Journal Article

Self-Organizing Maps for Integrated Environmental Assessment of the Mid-Atlantic Region

O’Neill, Robert V., Tran, Liem T., Knight, C. Gregory, Smith, Elizabeth R., O’Connell, Michael

2003

Overview

A new method has been developed to perform environmental assessment at regional scale. This involves a combination of a 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 environmental impacts of multiple factors across a large region. Using data on land-cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic region, the method was able to indicate areas that are in relatively poor environmental condition or vulnerable to future deterioration. Combining the strengths of SOM with those of PCA, the method offers an easy and useful way to perform a regional environmental assessment. Compared with traditional clustering and ranking approaches, the described method has considerable advantages, such as providing a valuable means for visualizing complex multidimensional environmental data at multiple scales and offering a single assessment or ranking needed for a regional environmental assessment while still facilitating the opportunity for more detailed analyses.

• Publisher: Springer,Springer Nature B.V
• Subject: Air pollution / Animal, plant and microbial ecology / Applied ecology / Biological and medical sciences / Conservation, protection and management of environment and wildlife / Environmental assessment / Environmental conditions / Environmental impact / Environmental management / Environmental Monitoring - methods / Fundamental and applied biological sciences. Psychology / General aspects / Geographic Information Systems / Land pollution / Neural Networks (Computer) / Principal components analysis / Risk Assessment / United States