Terrestrial Laser Scanning of Forest Structure

Dear Colleagues,

Terrestrial laser scanning (TLS) has the potential to revolutionise forest surveying. By allowing forests to be described in three dimensions, and at high resolution, it opens up the possibility for increasing both the accuracy of existing measurements and developing novel insights. While the foundations of this work have been laid through proof-of-concept studies, we are now in a position to make transformative advances.

Nevertheless, there remain a number of challenges. These include practical issues such as evaluating new and upgraded platforms for data collection, with many new devices in development; designing and assessing survey protocols; comparing TLS with traditional approaches; and integrating TLS data with complementary methods. Once scans have been collected, a new set of problems emerge, particularly in how to convert point cloud data into robust and replicable metrics of forest structure. Finally, while proof-of-principle work is still necessary, there have to date been relatively few direct applications of TLS to applied problems.

In this issue, we welcome all studies which deploy TLS approaches in forest ecosystems, whether natural or designed. We intend to cover all aspects from field methods, data processing, statistical analyses, and applications. The issue will therefore be a comprehensive account of the state of the field, along with providing inspiration and direction to this rapidly advancing area of research.

Specific topics include, but are not limited to:

• Demonstration of methodologies for field data collection
• Evaluation of novel TLS technologies (static or mobile)
• Comparison between TLS and other survey approaches
• Integration of airborne and terrestrial laser scanning
• Software approaches to data visualisation
• Extraction of forest physical parameters from point clouds
• Statistical approaches to inference from point clouds
• Applications of TLS data in forestry, forest ecology or conservation
• Calibration and validation of forest growth models using TLS data

Dr. Markus Eichhorn
Dr. Ting Yun
Guest Editors

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