Ronald E. McRoberts

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among state and federal agencies. The FHM program focuses on assessing and monitoring the health and sustainability of the nation’s forests and consists of four primary activities: detection monitoring, evaluation monitoring, intensive site monitoring, and research on monitoring techniques. Together, these four activities permit predictions of where and how(More)
Estimates of forest area were obtained for the states of Indiana, Iowa, Minnesota, and Missouri in the United States using stratified analyses and observations from forest inventory plots measured in federal fiscal year 1999. Strata were created by aggregating the land cover classes of the National Land Cover Data (NLCD), and strata weights were calculated(More)
km) centered at the exact locations, although the radii for most perturbations are less than 0.5 mi (0.8 km). Swapping consists of exchanging the locations for a small proportion of close proximity, ecologically similar, privately owned plots. Similarity criteria vary regionally but often include forest type group, stand size, and geographic proximity.(More)
Tremendous advances in the construction and assessment of forest attribute maps and related spatial products have been realized in recent years, partly as a result of the use of remotely sensed data as an information source. This review focuses on the current state of techniques for the construction and assessment of remote sensing-based maps and addresses(More)
This paper focuses on the use of models for increasing the precision of estimators in large-area forest surveys. It is motivated by the increasing availability of remotely sensed data, which facilitates the development of models predicting the variables of interest in forest surveys. We present, review and compare three different estimation frameworks where(More)
USDA Forest Service Forest Inventory and Analysis plot information is widely used for timber inventories, forest health assessments, and environmental risk analyses. With few exceptions, true plot locations are not revealed; the plot coordinates are manipulated to obscure the location of field plots and thereby preserve plot integrity. The influence of(More)
In applications of the k-nearest neighbour technique (kNN) with real-valued attributes of interest (Y) the predictions are biased for units with ancillary values of X with poor or no representation in a sample of n units. In this article a modelassisted calibration is proposed that reduces unit-level extrapolation bias. The bias is estimated as the(More)