When auxiliary information in the form of airborne laser scanning (ALS) is used to assist in estimating the population parameters of interest, the benefits of prior information from previous inventories are not self-evident. In a simulation study, we compared three different approaches: 1) using only current data, 2) using non-updated old data and current data in a composite estimator and 3) using updated old data and current data with a Kalman filter. We also tested three different estimators, namely i) Horwitz-Thompson for a case of no auxiliary information, ii) model-assisted estimation and iii) model-based estimation. We compared these methods in terms of bias, precision and accuracy, as estimators utilizing prior information are not guaranteed to be unbiased. The largest standard errors were obtained when neither prior information nor auxiliary information were used. If a growth model was not applied to update the old data, the resulting composite estimators were biased. Largest RMSEs were obtained using non-updated prior information in a composite estimator. Using the ALS data as auxiliary information produced smaller RMSE than using prior information from the old inventory. The smallest RMSEs were obtained when both the auxiliary data and updated old data were used. With growth updating the bias can be substantially reduced, although design-unbiasedness of the estimator cannot be guaranteed. Prior information from old inventory data can be useful also when combined with highly accurate auxiliary information, when both data sources are efficiently used. The benefits obtained from using the old data will increase if the past harvests can be detected without errors from changes in the auxiliary data instead of being predicted with models.

中文翻译：

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过去库存数据作为当前库存的先验信息的好处

当使用机载激光扫描（ALS）形式的辅助信息来帮助估算感兴趣的种群参数时，来自先前清单的先验信息的好处就不言而喻了。在模拟研究中，我们比较了三种不同的方法：1）仅使用当前数据，2）在复合估计器中使用未更新的旧数据和当前数据，以及3）使用带有卡尔曼滤波器的更新的旧数据和当前数据。我们还测试了三种不同的估计量，即i）在没有辅助信息的情况下的Horwitz-Thompson，ii）模型辅助的估计和iii）基于模型的估计。由于无法保证利用先验信息的估计量不会产生偏差，因此我们在偏差，精度和准确性方面比较了这些方法。当既不使用先验信息也不使用辅助信息时，将获得最大的标准误差。如果未使用增长模型来更新旧数据，则所得的综合估计量将产生偏差。在组合估算器中，使用未更新的先验信息可获得最大的RMSE。与使用旧库存中的先前信息相比，使用ALS数据作为辅助信息所产生的RMSE较小。当同时使用辅助数据和更新的旧数据时，可获得最小的RMSE。尽管无法保证估计量的设计无偏差，但随着增长的更新，偏差可以大大减少。当两个数据源都得到有效使用时，将来自旧库存数据的先验信息与高精度辅助信息结合起来也很有用。