@article{fdi:010069496,
  title = {{I}nverting aboveground biomass-canopy texture relationships in a landscape of forest mosaic in the {W}estern {G}hats of {I}ndia using very high resolution cartosat imagery},
  author = {{P}argal, {S}. and {F}araroda, {R}. and {R}ajashekar, {G}. and {B}alachandran, {N}. and {R}{\'e}jou-{M}{\'e}chain, {M}axime and {B}arbier, {N}icolas and {J}ha, {C}. {S}. and {P}{\'e}lissier, {R}apha{\¨e}l and {D}adhwal, {V}. {K}. and {C}outeron, {P}ierre},
  editor = {},
  language = {{ENG}},
  abstract = {{L}arge scale assessment of aboveground biomass ({AGB}) in tropical forests is often limited by the saturation of remote sensing signals at high {AGB} values. {F}ourier {T}ransform {T}extural {O}rdination ({FOTO}) performs well in quantifying canopy texture from very high-resolution ({VHR}) imagery, from which stand structure parameters can be retrieved with no saturation effect for {AGB} values up to 650 {M}gha(-1). {T}he method is robust when tested on wet evergreen forests but is more demanding when applied across different forest types characterized by varying structures and allometries. {T}he present study focuses on a gradient of forest types ranging from dry deciduous to wet evergreen forests in the {W}estern {G}hats ({WG}) of {I}ndia, where we applied {FOTO} to {C}artosat-1a images with 2.5 m resolution. {B}ased on 21 1-ha ground control forest plots, we calibrated independent texture-{AGB} models for the dry and wet zone forests in the area, as delineated from the distribution of {NDVI} values computed from {LISS}-4 multispectral images. {T}his stratification largely improved the relationship between texture-derived and field-derived {AGB} estimates, which exhibited a {R}-2 of 0.82 for a mean r{RMSE} of ca. 17%. {B}y inverting the texture-{AGB} models, we finally mapped {AGB} predictions at 1.6-ha resolution over a heterogeneous landscape of ca. 1500 km(2) in the {WG}, with a mean relative per-pixel propagated error <20% for wet zone forests, i.e., below the recommended {IPCC} criteria for {M}onitoring, {R}eporting and {V}erification ({MRV}) methods. {T}he method proved to perform well in predicting high-resolution {AGB} values over heterogeneous tropical landscape encompassing diversified forest types, and thus presents a promising option for affordable regional monitoring systems of greenhouse gas ({G}h{G}) emissions related to forest degradation.},
  keywords = {{F}ourier {T}ransform {T}exture {O}rdination ({FOTO}) ; aboveground biomass ({AGB}) ; {W}estern {G}hats ({WG}) ; tropical forests ; {C}artosat-1a ; very high resolution ({VHR}) ; error propagation ; {INDE} ; {ZONE} {TROPICALE} ; {GHATS} {OUEST}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {9},
  numero = {3},
  pages = {228 [20 ]},
  ISSN = {2072-4292},
  year = {2017},
  DOI = {10.3390/rs9030228},
  URL = {https://www.documentation.ird.fr/hor/fdi:010069496},
}