Using LiDAR technology in forestry activities.

Area of Science:

• Forestry
• Remote Sensing
• Geospatial Analysis

Background:

• Natural resource management, especially in forestry, is data-intensive and time-consuming.
• Traditional field data collection is laborious and costly for large-scale assessments.
• Emerging technologies are needed to streamline data acquisition and analysis in forestry.

Purpose of the Study:

• To present the advancements and potential applications of LiDAR remote sensing in forestry.
• To highlight LiDAR's capability in acquiring detailed forest structure and elevation data.
• To explore the utility of LiDAR-derived data for various forestry management activities.

Main Methods:

• Utilizing high-performance LiDAR remote sensing technology for data acquisition in forested areas.
• Processing LiDAR data to derive high-quality three-dimensional forest structure information.
• Generating accurate and high-resolution Digital Elevation Models (DEMs) from LiDAR data.

Main Results:

• LiDAR enables precise characterization of forest structures in three dimensions.
• High-resolution DEMs derived from LiDAR provide accurate topographical information for forests.
• LiDAR-based data significantly enhances the efficiency and accuracy of forestry applications.

Conclusions:

• LiDAR remote sensing is a powerful tool for modern forestry applications.
• LiDAR-derived data supports comprehensive stand characterization, inventory, and management.
• Applications include fire behavior modeling and optimizing forest operations, demonstrating LiDAR's broad utility.