Research Topics

Precision forestry is an approach that utilizes advanced technologies and data analytics to optimize and enhance forest management practices. By integrating various technologies such as remote sensing, LiDAR, drones, and data-driven decision-making, precision forestry aims to increase efficiency, sustainability, and productivity in forest-related activities.

Forest big data refers to the vast and complex volume of information generated from various sources within the forestry sector. This information is collected and analyzed to gain insights into forest ecosystems, understand their dynamics, and inform evidence-based decision-making in forest management, conservation, and policy development.

Understanding the forest value chain is vital for optimizing resource use, promoting sustainable practices, and identifying opportunities for innovation and efficiency improvements in the forest industry. It also helps in creating a balance between economic growth, social well-being, and environmental conservation within the forestry sector.

Regional circular forestry is an innovative approach to forest management that focuses on creating a circular economy within a specific geographic area. By embracing circular principles, it aims to create a regenerative and sustainable forest-based economy that benefits both nature and local communities in the long term.