Individual tree detection and stand basal area estimation based on 16 linear array TLS data

Ma Jingyi; Huang Huaguo; Huang Kan; Xing Lu

doi:10.13332/j.1000-1522.20180016

Journal of Beijing Forestry University > 2018 > 40(8): 23-32. > DOI: 10.13332/j.1000-1522.20180016

Ma Jingyi, Huang Huaguo, Huang Kan, Xing Lu. Individual tree detection and stand basal area estimation based on 16 linear array TLS data[J]. Journal of Beijing Forestry University, 2018, 40(8): 23-32. DOI: 10.13332/j.1000-1522.20180016

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Individual tree detection and stand basal area estimation based on 16 linear array TLS data

Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University, Beijing 100083, China

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Received Date: January 09, 2018
Revised Date: July 09, 2018
Published Date: July 31, 2018

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Abstract

Abstract

ObjectiveTerrestrial laser scanning (TLS) can be used for fast and non-destructive 3D measurement of forest canopy with less manpower, material resources and time consumption than traditional methods, and it has been widely used in forestry inventory. Most current studies use 360 degrees of scanning to conduct parameter extraction, which requires relatively long time to scan forest trees and process the big data. Fewer study has been found on the faster multi-linear array scanning; and corresponding algorithms on processing the sparse point cloud data have not yet developed. As a first trial, the application capability of multi-linear array TLS on forest parameter extraction needs to be verified.
MethodA new stem detection algorithm was proposed based on the 16 linear array TLS data from a single-station scanning. The key to the algorithm is using the distance difference to the scanning station to differ tree stems from other objects around them. The random sample consensus (RANSAC) algorithm for circle was used to fit the stem point cloud at breast height and extract DBH. After detection of all stems, the angle gauge method was introduced to estimate the basal area of the forest. A case study was performed in two places: the Dongsheng Country Park and the Olympic Forest Park in Beijing.
ResultThe detection rate of individual trees was above 80% if averaging multiple single-scanning TLS data; the detection rate in the sparse plot was about 95%; the detection rate decreased with the increasing distance from the scanning station, where 10 m was the maximum to achieve a relatively high detection rate. The determination coefficient of estimated DBH of individual trees calculated by the regression equation ranged in 0.72-0.82. The accuracy of stand average DBH was higher than 90%, which was good at the plot level. The forest plot basal area was estimated based on the DBH extracted from TLS using the angle gauge method. Compared with the field measurement, the relative accuracy of basal area was about 90%.
Conclusion This method can accurately acquire single tree DBH and stand average DBH as well as basal area based on the 16 linear array TLS data with high efficiency, which provides a new choice for forestry survey.
- 16 linear array terrestrial laser scanning,
- individual tree detection,
- DBH,
- angle gauge,
- basal area

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References (31)

References

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Individual tree detection and stand basal area estimation based on 16 linear array TLS data

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