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Abstract
The objective of this analysis is to develop a method of classification error assessment that can contribute to techniques designed to evaluate change products with an emphasis on edge locations in landscapes. Reference land-cover data were developed within 10 randomly sampled regions across the study site, approximately 9 km2 each. Sample pixels were partitioned and allocated among two domain categories, interior and edge. The assignment of pixels to domain categories was based on neighbourhood heterogeneity. Classification error was assessed within domain categories on a pixel-by-pixel basis, evaluating agreement between map values and majority land cover. To demonstrate the methodology, we present summary results for this technique applied to a land-cover classification of south-central Indiana. Omission error was less than 8.3% within interior domains and from 25.8% to 36.4% in the edge. Commission error was below 26.7% within the interior domains and ranged from 13.9 to 74.6% in the edge domains.
Acknowledgements
We gratefully acknowledge support from the Human and Social Dynamics programme at the National Science Foundation through funding to the Center for the Study of Institutions, Population, and Environmental Change, Indiana University (grant BCS0624178). We would like to extend special thanks to Joanna Broderick, Technical Editor/Publications Coordinator at the Center for the Study of Institutions, Populations, and Environmental Change and to Tatyana Ruseva for reading multiple versions of this article.