Exploring the Potential of Mobile Laser Scanning to Quantify Forest Structural Complexity

2022 | journal article; research paper. A publication with affiliation to the University of Göttingen.

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​Exploring the Potential of Mobile Laser Scanning to Quantify Forest Structural Complexity​
Neudam, L.; Annighöfer, P. & Seidel, D. ​ (2022) 
Frontiers in Remote Sensing3 art. 861337​.​ DOI: https://doi.org/10.3389/frsen.2022.861337 

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Authors
Neudam, Liane; Annighöfer, Peter; Seidel, Dominik 
Abstract
Today, creating or maintaining forest structural complexity is a management paradigm in many countries due to the positive relationships between structural complexity and several forest functions and services. In this study, we tested whether the box-dimension (Db), a holistic and objective measure to describe the structural complexity of trees or forests, can be used to quantify the structural complexity of 14 European beech (Fagus sylvatica L.) dominated forest plots by means of mobile laser scanning (MLS). The goal of this study was to explore the potential of this approach for quantifying the effect of leaves (summer vs winter) and management (lately unmanaged vs managed) on forest structural complexity. The findings suggest that repeated measurements on the same site and at the same time yielded consistent results if the measuring scheme is standardized. The results also showed that standardized measurement protocols allowed quantifying differences in forest structural complexity due to season. The highest stand structural complexity was found in leaf-on condition during summer, with the complexity being significantly higher than in winter condition. Also, in case of our beech-dominated plots, managed forests were more complex in structure than formerly managed but now unmanaged forests. This study illustrates the potential of MLS for monitoring the changes in forest structural complexity and allows correcting stand structural information for seasonality
Issue Date
2022
Journal
Frontiers in Remote Sensing 
Organization
Fakultät für Forstwissenschaften und Waldökologie ; Burckhardt-Institut ; Abteilung Räumliche Strukturen und Digitalisierung von Wäldern ; Abteilung Waldbau und Waldökologie der gemäßigten Zonen 
ISSN
2673-6187
eISSN
2673-6187
Language
English
Sponsor
Open-Access-Publikationsfonds 2022

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