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Continuous forest inventory using multistage unequal probability sampling with partial replacement Huang, Shongming

Abstract

Continuous forest inventory (CFI) with partial replacement of sampling units (SPR) has been established as an efficient inventory technique. Previous CFI with SPR theory was based on equal probability sampling which might not be as efficient as the unequal probability sampling that is now widely used in forest inventories. In this study, the general theory of multistage sampling combined with CFI using unequal probabilities in a SPR structure on two occasions is discussed. Estimators of the current means and the change in means for both one-stage and two-stage cases are given, along with the estimators for the overall variances. The estimators derived for estimating the current means take the same form as those developed by other researchers. However, the estimators proposed for predicting the change in means take simpler forms than those presented in the literature. This might result in greater simplicity when used in data processing. The application of CFI with SPR using multistage unequal probability sampling to a Chinese national forest inventory is presented for illustrative purposes. Some particular points are addressed regarding specific situations in China. Although no precise theoretical demonstration of the gains from using this method is given, the combination of highly efficient sampling with unequal probabilities and the very practical multistage sampling in CFI with SPR inventories can certainly provide an efficient alternative to traditional Chinese inventory systems.

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