Self-Organizing Maps for Integrated Environmental Assessment of the Mid-Atlantic Region |
| |
Authors: | Tran Liem T Knight C Gregory O’Neill Robert V Smith Elizabeth R O’Connell Michael |
| |
Institution: | (1) Center for Integrated Regional Assessment and Department of Geography, The Pennsylvania State University, 2217 Earth and Engineering Sciences Building, University Park, PA 16802, USA;(2) T.N. and Associates, 124 South Jefferson Circle, Oak Ridge, TN 37830, USA;(3) United States Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, U.S. EPA (E243-05), 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, USA;(4) Waratah Corporation, 2505 Meridian Parkway, Suite 175, Durham, NC, USA |
| |
Abstract: | 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. |
| |
Keywords: | Environmental assessment Self-organizing map Principal component analysis Cumulative impact |
本文献已被 PubMed SpringerLink 等数据库收录! |
|