Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USA
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Abstract
A vegetation community map was produced for the Ozark National Scenic Riverways consistent with the association level of the National Vegetation Classification System. Vegetation communities were differentiated using a large array of variables derived from remote sensing and topographic data, which were fused into independent mathematical functions using a discriminant analysis classification approach. Remote sensing data provided variables that discriminated vegetation communities based on differences in color, spectral reflectance, greenness, brightness, and texture. Topographic data facilitated differentiation of vegetation communities based on indirect gradients (e.g., landform position, slope, aspect), which relate to variations in resource and disturbance gradients. Variables derived from these data sources represent both actual and potential vegetation community patterns on the landscape. A hybrid combination of statistical and photointerpretation methods was used to obtain an overall accuracy of 63 percent for a map with 49 vegetation community and land-cover classes, and 78 percent for a 33-class map of the study area.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Mapping vegetation communities using statistical data fusion in the Ozark National Scenic Riverways, Missouri, USA |
| Series title | Photogrammetric Engineering and Remote Sensing |
| DOI | 10.14358/PERS.74.2.247 |
| Volume | 74 |
| Issue | 2 |
| Year Published | 2008 |
| Language | English |
| Publisher | American Society for Photogrammetry and Remote Sensing |
| Contributing office(s) | Columbia Environmental Research Center |
| Description | 18 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Photogrammetric Engineering and Remote Sensing |
| First page | 247 |
| Last page | 264 |
| Google Analytic Metrics | Metrics page |