@article{fdi:010087318,
  title = {{A} new method for incorporating hillslope effects to improve canopy-height estimates from large-footprint {LIDAR} waveforms},
  author = {{A}llouis, {T}. and {D}urrieu, {S}. and {C}outeron, {P}ierre},
  editor = {},
  language = {{ENG}},
  abstract = {{F}orest structure variables, such as the canopy height, are of central interest for the quantification of ecosystem functions and the assessment of biomass levels. {T}he objective of this letter is to propose a new method for ridding canopy-height estimates from the influence of the hillslope within large-footprint (light detection and ranging) {LIDAR} waveforms. {T}he method is based on modeling (using two generalized {G}aussian functions) and the fitting of canopy and ground components to large-footprint (30 m) waveforms. {T}he canopy heights were estimated for 27 waveforms: {A} root-mean-square error of 3.3 m was obtained using a high-resolution digital terrain model ({DTM}) to estimate the ground component (4.3 m using the 80-m-resolution {S}huttle {R}adar {T}opography {M}ission {DTM}) and 3.5 m when self-estimating the ground component (hillslope) based on the large-footprint waveform. {T}his approach opens new possibilities for waveform decomposition for natural resources and topography assessments based on large-footprint {LIDAR} waveforms in forest environments.},
  keywords = {{D}igital terrain model ({DTM}) ; forest structure ; {G}aussian ; high resolution ; nonlinear least squares ({NLS}) fitting ; signal processing ; tree height},
  booktitle = {},
  journal = {{IEEE} {G}eoscience and {R}emote {S}ensing {L}etters},
  volume = {9},
  numero = {4},
  pages = {730--734},
  ISSN = {1545-598{X}},
  year = {2012},
  DOI = {10.1109/lgrs.2011.2179635},
  URL = {https://www.documentation.ird.fr/hor/fdi:010087318},
}