ArticleMethodsX2025
Smartphone LiDAR for urban forest carbon assessment: A comparative study with traditional methods.
Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
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Abstract
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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