A Comparative Evaluation of Threshold Segmentation and LiDAR for Sawmill Residue Volume Estimation

The sawn timber production process generates up to 63% of residues during primary processing in sawmills. For this industry, the devaluation and disposal of these residues remain significant challenges; proper management requires a more accurate quantification of the volume. This study evaluates and compares two indirect methods for estimating the volume of stacked residues: one based on image processing and the other on terrestrial LiDAR technology. Residues of Pinus spp. from a sawmill were used, with their actual volume determined using a xylometer. The image-based method, which uses threshold-based segmentation, achieved a R2 = 0.64 and RMSE = 0.006 m3. In contrast, the LiDAR-based method, which derives measurements directly from 3D reconstruction, obtained an R2 = 0.506 and RMSE = 0.009 m3. Despite these differences, ANOVA testing (p > 0.05) indicated no statistically significant differences between the methods. The results suggest that both approaches may serve as preliminary tools for forest residue quantification and provide a solid foundation for future research aimed at developing field-applicable technological solutions.

Authors

Institutions

Publication Details

Journal
Forests
Published
2025-06-22
DOI
https://doi.org/10.3390/f16071045
Primary Topic
Mineral Processing and Grinding
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comparative Evaluation of Threshold Segmentation and LiDAR for Sawmill Residue Volume Estimation

Pablito Marcelo López‐Serrano, Artemio Carrillo-Parra, Juan García-Quezada, Pedro Antonio Domínguez-Calleros et al.
Forests
Mineral Processing and Grinding
article

A Comparative Evaluation of Threshold Segmentation and LiDAR for Sawmill Residue Volume Estimation

Pablito Marcelo López‐Serrano, Artemio Carrillo-Parra, Juan García-Quezada, Pedro Antonio Domínguez-Calleros, Jorge Luis Compeán-Aguirre, Leonardo Vásquez-Ibarra, Carlos Borrego-Núñez
article en

Abstract

The sawn timber production process generates up to 63% of residues during primary processing in sawmills. For this industry, the devaluation and disposal of these residues remain significant challenges; proper management requires a more accurate quantification of the volume. This study evaluates and compares two indirect methods for estimating the volume of stacked residues: one based on image processing and the other on terrestrial LiDAR technology. Residues of Pinus spp. from a sawmill were used, with their actual volume determined using a xylometer. The image-based method, which uses threshold-based segmentation, achieved a R2 = 0.64 and RMSE = 0.006 m3. In contrast, the LiDAR-based method, which derives measurements directly from 3D reconstruction, obtained an R2 = 0.506 and RMSE = 0.009 m3. Despite these differences, ANOVA testing (p > 0.05) indicated no statistically significant differences between the methods. The results suggest that both approaches may serve as preliminary tools for forest residue quantification and provide a solid foundation for future research aimed at developing field-applicable technological solutions.

ForestsVol. 16(7)
Universidad Juárez del Estado de Durango (MX), Catholic University of the Maule (CL)
Openalex Percentile: Top 86%
Mineral Processing and Grinding
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Comparative Evaluation of Threshold Segmentation and LiDAR for Sawmill Residue Volume Estimation — Pablito Marcelo López‐Serrano, Artemio Carrillo-Parra, et al. · Forests (2025) | TGRS Research Map | TGRS