Abstract The term shelf-life is used to characterize the elapsed time beyond which a commodity loses its usefulness. The term is most often used with reference to foods and medicines, but herein it is used to characterize the elapsed time beyond which airborne laser scanning (ALS) data are no longer useful for enhancing inferences for forest inventory population parameters. National forest inventories (NFI) have a long history of using remotely sensed auxiliary information to enhance inferences. Although the combination of model-assisted estimators and ALS auxiliary data has been demonstrated to be particularly useful for this purpose, the expense associated with the acquisition of the ALS data has been an argument against their operational use. However, the longer the shelf-life of ALS data, the less the continuing acquisition costs and the greater the utility of the data. The objective of the study was to assess the shelf-life of ALS data for enhancing inferences in the form of confidence intervals for mean aboveground, live tree, stem biomass per unit area. Confidence intervals were constructed using both model-assisted estimators and post-stratified estimators, four measurements of mostly the same forest inventory plots at 5-year intervals over a 17-year period, and a single set of ALS data acquired near the end of the 17-year period. The study area in north central Minnesota in the USA was characterized by naturally regenerated, uneven-aged, mixed species stands on both lowland and upland sites. The primary conclusions were twofold. First, the shelf-life of ALS data when used with model-assisted estimators exceeded 10 years, and second, even for 12 years elapsed time between plot measurement and ALS data acquisition, the variance of the model-assisted estimator of the mean was smaller by a factor of at least 1.75 than the variance of the stratified estimator used by the national forest inventory.

中文翻译：

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用于增强森林清单推断的机载激光扫描数据的保质期

摘要 保质期一词用于表征商品失去其用途所经过的时间。该术语最常用于食品和药品，但在此用于表征机载激光扫描 (ALS) 数据不再用于增强对森林清单种群参数的推断所经过的时间。国家森林清单 (NFI) 在使用遥感辅助信息来增强推理方面有着悠久的历史。尽管模型辅助估计器和 ALS 辅助数据的组合已被证明对此目的特别有用，但与获取 ALS 数据相关的费用一直是反对其操作使用的论据。然而，ALS 数据的保质期越长，持续获取成本越低，数据的效用就越大。该研究的目的是评估 ALS 数据的保质期，以增强单位面积平均地上、活树、茎生物量的置信区间形式的推断。置信区间是使用模型辅助估计量和分层后估计量构建的，在 17 年期间以 5 年为间隔对大部分相同的森林清单地块进行四次测量，以及在接近结束时获得的一组 ALS 数据17 年期间。美国明尼苏达州中北部的研究区的特点是自然再生、年龄不均、混合物种分布在低地和高地。主要结论是双重的。首先，ALS 数据与模型辅助估计器一起使用时的保质期超过 10 年，