Modeling sensitivity to accuracy in classified imagery: a study of areal interpolation by dasymetric mapping.
Part of a special section on the creation of meaningful and appropriate spatial units of analysis and their use in further geographic analysis. A study was conducted to examine the propagation of error in a classified Landsat image into the areal interpolation of population counts. Areal interpola...
| Publicado en: | Professional Geographer Vol. 48; pp. 299 - 310 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Taylor & Francis Ltd
August 1996
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Part of a special section on the creation of meaningful and appropriate spatial units of analysis and their use in further geographic analysis. A study was conducted to examine the propagation of error in a classified Landsat image into the areal interpolation of population counts. Areal interpolation is defined as the process by which data gathered from one set of zonal units can be estimated for another zonal division of the same space that shares few or no boundaries with the first. The methods of areal interpolation examined are reviewed, and the error modeling procedures employed are outlined. The nature of the errors in classified Landsat imagery is discussed, and methods for simulating errors in a classified image are presented. The findings reveal that population estimates by dasymetric mapping are largely insensitive to errors of classification in the Landsat image when compared with other methods tested. |
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