<abstract xmlns="http://www.w3.org/1999/xhtml">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.</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.

Estimation of change in forest height growth

Institute of Forestry and Rural Engineering

Forestry Studies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Estimation of change in forest height growth"}

Forest height increment rate is related to the forest growth conditions. Data bases of previous forest inventories contain information about forest heightage...

Estimation of change in forest height growth

Online veröffentlicht: 25. Apr. 2018

Seitenbereich: 5 - 16

Eingereicht: 15. Nov. 2017

Akzeptiert: 29. Jan. 2018

DOI: https://doi.org/10.1515/fsmu-2017-0009

Schlüsselwörter
laser scanning, change detection, permanent sample plots, historical forest data, forest growth models

© 2017 Mait Lang et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Estimation of change in forest height growth

Online veröffentlicht: 25. Apr. 2018

Seitenbereich: 5 - 16

Eingereicht: 15. Nov. 2017

Akzeptiert: 29. Jan. 2018

DOI: https://doi.org/10.1515/fsmu-2017-0009

Schlüsselwörterlaser scanning, change detection, permanent sample plots, historical forest data, forest growth models

© 2017 Mait Lang et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
laser scanning, change detection, permanent sample plots, historical forest data, forest growth models