Site index (SI) is determined from the top height development and is a proxy for forest productivity, defined as the expected top height for a given species at a certain index age. In Norway, an index age of 40 years is used. By using bi-temporal airborne laser scanning (ALS) data, SI can be determined using models estimated from SI observed on field plots (the direct approach) or from predicted top heights at two points in time (the height differential approach). Time series of ALS data may enhance SI determination compared to conventional methods used in operational forest inventory by providing more detailed information about the top height development. We used longitudinal data comprising spatially consistent field and ALS data collected from training plots in 1999, 2010, and 2022 to determine SI using the direct and height differential approaches using all combinations of years and performed an external validation. We also evaluated the use of data assimilation. Values of root mean square error obtained from external validation were in the ranges of 16.3%–21.4% and 12.8%–20.6% of the mean field-registered SI for the direct approach and the height differential approach, respectively. There were no statistically significant effects of time series length or the number of points in time on the obtained accuracies. Data assimilation did not result in any substantial improvement in the obtained accuracies. Although a time series of ALS data did not yield greater accuracies compared to using only two points in time, a larger proportion of the study area could be used in ALS-based determination of SI when a time series was available. This was because areas that were unsuitable for SI determination between two points in time could be subject to SI determination based on data from another part of the time series.

中文翻译：

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使用机载激光扫描数据的时间序列确定站点索引


立地指数 （SI） 由最高高度发展确定，是森林生产力的代表，定义为给定物种在特定指数年龄的预期最高高度。在挪威，使用 40 年的指数年龄。通过使用双颞面机载激光扫描 （ALS） 数据，可以使用根据场图上观察到的 SI 估计的模型（直接方法）或从两个时间点的预测顶部高度（高度差分方法）估计的模型来确定 SI。与运营森林清查中使用的传统方法相比，ALS 数据的时间序列可以通过提供有关顶部高度发展的更多详细信息来增强 SI 确定。我们使用纵向数据，包括从 1999 年、 2010 年和 2022 年的训练图中收集的空间一致场和 ALS 数据，使用所有年份组合的直接和身高差异方法确定 SI，并进行了外部验证。我们还评估了数据同化的使用。对于直接方法和高度差分方法，从外部验证获得的均方根误差值分别在平均场注册 SI 的 16.3%–21.4% 和 12.8%–20.6% 范围内。时间序列长度或时间点数对所获得的准确性没有统计学上的显著影响。数据同化没有导致所获得的准确性有任何实质性的提高。尽管与仅使用两个时间点相比，ALS 数据的时间序列并没有产生更高的准确性，但当时间序列可用时，更大比例的研究区域可用于基于 ALS 的 SI 确定。 这是因为不适合在两个时间点之间确定 SI 的区域可能会根据时间序列另一部分的数据进行 SI 确定。