Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods

Urban forestry plays a critical role in enhancing environmental quality and urban livability, making accurate tree growth assessment essential for effective green space management. This study examines methods for measuring tree growth and estimating carbon sequestration using primary data collected...

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Main Authors: Pornperm Sae-ngow, Morakot Worachairungreung, Phonpat Hemwan, Natthicha Toathuean, Namtip Chimpalee, Nayot Kulpanich
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:MethodsX
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Online Access:http://www.sciencedirect.com/science/article/pii/S2215016125003188
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author Pornperm Sae-ngow
Morakot Worachairungreung
Phonpat Hemwan
Natthicha Toathuean
Namtip Chimpalee
Nayot Kulpanich
author_facet Pornperm Sae-ngow
Morakot Worachairungreung
Phonpat Hemwan
Natthicha Toathuean
Namtip Chimpalee
Nayot Kulpanich
author_sort Pornperm Sae-ngow
collection DOAJ
description Urban forestry plays a critical role in enhancing environmental quality and urban livability, making accurate tree growth assessment essential for effective green space management. This study examines methods for measuring tree growth and estimating carbon sequestration using primary data collected from field surveys. The data include diameter at breast height (DBH) and tree height (H) from a sample of 50 trees, categorized into two groups: (1) perennial tree species and (2) palm species. Data collection was conducted using both traditional measurement techniques and the Arboreal Tree Height (ATH) application with Smartphone LiDAR. • A comparative analysis of the two methods revealed that DBH measurements had a statistically significant R² value of 0.987, while for tree height, the R² value was 0.897. • In terms of carbon sequestration estimation, perennial trees showed an R² value of 0.950, while palm species yielded an R² value of 0.9524.These findings confirm the reliability of ATH app and allometric equations for accurate carbon sequestration estimation. This methodology enhances data management and carbon sequestration assessments, supporting greenhouse gas reduction and sustainable urban development.
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series MethodsX
spelling doaj-art-b17dc9c58ae240e88abc4941ce760b572025-08-20T02:42:42ZengElsevierMethodsX2215-01612025-12-011510347310.1016/j.mex.2025.103473Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methodsPornperm Sae-ngow0Morakot Worachairungreung1Phonpat Hemwan2Natthicha Toathuean3Namtip Chimpalee4Nayot Kulpanich5Geography and Geo-Informatics Program, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University Bangkok, ThailandGeography and Geo-Informatics Program, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University Bangkok, ThailandDepartment of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai, ThailandGeography and Geo-Informatics Program, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University Bangkok, ThailandGeography and Geo-Informatics Program, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University Bangkok, ThailandGeography and Geo-Informatics Program, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University Bangkok, Thailand; Corresponding author.Urban forestry plays a critical role in enhancing environmental quality and urban livability, making accurate tree growth assessment essential for effective green space management. This study examines methods for measuring tree growth and estimating carbon sequestration using primary data collected from field surveys. The data include diameter at breast height (DBH) and tree height (H) from a sample of 50 trees, categorized into two groups: (1) perennial tree species and (2) palm species. Data collection was conducted using both traditional measurement techniques and the Arboreal Tree Height (ATH) application with Smartphone LiDAR. • A comparative analysis of the two methods revealed that DBH measurements had a statistically significant R² value of 0.987, while for tree height, the R² value was 0.897. • In terms of carbon sequestration estimation, perennial trees showed an R² value of 0.950, while palm species yielded an R² value of 0.9524.These findings confirm the reliability of ATH app and allometric equations for accurate carbon sequestration estimation. This methodology enhances data management and carbon sequestration assessments, supporting greenhouse gas reduction and sustainable urban development.http://www.sciencedirect.com/science/article/pii/S2215016125003188Smartphone LiDAR for Carbon Sequestrationutbl
spellingShingle Pornperm Sae-ngow
Morakot Worachairungreung
Phonpat Hemwan
Natthicha Toathuean
Namtip Chimpalee
Nayot Kulpanich
Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
MethodsX
Smartphone LiDAR for Carbon Sequestrationutbl
title Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
title_full Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
title_fullStr Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
title_full_unstemmed Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
title_short Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods
title_sort smartphone lidar for urban forest carbon assessment a comparative study with traditional methods
topic Smartphone LiDAR for Carbon Sequestrationutbl
url http://www.sciencedirect.com/science/article/pii/S2215016125003188
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