@article{fdi:010058962,
  title = {{T}he utility of remotely-sensed vegetative and terrain covariates at different spatial resolutions in modelling soil and watertable depth (for digital soil mapping)},
  author = {{T}aylor, {J}. {A}. and {J}acob, {F}r{\'e}d{\'e}ric and {G}alleguillos, {M}. and {P}revot, {L}. and {G}uix, {N}. and {L}agacherie, {P}.},
  editor = {},
  language = {{ENG}},
  abstract = {{D}igital soil modelling and mapping is reliant on the availability and utility of easily derived and accessible covariates. {I}n this paper, the value of covariates derived from a time-series of remotely-sensed {ASTER} satellite imagery and digital elevation models were evaluated for modelling two soil attributes - soil depth and watertable depth. {M}odelling was performed at two resolutions: a fine resolution (15 m pixels) that relates to the resolution of the {ASTER} {V}isible-{NIR} bands, and a larger resolution (90 m pixels) that relates to the resolution of the thermal bands of the {ASTER} imagery. {U}pscaling to a larger pixel size and downscaling to a smaller pixel size were performed to adjust the covariates where necessary. {A} regression tree approach was used to model soil depth and watertable depth, recorded as a binary 'deep' or 'shallow' response, using the {ASTER} imagery-derived covariates and digital terrain attributes ({DTA}s). {M}odelling was performed at a single spatial resolution (15 or 90 m pixels) using the imagery-derived covariates only, the {DTA}s only, or a mixture of both. {A} multi-resolution model was also generated, by using both imagery-derived covariates and {DTA}s at both resolutions. {W}hen mixed with the {DTA}s, the imagery-derived covariates helped explain the uncertainty (variance) in the soil depth data but not in the watertable depth. {T}he {ASTER}-derived down-scaled evapotranspiration-based covariates were of particular significance in the soil depth modelling. {W}atertable depth was best explained by models that used {DTA}s at a smaller pixel size. {I}nformation on vegetative growth was neither superior nor complementary to information on terrain for modelling watertable depth. {U}sing a multi-resolution model significantly improved the modelling of soil depth but not of watertable depth. {T}he effect of covariate and modelling resolution on model performance is discussed within the context of the {G}lobal{S}oil{M}ap.net project.},
  keywords = {{ASTER} ; {E}vapotranspiration ; {NDVI} ; {D}igital terrain attributes ; {R}egression tree ; {G}lobal{S}oil{M}ap.net},
  booktitle = {},
  journal = {{G}eoderma},
  volume = {193},
  numero = {},
  pages = {83--93},
  ISSN = {0016-7061},
  year = {2013},
  DOI = {10.1016/j.geoderma.2012.09.009},
  URL = {https://www.documentation.ird.fr/hor/fdi:010058962},
}