@article{fdi:010074942,
  title = {{H}ybrid atmospheric correction algorithms and evaluation on {VNIR}/{SWIR} {H}yperion satellite data for soil organic carbon prediction},
  author = {{M}inu, {S}. and {S}hetty, {A}. and {G}omez, {C}{\'e}cile},
  editor = {},
  language = {{ENG}},
  abstract = {{V}isible near-infrared and shortwave infrared data acquired by space-borne sensors contain atmospheric noise, along with target reflectance that may affect its end applications, e.g. geological, vegetation, soil surface studies, etc. {S}everal atmospheric correction algorithms have been already developed to remove unwanted atmospheric components of a spectral signature of {E}arth targets obtained from airborne/spaceborne hyperspectral image. {I}n spite of this, choosing of an appropriate atmospheric correction algorithm is an ongoing research. {I}n this study, two hybrid atmospheric correction ({HAC}) algorithms incorporating a modified empirical line ({EL}m) method were proposed. {T}he first {HAC} model (named {HAC}_1) combines (i) a radiative transfer ({RT}) model based on the concepts of {RT} equations, which uses real-time in situ atmospheric and climatic data, and (ii) an {EL}m technique. {T}he second one (named {HAC}_2) combines (i) the well-known {AT}mospheric {COR}rection ({ATCOR}) model and (ii) an {EL}m technique. {B}oth {HAC} algorithms and their component single atmospheric correction algorithms ({ATCOR}, {RT}, and {EL}m) were applied to radiance data acquired by {H}yperion satellite sensor over study sites in {A}ustralia. {T}he performances of both {HAC} algorithms were analysed in two ways. {F}irst, the {H}yperion reflectances obtained by five atmospheric correction algorithms were analysed and compared using spectral metrics. {S}econd, the performance of each atmospheric correction algorithm was analysed for prediction of soil organic carbon ({SOC}) using {H}yperion reflectances obtained from atmospheric correction algorithms. {T}he prediction model of {SOC} was built using partial least square regression model. {T}he results show that (i) both the hybrid models produce a good spectrum with lower {S}pectral {A}ngle {M}apper and {S}pectral {I}nformation {D}ivergence values and (ii) both hybrid algorithms provided better {SOC} prediction accuracy, in terms of coefficient of determination ({R}-2), residual prediction deviation ({RPD}), and ratio of performance to interquartile ({RPIQ}), with {R}-2 >= 0.75, {RPD} >= 2, and {RPIQ} >= 2.58 than single algorithms. {HAC} algorithms, developed using {EL}m technique, may be recommended for atmospheric correction of {H}yperion radiance data, when archived {H}yperion reflectance data have to be used for {SOC} prediction mapping.},
  keywords = {{AUSTRALIE}},
  booktitle = {},
  journal = {{I}nternational {J}ournal of {R}emote {S}ensing},
  volume = {39},
  numero = {22},
  pages = {8246--8270},
  ISSN = {0143-1161},
  year = {2018},
  DOI = {10.1080/01431161.2018.1483087},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074942},
}