UAV-Based Multispectral Imagery for Area-Wide Sustainable Tree Risk Management

Kinga Mazurek, Łukasz Zając, Marzena Suchocka (), Tomasz Jelonek, Adam Juźwiak and Marcin Kubus
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Kinga Mazurek: Institute of Environmental Engineering, Warsaw University of Life Sciences—SGGW, Nowoursynowska St. 159, 02-776 Warsaw, Poland
Łukasz Zając: Faculty of Forestry and Wood Technology, Poznan University of Life Sciences, St. Wojska Polskiego 28, 60-637 Poznan, Poland
Marzena Suchocka: Institute of Environmental Engineering, Warsaw University of Life Sciences—SGGW, Nowoursynowska St. 159, 02-776 Warsaw, Poland
Tomasz Jelonek: Faculty of Forestry and Wood Technology, Poznan University of Life Sciences, St. Wojska Polskiego 28, 60-637 Poznan, Poland
Adam Juźwiak: Independent Researcher, 82-500 Kwidzyn, Poland
Marcin Kubus: Department of Landscape Architecture, West Pomeranian University of Technology, Papieża Pawła VI St. 3a, 71-459 Szczecin, Poland

Sustainability, 2025, vol. 17, issue 19, 1-22

Abstract: The responsibility for risk assessment and user safety in forested and recreational areas lies with the property owner. This study shows that unmanned aerial vehicles (UAVs), combined with remote sensing and GIS analysis, effectively support the identification of high-risk trees, particularly those with reduced structural stability. UAV-based surveys successfully detect 78% of dead or declining trees identified during ground inspections, while significantly reducing labor and enabling large-area assessments within a short timeframe. The study covered an area of 6.69 ha with 51 reference trees assessed on the ground. Although the multispectral camera also recorded the red-edge band, it was not included in the present analysis. Compared to traditional ground-based surveys, the UAV-based approach reduced fieldwork time by approx. 20–30% and labor costs by approx. 15–20%. Orthomosaics generated from images captured by commercial multispectral drones (e.g., DJI Mavic 3 Multispectral) provide essential information on tree condition, especially mortality indicators. UAV data collection is fast and relatively low-cost but requires equipment capable of capturing high-resolution imagery in specific spectral bands, particularly near-infrared (NIR). The findings suggest that UAV-based monitoring can enhance the efficiency of large-scale inspections. However, ground-based verification remains necessary in high-traffic areas where safety is critical. Integrating UAV technologies with GIS supports the development of risk management strategies aligned with the principles of precision forestry, enabling sustainable, more proactive and efficient monitoring of tree-related hazards.

Keywords: sustainable forest management; remote sensing in forest; hazard and risk management in forests; urban forestry; climate change mitigation in forests; forest wildlife habitat management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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