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SELF-ORGANIZING MAPS FOR INTEGRATED ASSESSMENT OF THE MID-ATLANTIC REGION
Citation:
Tran, L. T., C. G. Knight, R. V. O'Neill, E R. Smith, AND M. O'Connell. SELF-ORGANIZING MAPS FOR INTEGRATED ASSESSMENT OF THE MID-ATLANTIC REGION. ENVIRONMENTAL MANAGEMENT 31(6):822-835, (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:
A. new method was developed to perform an environmental assessment for the
Mid-Atlantic Region (MAR). This was a combination of the self-organizing map (SOM) neural network and principal component analysis (PCA). The method is capable of clustering ecosystems in terms of environmental conditions and suggesting relative cumulative impacts across a large region. Using data on land-cover, population, roads, streams, air pollution, and
topography of the Mid-Atlantic region, we were able to point out areas which were in relatively
poor condition and/or vulnerable to future deterioration, Combining the strengths of SOM with
PCA, the method offers an easy and useful way to perform a regional environmental assessment.