Risk assessment of tree falls is essential for urban management and demands reliable methods and criteria capable of providing accurate information on assessed individuals. Among the tools currently used, resistograph stands out since it enables the detection of biomechanical problems through readings of needle penetration resistance. Recently, impulse tomography has been used as advanced technology to detect inner rottenness based on measurements of energy propagation velocity in inner tissues, generating a tomographic image that highlights higher and lower density areas related to lesions and rot processes. We compared these two risk assessment methods of trees to evaluate data reliability generated from impulse tomography, contrasting its results with data from resistograph. We obtained a model with high determination coefficient (R²) of 0.9977, showing that data provided by impulse tomography are high quality and reliable.
Fall risks; resistograph; impulse tomography
