Precision Forestry and Advanced Technology in Management of Forest Health

In the futuristic realm of forest management, precision forestry emerges as a pivotal tool for achieving sustainable and efficient practices. It is a modern approach that leverages advanced technologies—such as remote sensing, geographic information systems (GIS), LiDAR, drones, and data analytics—to support site-specific decision-making. By shifting from traditional, broad-scale methods to data-driven interventions, precision forestry enables managers to tailor actions to the unique conditions of specific forest sites. This transition improves operational efficiency while supporting long-term ecosystem sustainability. As environmental challenges intensify, precision forestry represents a crucial evolution in the way we understand and manage forest landscapes.

Conducting forest operations that align with site-specific conditions is increasingly essential in the face of climate change and the growing threats from abiotic and biotic stressors. Traditional forest management often lacks the responsiveness needed to address these localized and evolving challenges. Precision forestry offers an adaptive, targeted approach—one that facilitates more accurate planning and real-time decision-making. Recent advances, including high-resolution spatial data, predictive modeling, and drone-enabled monitoring, have further expanded the potential of precision forestry to mitigate risks, improve resilience, and enhance forest health. This Research Topic aims to explore how these innovations can be applied to meet the current and future demands of sustainable forest management.

This Research Topic welcomes Review, Opinion, and Original Research articles that demonstrate or provide new insights into how advanced technologies can be used to monitor the occurrence or impact of abiotic and biotic disorders and/or how such technology can be harnessed to make informed forest management decisions.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Mini Review
• Opinion
• Original Research
• Perspective
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review

Keywords: biotic stressors geographic information systems LiDAR monitoring proximal sensing remote sensing silviculture unmanned aerial vehicles

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.