Incorporating spatial and operational constraints in the sampling designs for forest inventories

摘要

Besides the evaluation of the volume of standing trees, goals of forest inventories include collecting geophysical information and monitoring fragile ecosystems. In the province of Quebec, Canada, their implementation faces challenging methodological problems. The survey area covers a large territory that is hardly accessible and has a diverse forest. The main operational goals are to spread the sampled plots throughout the survey area and to capture, in the sample, the forest heterogeneity while keeping the cost at a reasonable level. In many inventories, a two-dimensional systematic sampling design is applied, and the rich auxiliary information is only used at the estimation stage. We show how to use modern and advanced sampling techniques to improve the planning of forest inventories and meet complex operational goals. For the Quebec forest inventory, we build a two-stage sampling design that has clusters of plots to optimize field work and predetermined sample sizes for forest types. Constraints of spreading the sample in the whole territory and of balancing according to auxiliary variables are also implemented. To meet these requirements, we use unequal inclusion probabilities, balanced sampling, highly stratified balanced sampling, and sample spreading. The impact of these novel techniques on the implementation of requirements and on the precision of survey estimates is investigated using Quebec inventory data. Copyright (C) 2015 John Wiley & Sons, Ltd.