Design-based regression estimation of net change for forest inventories

A simple design-based approach to estimating net change of a forest attribute such as timber volume is to observe the change directly on the plot level and then make that the response variable of interest using established estimation techniques such as multiphase regression estimators. This direct approach is only possible for inventories with permanent plots and is constrained to estimating net change over time periods matching the duration of the remeasurement cycle. Indirect estimation involves applying one of the aforementioned techniques to estimate the state at two time points and taking their difference. Indirect methods, although less common, are not necessarily constrained to permanent plots and can estimate net change over any desired time span for annual designs. This article compares design-based direct and indirect regression estimators under the Monte Carlo approach and illustrates their performances with data from the Swiss National Forest Inventory. The major finding is that direct estimation should be preferred whenever change is observable directly on the plot level but that multiphase indirect estimation can still improve precision when direct estimation is not possible such as for inventories employing only temporary plots.