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A Prior Evaluation of Two-Stage Cluster Sampling for Accuracy Assessment of Large-Area Land-Cover Maps

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Abstract:Two-stage cluster sampling reduces the cost of collecting accuracy assessment reference data by constraining sample elements to fall within a limited number of geographic domains (clusters). However, because classification error is typically positively spatially correlated, within-cluster correlation may reduce the precision of the accuracy estimates. The detailed population information to quantify a priori the effect of within-cluster correlation on precision is typically unavailable. Consequently, a convenient, practical approach to evaluate the likely performance of a two-stage cluster is needed. We describe such an a priori evaluation protocol focusing on the spatial distribution of the sample by land-cover class across different cluster sizes and costs of different sampling options, including options not imposing clustering. This protocol also assesses the two-stage design's adequacy for estimating the precision of accuracy estimates for rare land-cover classes. We illustrate the approach using two large-area, regional accuracy assessments from the National Land-Cover Data (NLCD), and describe how the a priori evaluation was used as a decision-making tool when implementing the NLCD design.
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Citation:Wickham, J. D., S. V. Stehman, J. H. Smith, T. Wade, and L. Yang. A Prior Evaluation of Two-Stage Cluster Sampling for Accuracy Assessment of Large-Area Land-Cover Maps. INTERNATIONAL JOURNAL OF REMOTE SENSING 25(6):1235-1252, (2004).
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Contact: Chris Siebert - (702) 798-2234 or siebert.christopher@epa.gov
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Division: Environmental Sciences Division
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Branch: Landscape Ecology Branch
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Product Type: Journal
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Published: 03/20/2004
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Related Entries:
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Bullet Item Mrlc-Land Cover Mapping, Accuracy Assessment and Application Research
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