We found in an object-based accuracy assessment of a landcover polygon map (doi:10.1080/01431161.2013.875630) that the likelihood of correct classification of patches decreases as their size decreases, slightly for large and medium-sized patches, and more dramatically for patches within two orders of magnitude of the pixel size of the input image. Whenever the correct class of a misclassified patch is shared by a correctly classified adjacent patch, the local configuration of patches will be misrepresented in addition to the local composition of classes. Therefore, if further studies confirm the abrupt decline in accuracy we observed, the suggestion by Langford et al. (2006; Ecosystems 9: 474–488) that “there is potential for large errors in nearly every landscape pattern analysis ever published” would become an understatement. Are you aware of any studies beyond Smith et al. (2002; PE&RS 68:65-70) supporting (or contradicting) this finding, and do you think that if confirmed, this would be reason enough to abandon the patch-mosaic paradigm?
NB. For those lacking institutional access, a free copy of my article “The impact of object size on the thematic accuracy of landcover maps” can be downloaded from:
http://www.tandfonline.com/eprint/nTd7ZU2h2MYZ9mnqAFWJ/full
until the download allocation (50) is exhausted. Please do not use if you can download through your institution.
A couple years ago, I had the same question. The answer was definitely small patches more prone to misclassification than larger patches. Later on my research concern was on Biodiversity Economics and I found correlation with Fragstat Program. The concept of Biodiversity Economics is based on the 4 stages: Genes, Species, Ecosystems and their Functionality. The same approach is given by Fragstat program. Your study used reference data collected for the accuracy assessment of the Alberta Biodiversity Monitoring Institute’s (ABMI’s). The idea of Biodiversity Economics can be related either as Biological Science or Scale Approach. Landscape Metrics based on Remote Sensing Data can give you a key to judge landscape patterns. Review Article of Landscape Metrics Based on Remote
Sensing Data in Journal of Environmental Science and Engineering, 5 (2011) 1542-1560 is a suggestion when someone is working with anything related to biodiversity. In that article, I gathered authors papers on Landscape Metrics. In addition, some categorizations are performed in the same paper. As you mentioned for the heterogeneity as a measure in accuracy assessment which is considered as landscape metrics. Euclidean Nearest Neighborhood (ENN), Shannon Diversity Index (SHDI), Shape Index, Patch Density (PD) index, Proximity index, Number of Patches (NP) index are other proposed landscape indices. If you really want to be precise in your results use Biodiversity Economics concepts as the valuation tools. If you attain on RS approach for the accuracy assessments view Landscape Metrics based on RS or onsite data.
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