk management strategies. A total of 9 methods, ranging from simple spatial overlays to estimates of changes in multivariate state space, have been tested with regard to sensitivity to data issues such asi skewed distributions, continuous versus discontinuous data, and imbalance of indicators or metrics (e.g. a large amount of terrestrial data versus a small amount of aquatic! data), as well as suitability for addressing different assessment questions. Utilizing available data for the Mid-Atlantic region over a total of 73 variables, testing was also done tql identify whether different integration results were similar, or whether individual methods provide unique information and should be used in concert. The results of this analysis identifies potential limitations of methods due to data structure and suggests that assessment of vulnerabilities can best be accomplished using a suite of methods that rank on condition, vulnerability (risk of future damage), and risk management feasibility.