@article{fdi:010090786,
  title = {{L}i{DAR} data fusion to improve forest attribute estimates : a review},
  author = {{B}alestra, {M}. and {M}arselis, {S}. and {S}ankey, {T}. {T}. and {C}abo, {C}. and {L}iang, {X}. {L}. and {M}okros, {M}. and {P}eng, {X}. and {S}ingh, {A}. and {S}terenczak, {K}. and {V}ega, {C}. and {V}incent, {G}r{\'e}goire and {H}ollaus, {M}.},
  editor = {},
  language = {{ENG}},
  abstract = {{P}urpose of the {R}eview {M}any {L}i{DAR} remote sensing studies over the past decade promised data fusion as a potential avenue to increase accuracy, spatial-temporal resolution, and information extraction in the final data products. {H}ere, we performed a structured literature review to analyze relevant studies on these topics published in the last decade and the main motivations and applications for fusion, and the methods used. {W}e discuss the findings with a panel of experts and report important lessons, main challenges, and future directions.{R}ecent {F}indings {L}i{DAR} fusion with other datasets, including multispectral, hyperspectral, and radar, is found to be useful for a variety of applications in the literature, both at individual tree level and at area level, for tree/crown segmentation, aboveground biomass assessments, canopy height, tree species identification, structural parameters, and fuel load assessments etc. {I}n most cases, gains are achieved in improving the accuracy (e.g. better tree species classifications), and spatial-temporal resolution (e.g. for canopy height). {H}owever, questions remain regarding whether the marginal improvements reported in a range of studies are worth the extra investment, specifically from an operational point of view. {W}e also provide a clear definition of "data fusion" to inform the scientific community on data fusion, combination, and integration.{S}ummary {T}his review provides a positive outlook for {L}i{DAR} fusion applications in the decade to come, while raising questions about the trade-off between benefits versus the time and effort needed for collecting and combining multiple datasets.},
  keywords = {{L}aser {S}canner ; {T}rees ; {F}orest structure ; {M}ultispectral ; {H}yperspectral and ; {R}adar},
  booktitle = {},
  journal = {{C}urrent {F}orestry {R}eports},
  volume = {[{E}arly access]},
  numero = {},
  pages = {[17 p.]},
  ISSN = {2198-6436},
  year = {2024},
  DOI = {10.1007/s40725-024-00223-7},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090786},
}