@article{fdi:010063611,
  title = {{A}boveground biomass mapping of {A}frican forest mosaics using canopy texture analysis : toward a regional approach},
  author = {{B}astin, {J}. {F}. and {B}arbier, {N}icolas and {C}outeron, {P}ierre and {A}dams, {B}. and {S}hapiro, {A}. and {B}ogaert, {J}. and {D}e {C}anni{\`e}re, {C}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the {REDD}+ program), optical very high resolution ({VHR}) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass ({AGB}) at less expense than methods based on airborne remote sensing data. {A}mong the methods for processing these {VHR} images, {F}ourier textural ordination ({FOTO}) presents a good method to detect forest canopy structural heterogeneity and therefore to predict {AGB} variations. {N}otably, the method does not saturate at intermediate {AGB} values as do pixelwise processing of available space borne optical and radar signals. {H}owever, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun-scene-sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in {C}entral {A}frica. {I}n this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing {FOTO} indices of images acquired from two different sensors ({G}eoeye-1 and {Q}uick{B}ird-2) and different sun-scene-sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. {A} good agreement was found between observed and predicted {AGB} (residual standard error [{RSE}] = 15%; {R}-2 = 0.85; {P} < 0.001) across a wide range of {AGB} levels from 26 {M}g/ha to 460 {M}g/ha, and was confirmed by cross validation. {A} high-resolution biomass map (100-m pixels) was produced for a 400-km(2) area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 {M}g/ha). {T}hese results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. {I}n particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or {REDD}+ national monitoring, reporting and verification bodies.},
  keywords = {aboveground biomass ; canopy structure ; canopy texture analysis ; central {A}frica ; {C}ongo {B}asin forest ; forest classification ; forest-stand structure ; {F}ourier transform ; remote sensing ; very high resolution imagery ; {CONGO} {BASSIN} ; {REPUBLIQUE} {DEMOCRATIQUE} {DU} {CONGO}},
  booktitle = {},
  journal = {{E}cological {A}pplications},
  volume = {24},
  numero = {8},
  pages = {1984--2001},
  ISSN = {1051-0761},
  year = {2014},
  DOI = {10.1890/13-1574.1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010063611},
}