@article{fdi:010071066,
  title = {{D}eveloping a predictive environment-based model for mapping biological soil crust patterns at the local scale in the {S}ahel},
  author = {{B}eaugendre, {N}. and {M}alam {I}ssa, {O}umarou and {C}hone, {A}. and {C}erdan, {O}. and {D}esprats, {J}. {F}. and {R}ajot, {J}ean-{L}ouis and {S}annier, {C}. and {V}alentin, {C}hristian},
  editor = {},
  language = {{ENG}},
  abstract = {{S}everal studies have demonstrated the great range of possibilities offered by remote sensing in identifying, estimating and mapping biological soil crust ({BSC}) patterns, i.e. a feature recognised to play major functions in drylands. {H}owever those techniques are suitable mainly where {BSC} patterns are abundant ( > 30%) and vegetation cover low (< 10%), otherwise reflectance values matched different levels of {BSC}s mixed with vegetation and bare soil surfaces. {T}his study developed an alternative methodology in mapping {BSC} presence in areas with a wide range of {BSC} cover associated with different mosaics encompassing vegetation and bare surfaces in the {S}ahel. {D}ata were collected during intensive field surveys and remote sensing imagery of two typical {S}ahelian watersheds in western {N}iger ({B}anizoumbou and {T}amou). {S}tatistical methods were used to explore relationships between {BSC} occurrence and abundance and key environmental factors (rainfall, land use, land cover, vegetation, physical crusts). {A} predictive model of {BSC} spatial distribution was developed based on logistic regressions. {T}his model allowed predicting and mapping {BSC} occurrence in areas where {BSC} cover ranged from 0 to 65% at {T}amou (15% in average) and 1 to 48% at {B}anizoumbou (4% in average) and where vegetation cover ranged from < 1% to > 75%. {P}redicted values were obtained with an overall accuracy of 77.7% (kappa = 0.54), classifying the model as good and discriminant. {T}his work is the first step in assessing the local scale ecological functions of {BSC}. {F}urther work is needed for extrapolation at the regional scale in order to provide a useful tool for ecological surveys and for predictions of soil surface dynamics related to global changes in dryland areas.},
  keywords = {{S}outh-western {N}iger ; {B}iocrust ; {P}hysical crusts ; {L}and use ; {L}and photo interpretation ; {H}igh.resolution satellite images ; {NIGER} ; {SAHEL}},
  booktitle = {},
  journal = {{C}atena},
  volume = {158},
  numero = {},
  pages = {250--265},
  ISSN = {0341-8162},
  year = {2017},
  DOI = {10.1016/j.catena.2017.06.010},
  URL = {https://www.documentation.ird.fr/hor/fdi:010071066},
}