Quantification of occlusions influencing the tree stem curve retrieving from single-scan terrestrial laser scanning data

Peng Wan, Tiejun Wang, Wuming Zhang*, Xinlian Liang, Andrew K. Skidmore, Guangjian Yan

*Corresponding author for this work

    Research output: Contribution to journalArticle

    4 Citations (Scopus)
    6 Downloads (Pure)

    Abstract

    Background: The stem curve of standing trees is an essential parameter for accurate estimation of stem volume. This study aims to directly quantify the occlusions within the single-scan terrestrial laser scanning (TLS) data, evaluate its correlation with the accuracy of the retrieved stem curves, and subsequently, to assess the capacity of single-scan TLS to estimate stem curves.

    Methods: We proposed an index, occlusion rate, to quantify the occlusion level in TLS data. We then analyzed three influencing factors for the occlusion rate: the percentage of basal area near the scanning center, the scanning distance and the source of occlusions. Finally, we evaluated the effects of occlusions on stem curve estimates from single-scan TLS data.

    Results: The results showed that the correlations between the occlusion rate and the stem curve estimation accuracies were strong (r = 0.60–0.83), so was the correlations between the occlusion rate and its influencing factors (r = 0.84–0.99). It also showed that the occlusions from tree stems were the main factor of the low detection rate of stems, while the non-stem components mainly influenced the completeness of the retrieved stem curves.

    Conclusions: Our study demonstrates that the occlusions significantly affect the accuracy of stem curve retrieval from the single-scan TLS data in a typical-size (32 m × 32 m) forest plot. However, the single-scan mode has the capacity to accurately estimate the stem curve in a small forest plot (< 10 m × 10 m) or a plot with a lower occlusion rate, such as less than 35% in our tested datasets. The findings from this study are useful for guiding the practice of retrieving forest parameters using single-scan TLS data.

    Original languageEnglish
    Article number43
    Pages (from-to)1-13
    Number of pages13
    JournalForest Ecosystems
    Volume6
    Early online date14 Oct 2019
    DOIs
    Publication statusPublished - 2019

    Bibliographical note

    Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

    Keywords

    • Stem curve
    • Stem volume
    • Terrestrial laser scanning
    • Scan mode

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