@article{fdi:010084222,
  title = {{E}valuation of automated pipelines for tree and plot metric estimation from {TLS} data in tropical forest areas},
  author = {{M}artin-{D}ucup, {O}. and {M}ofack, {G}. {H}. and {W}ang, {D}. and {R}aumonen, {P}. and {P}loton, {P}ierre and {S}onke, {B}. and {B}arbier, {N}icolas and {C}outeron, {P}ierre and {P}{\'e}lissier, {R}apha{\¨e}l},
  editor = {},
  language = {{ENG}},
  abstract = {{B}ackground and {A}ims {T}errestrial {L}i{DAR} scanning ({TLS}) data are of great interest in forest ecology and management because they provide detailed 3-{D} information on tree structure. {A}utomated pipelines are increasingly used to process {TLS} data and extract various tree- and plot-level metrics. {W}ith these developments comes the risk of unknown reliability due to an absence of systematic output control. {I}n the present study, we evaluated the estimation errors of various metrics, such as wood volume, at tree and plot levels for four automated pipelines. {M}ethods {W}e used {TLS} data collected from a 1-ha plot of tropical forest, from which 391 trees >10 cm in diameter were fully processed using human assistance to obtain control data for tree- and plot-level metrics. {K}ey {R}esults {O}ur results showed that fully automated pipelines led to median relative errors in the quantitative structural model ({QSM}) volume ranging from 39 to 115 % at the tree level and 10 to 134 % at the 1-ha plot level. {F}or tree-level metrics, the median error for the crown-projected area ranged from 46 to 59 % and that for the crown-hull volume varied from 72 to 88 %. {T}his result suggests that the tree isolation step is the weak link in automated pipeline methods. {W}e further analysed how human assistance with automated pipelines can help reduce the error in the final {QSM} volume. {A}t the tree scale, we found that isolating trees using human assistance reduced the error in wood volume by a factor of 10. {A}t the 1-ha plot scale, locating trees with human assistance reduced the error by a factor of 3. {C}onclusions {O}ur results suggest that in complex tropical forests, fully automated pipelines may provide relatively unreliable metrics at the tree and plot levels, but limited human assistance inputs can significantly reduce errors.},
  keywords = {{AGB} estimation ; wood volume ; tree crown metrics ; quantitative structural model ({QSM}) ; {CAMEROUN} ; {ZONE} {TROPICALE}},
  booktitle = {},
  journal = {{A}nnals of {B}otany},
  volume = {128},
  numero = {6},
  pages = {753--765},
  ISSN = {0305-7364},
  year = {2021},
  DOI = {10.1093/aob/mcab051},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084222},
}