An evaluation of sampling strategies to improve precision of estimates of gross change in land use and land cover

Statistical sampling offers a cost-effective, practical alternative to complete-coverage mapping for the objective of estimating gross change in land cover over large areas. Because land cover change is typically rare, the sampling strategy must take advantage of design and analysis tools that enhance precision. Using two populations of land cover change in the eastern United States, we demonstrate that the choice of sampling unit size and use of a survey sampling regression estimator can significantly improve precision with only a minor increase in cost.