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Incorporating Spatial and Operational Constraints in the Sampling Designs for Forest Inventories
Goals of forest inventories include understanding the forest temporal evolution and monitoring fragile ecosystems. In the province of Quebec, Canada, their implementation faces challenging methodological problems. The survey area covers a large territory which is hardly accessible and has diverse forest. Main operational goals are to spread the sampled plots throughout the survey area and to well represent all forest types in the sample. They are hard to achieve while keeping the costs within budget. Usually, 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, considering many requirements. 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.
Fast Balanced Sampling for Highly Stratified Population
Balanced sampling is a very efficient sampling design when the variable of interest is correlated to the auxiliary variables on which the sample is balanced. Chauvet (2009) proposed a procedure to select balanced samples in a stratified population. Unfortunately, Chauvet's procedure can be slow when the number of strata is very large. In this paper, we propose a new algorithm to select balanced samples in a stratified population. This new procedure is at the same time faster and more accurate than Chauvet's. Balanced sampling can then be applied on a highly stratified population when only a few units are selected in each stratum. This algorithm turns out to be valuable for many applications. For instance, it can improve the quality of the estimates produced by multistage surveys for which only one or two primary sampling units are selected in each stratum. Moreover, this algorithm may be used to treat nonresponse.
Incorporating spatial and operational constraints in the sampling designs for forest inventories
In the province of Quebec, Canada, the forest is examined through regular inventories. Requirements for the spreading and the type of trees and for the cost are difficult to manage. We show that modern and advanced sampling techniques can be used to improve the planning of the forest inventories, even if there are many requirements. Our design includes balanced sampling, highly stratified balanced sampling and sample spreading through a two stage sample. The impact of these techniques on the satisfaction of the requirements and on the precision of survey estimates is investigated using field data from a Quebec inventory.
Variance estimation of changes in repeated surveys and its application to the Swiss survey of value added
We propose a method for estimating the variance of estimators of changes over time, a method that takes account of all the components of these estimators: the sampling design, treatment of non-response, treatment of large companies, correlation of non-response from one wave to another, the effect of using a panel, robustification, and calibration using a ratio estimator. This method, which serves to determine the confidence intervals of changes over time, is then applied to the Swiss survey of value added.
Incorporating spatial and operational constraints in the sampling designs for forest inventories
In the province of Quebec, Canada, the forest is examined through regular inventories. Requirements for the spreading and the type of trees and for the cost are difficult to manage. We show that modern and advanced sampling techniques can be used to improve the planning of the forest inventories, even if there are many requirements. Our design includes balanced sampling, highly stratified balanced sampling and sample spreading through a two stage sample. The impact of these techniques on the satisfaction of the requirements and on the precision of survey estimates is investigated using field data from a Quebec inventory.
Variance estimation of changes in repeated surveys and its application to the Swiss survey of value added
We propose a method for estimating the variance of estimators of changes over time, a method that takes account of all the components of these estimators: the sampling design, treatment of non-response, treatment of large companies, correlation of non- response from one wave to another, the effect of using a panel, robustification, and calibration using a ratio estimator. This method, which serves to determine the confidence intervals of changes over time, is then applied to the Swiss survey of value added.