Close-Range LiDAR for Forest Structure and Dynamics Monitoring

Dear Colleagues,

LiDAR technology is transforming forestry by providing precise, high-resolution, three-dimensional data about forest structures and dynamics. This capability has made small-scale forestry applications essential for gathering the detailed information necessary for effective forest management planning (FMP). Close-range LiDAR sensing has become an invaluable tool for in-depth forest research and management, demonstrating its versatility across various environments and biomes. Its applications in forest inventory, biomass estimation, health status monitoring, and habitat modeling are crucial for sustainable forest management, conservation, and climate change studies. Therefore, the integration of multi-source data and multi-scale studies focused on forest ecosystem services, such as monitoring and mapping, is highly encouraged.

This Special Issue aims to explore diverse applications of LiDAR remote sensing in studying forest structure and dynamics, utilizing various platforms and sensors within forest sciences. Topics can range from estimating forest parameters at the tree or plot level to broader, more comprehensive objectives and scales. For instance, continuous forest-cover studies over large areas using LiDAR can offer invaluable insights into forest growth and dynamics, including soil fertility and other soil characteristics. This approach, involving regular monitoring and detailed analysis over time, enables a deeper understanding of forest development and responses to various factors.

• Contributions to this Special Issue may address, but are not limited to, the following topics:
• Forest change;
• Forest ecology;
• The estimation of tree, plot, and stand variables for forest inventory purposes;
• Forest monitoring and mapping;
• Canopy height measurements for carbon storage and biomass;
• Species recognition;
• Health status assessment;
• Forest planning and management;
• Forest soil.

Dr. Panagiotidis Dimitrios
Guest Editor

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