Longitudinal electrical resistivity profiles for non-destructive tree trunks inspection

ABSTRACT Background: The development and application of new technologies and solutions are extremely important to manage and monitor urban forestry to prevent accidents resulting from falls that often result in social and property damage. To evaluate the internal conditions of a tree, it is recommended to use indirect methods, both for the trunk and the root system. However, existing methods can predict trunk properties at the lower level in some situations, that can lead to a misinterpretation of the actual phytosanitary status of the evaluated specimen and cause the incomplete assessment. Thus, the present work aimed to evaluate, with acquisition and software development, the use of geophysical method of electrical resistivity (ER), with longitudinal profiles along the trunk, every 45º, for internal and non-destructive analysis of two specimens of Eucalyptus sp. and one of Pachira aquatica trees. In these trees, data were acquired and compared each other’s by ER, mechanical impulse tomography and resistograph. Results: This approach allows for the investigation the entire length of the trunk, in a reduced time. From the results, it was possible to establish qualitative (from images) and some quantitative (physical property values) relationships between the ER, impulse tomography and resistography, by the internal image generated and the physical properties obtained. Conclusion: Both in the interpretation of the generated images and the values obtained, they exhibited different characteristics of the studied wood, demonstrating the potential of the developed methodology for rapid and precise application in urban trees.

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Publication Details

Journal
CERNE
Published
2025-01-01
DOI
https://doi.org/10.1590/01047760202531013426
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.80
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article

Longitudinal electrical resistivity profiles for non-destructive tree trunks inspection

João Vicente de Figueiredo Latorraca, Vinícius Rafael Neris dos Santos, Bruno Araújo Furtado de Mendonça, Marcelo Farias Caetano
1 citations
CERNE
Remote Sensing and LiDAR Applications
0.80
article

Longitudinal electrical resistivity profiles for non-destructive tree trunks inspection

João Vicente de Figueiredo Latorraca, Vinícius Rafael Neris dos Santos, Bruno Araújo Furtado de Mendonça, Marcelo Farias Caetano
article en
1 citations

Abstract

ABSTRACT Background: The development and application of new technologies and solutions are extremely important to manage and monitor urban forestry to prevent accidents resulting from falls that often result in social and property damage. To evaluate the internal conditions of a tree, it is recommended to use indirect methods, both for the trunk and the root system. However, existing methods can predict trunk properties at the lower level in some situations, that can lead to a misinterpretation of the actual phytosanitary status of the evaluated specimen and cause the incomplete assessment. Thus, the present work aimed to evaluate, with acquisition and software development, the use of geophysical method of electrical resistivity (ER), with longitudinal profiles along the trunk, every 45º, for internal and non-destructive analysis of two specimens of Eucalyptus sp. and one of Pachira aquatica trees. In these trees, data were acquired and compared each other’s by ER, mechanical impulse tomography and resistograph. Results: This approach allows for the investigation the entire length of the trunk, in a reduced time. From the results, it was possible to establish qualitative (from images) and some quantitative (physical property values) relationships between the ER, impulse tomography and resistography, by the internal image generated and the physical properties obtained. Conclusion: Both in the interpretation of the generated images and the values obtained, they exhibited different characteristics of the studied wood, demonstrating the potential of the developed methodology for rapid and precise application in urban trees.

CERNEVol. 31
Universidade Federal Rural do Rio de Janeiro (BR), Universidade de São Paulo (BR)
Openalex Percentile: Top 31%
Remote Sensing and LiDAR Applications
0.80
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