@article{fdi:010060453,
  title = {{M}apping local density of young {E}ucalyptus plantations by individual tree detection in high spatial resolution satellite images},
  author = {{Z}hou, {J}. and {P}roisy, {C}hristophe and {D}escombes, {X}. and {L}e {M}aire, {G}. and {N}ouvellon, {Y}. and {S}tape, {J}. {L}. and {V}iennois, {G}. and {Z}erubia, {J}. and {C}outeron, {P}ierre},
  editor = {},
  language = {{ENG}},
  abstract = {{L}ocal tree density may vary in young {E}ucalyptus plantations under the effects of environmental conditions or inadequate management, and these variations need to be mapped over large areas as they have a significant impact on the final biomass harvested. {H}igh spatial resolution optical satellite images have the potential to provide crucial information on tree density at an affordable cost for forest management. {H}ere, we test the capacity of this promising technique to map the local density of young and small {E}ucalyptus trees in a large plantation in {B}razil. {W}e use three {W}orldview panchromatic images acquired at a 50 cm resolution on different dates corresponding to trees aged 6, 9 and 13 months and define an overall accuracy index to evaluate the quality of the detection results. {T}he best agreement between the local densities obtained by visual detection and by marked point process modeling was found at 9 months, with only small omission and commission errors and a stable 4% underestimation of the number of trees across the density gradient. {W}e validated the capability of the {MPP} approach to detect trees aged 9 months by making a comparison with local densities recorded on 112 plots of similar to 590 m(2) and ranging between 1360 and 1700 trees per hectare. {W}e obtained a good correlation (r(2) = 0.88) with a root mean square error of 31 trees/ha. {W}e generalized detection by computing a consistent map over the whole plantation. {O}ur results showed that local tree density was not uniformly distributed even in a well-controlled intensively-managed {E}ucalyptus plantation and therefore needed to be monitored and mapped. {U}se of the marked point process approach is then discussed with respect to stand characteristics (canopy closure), acquisition dates and recommendations for algorithm parameterization.},
  keywords = {{C}rown identification ; {O}bject detection ; {S}tochastic point process ; {F}orests ; {R}emote sensing ; {B}razil ; {BRESIL}},
  booktitle = {},
  journal = {{F}orest {E}cology and {M}anagement},
  volume = {301},
  numero = {{SI}},
  pages = {129--141},
  ISSN = {0378-1127},
  year = {2013},
  DOI = {10.1016/j.foreco.2012.10.007},
  URL = {https://www.documentation.ird.fr/hor/fdi:010060453},
}