@article{fdi:010066800,
  title = {{R}egional scale rain-forest height mapping using regression-kriging of spaceborne and airborne lidar data : application on {F}rench {G}uiana},
  author = {{F}ayad, {I}. and {B}aghdadi, {N}. and {B}ailly, {J}. {S}. and {B}arbier, {N}icolas and {G}ond, {V}. and {H}erault, {B}. and {E}l {H}ajj, {M}. and {F}abre, {F}. and {P}errin, {J}.},
  editor = {},
  language = {{ENG}},
  abstract = {{L}i{DAR} data has been successfully used to estimate forest parameters such as canopy heights and biomass. {M}ajor limitation of {L}i{DAR} systems (airborne and spaceborne) arises from their limited spatial coverage. {I}n this study, we present a technique for canopy height mapping using airborne and spaceborne {L}i{DAR} data (from the {G}eoscience {L}aser {A}ltimeter {S}ystem ({GLAS})). {F}irst, canopy heights extracted from both airborne and spaceborne {L}i{DAR} were extrapolated from available environmental data. {T}he estimated canopy height maps using {R}andom {F}orest ({RF}) regression from airborne or {GLAS} calibration datasets showed similar precisions (~6 m). {T}o improve the precision of canopy height estimates, regression-kriging was used. {R}esults indicated an improvement in terms of root mean square error ({RMSE}, from 6.5 to 4.2 m) using the {GLAS} dataset, and from 5.8 to 1.8 m using the airborne {L}i{DAR} dataset. {F}inally, in order to investigate the impact of the spatial sampling of future {L}i{DAR} missions on canopy height estimates precision, six subsets were derived from the initial airborne {L}i{DAR} dataset. {R}esults indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. {T}his precision decreased to 4.8 m for flight line spacing of 50 km.},
  keywords = {canopy height mapping ; forests ; {ICES}at {GLAS} ; {F}rench {G}uiana ; airborne ; {L}i{DAR} ; {GUYANE} {FRANCAISE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {8},
  numero = {3},
  pages = {art. 240 [18 p.]},
  ISSN = {2072-4292},
  year = {2016},
  DOI = {10.3390/rs8030240},
  URL = {https://www.documentation.ird.fr/hor/fdi:010066800},
}