@article{fdi:010083233,
  title = {{C}ontribution of phytoecological data to spatialize soil erosion : application of the {RUSLE} model in the {A}lgerian atlas},
  author = {{B}oussadia-{O}mari, {L}. and {O}uillon, {S}ylvain and {H}irche, {A}. and {S}alamani, {M}. and {G}uettouche, {M}. {S}. and {I}haddaden, {A}. and {N}edjraoui, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}mong the models used to assess water erosion, the {RUSLE} model is commonly used. {P}olicy makers can act on cover ({C}-factor) and conservation practice ({P}-factor) to reduce erosion, with less costly action on soil surface characteristics. {H}owever, the widespread use of vegetation indices such as {NDVI} does not allow for a proper assessment of the {C}-factor in drylands where stones, crusted surfaces and litter strongly influence soil protection. {T}wo sub-factors of {C}, canopy cover ({CC}) and soil cover ({SC}), can be assessed from phytoecological measurements that include gravel-pebbles cover, physical mulch, annual and perennial vegetation. {T}his paper introduces a method to calculate the {C}-factor from phytoecological data and, in combination with remote sensing and a geographic information system ({GIS}), to map it over large areas. {A} supervised classification, based on field phytoecological data, is applied to radiometric data from {L}andsat-8/{OLI} satellite images. {T}hen, a {C}-factor value, whose {SC} and {CC} subfactors are directly derived from the phytoecological measurements, is assigned to each land cover unit. {T}his method and {RUSLE} are implemented on a pilot region of 3828 km(2) of the {S}aharan {A}tlas, composed of rangelands and steppe formations, and intended to become an observatory. {T}he protective effect against erosion by gravel-pebbles (50%) is more than twice that of vegetation (23%). {T}he {C}-factor derived from {NDVI} (0.67) is higher and more evenly distributed than that combining these two contributions (0.37 on average). {F}inally, priorities are proposed to decision-makers by crossing the synthetic map of erosion sensitivity and a decision matrix of management priorities.},
  keywords = {{W}ater erosion ; {V}ulnerability ; {R}emote sensing ; {L}and-use mapping ; {A}ridity ; {S}oil protection ; {A}lgerian atlas ; {ALGERIE} ; {ATLAS} {SAHARIEN}},
  booktitle = {},
  journal = {{I}nternational {S}oil and {W}ater {C}onservation {R}esearch},
  volume = {9},
  numero = {4},
  pages = {502--519},
  ISSN = {2095-6339},
  year = {2021},
  DOI = {10.1016/j.iswcr.2021.05.004},
  URL = {https://www.documentation.ird.fr/hor/fdi:010083233},
}