森林高度生长变化的估计

Q4 Agricultural and Biological Sciences
Mait Lang, T. Arumäe, D. Laarmann, A. Kiviste
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引用次数: 5

摘要

摘要森林高度增长率与森林生长条件有关。以往的森林清查数据库包含大量林分的森林高度关系信息,而对永久样地的重复测量为比较提供了很好的参考。森林林分的机载激光重复扫描是估算森林结构变化的另一个来源。在本研究中,对永久样地(66)和具有重复机载激光扫描数据的林分样地(61)进行了10年左右中老年林分的高度生长与代数差分模型的比较。该模型基于1984-1993年期间森林清查记录的大型数据集。与代数差分模型相比,在爱沙尼亚东南部,基于树木高度测量的永久样地(9厘米/年- 1)以及具有重复激光扫描数据的林分(4.5厘米/年- 1)的森林高度增长在统计上显著增加。两组数据之间的差异可以用平均年龄和立地类别来解释,但与旧森林清查数据相比,森林高度的增长表明试验区森林的生长条件有所改善。研究结果还提示,基于经验数据的森林生长模型需要更新,以避免有偏差的生长估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of change in forest height growth
Abstract Forest height increment rate is related to the forest growth conditions. Data bases of previous forest inventories contain information about forest heightage relationship on large number of forest stands while repeated measurements of permanent sample plots provide an excellent reference for comparison. Repeated airborne laser scanning of forest stands is an additional source for the estimation of change in forest structure. In this study, height growth of middle-aged and older forest stands for about 10 year period was compared to an algebraic difference model on permanent sample plots (66) and for a sample of forest stands with repeated airborne laser scanning data (61). The model was based on a large dataset of forest inventory records from the period of 1984–1993. Statistically significant increased forest height growth was found in permanent sample plots based on tree height measurements (9 cm yr−1) as well in stands with repeated laser scanning data (4.5 cm yr−1) in South-East Estonia compared to the algebraic difference model. The difference between the two data sets was explained by their mean age and site class, but the increased forest height growth compared to the old forest inventory data indicates improved growth conditions of forests in the test area. The results hint also that empirical data-based forest growth models need to be updated to avoid biased growth estimates.
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来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
CiteScore
0.70
自引率
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