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• W2037873485 abstract "Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias." @default.
• W2037873485 created "2016-06-24" @default.
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• W2037873485 date "2009-06-15" @default.
• W2037873485 modified "2023-10-17" @default.
• W2037873485 title "Estimating accuracy of land-cover composition from two-stage cluster sampling" @default.
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• W2037873485 doi "https://doi.org/10.1016/j.rse.2009.02.011" @default.
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