Semiautomatic Diameter-at-Breast-Height Extraction from Structure-from-Motion-Based Point Clouds Using a Low-Cost Fisheye Lens

The diameter at breast height (DBH) is a fundamental index used to characterize trees and establish forest inventories. The conventional method of measuring the DBH involves using steel tape meters, rope, and calipers. Alternatively, this study has shown that it can be calculated automatically using image-based algorithms, thus reducing time and effort while remaining cost-effective. The method consists of three main steps: image acquisition using a fisheye lens, 3D point cloud generation using structure-from-motion (SfM)-based image processing, and improved DBH estimation. The results indicate that this proposed methodology is comparable to traditional urban forest DBH measurements, with a root-mean-square error ranging from 0.7 to 2.4 cm. The proposed approach has been evaluated using real-world data, and it has been determined that the F-score assessment metric achieves a maximum of 0.91 in a university garden comprising 74 trees. The successful automated DBH measurements through SfM combined with fisheye lenses demonstrate the potential to improve urban tree inventories.

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Publication Details

Journal
Forests
Published
2025-02-28
DOI
https://doi.org/10.3390/f16030439
Citations
3
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
2.40
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article

Semiautomatic Diameter-at-Breast-Height Extraction from Structure-from-Motion-Based Point Clouds Using a Low-Cost Fisheye Lens

Mustafa Zeybek
3 citations
Forests
Remote Sensing and LiDAR Applications
2.40
article

Semiautomatic Diameter-at-Breast-Height Extraction from Structure-from-Motion-Based Point Clouds Using a Low-Cost Fisheye Lens

Mustafa Zeybek
article en
3 citations

Abstract

The diameter at breast height (DBH) is a fundamental index used to characterize trees and establish forest inventories. The conventional method of measuring the DBH involves using steel tape meters, rope, and calipers. Alternatively, this study has shown that it can be calculated automatically using image-based algorithms, thus reducing time and effort while remaining cost-effective. The method consists of three main steps: image acquisition using a fisheye lens, 3D point cloud generation using structure-from-motion (SfM)-based image processing, and improved DBH estimation. The results indicate that this proposed methodology is comparable to traditional urban forest DBH measurements, with a root-mean-square error ranging from 0.7 to 2.4 cm. The proposed approach has been evaluated using real-world data, and it has been determined that the F-score assessment metric achieves a maximum of 0.91 in a university garden comprising 74 trees. The successful automated DBH measurements through SfM combined with fisheye lenses demonstrate the potential to improve urban tree inventories.

ForestsVol. 16(3)
Selçuk University (TR)
Openalex Percentile: Top 14%
Remote Sensing and LiDAR Applications
2.40
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