@article{fdi:010044271,
  title = {{T}he association between the geographic distribution of {T}riatoma pseudomaculata and {T}riatoma wygodzinskyi ({H}emiptera: {R}eduviidae) with environmental variables recorded by remote sensors},
  author = {de la {F}uente, {A}. {L}. {C}. and {P}orcasi, {X}. and {N}oireau, {F}ran{\c{c}}ois and {D}iotaiuti, {L}. and {G}orla, {D}. {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n this {S}tudy, predictive models, of geographic distribution patterns of {T}riatoma pseudomaculata ({T}ps) and {T}. wygodzinskyi ({T}wy) were carried out. {T}hey were based oil biophysical variables estimated from information provided by the satellite remote sensors {AVHRR} ({A}dvanced {V}ery {H}igh {R}esolution {R}adiometer) and {MODIS} ({MOD}erate-resolution {I}maging {S}pectroradiometer). {O}ur goal was to analyze the potential geographic distribution of {T}ps and {T}wy and to assess the performance of three predictive models (one for each species and one for both species together) based oil temperature, vapour pressure deficit. vegetation and altitude. {T}he geographic distribution analysis shows that all models performed well (>85.7% of overall correct classification of presence and absence point data). {T}he {MODIS}-based models showed lower correct classifications than the {AVHRR}-based models. {T}he results strongly suggest that environmental information provided by remote sensors call be successfully used in studies oil the geographic distribution of poorly understood {C}hagas disease vector species.},
  keywords = {{T}riatoma pseudomaculata ; {T}riatoma wygodzinskyi ; {G}eographic ; distribution ; {E}nvironmental variables ; {R}emote sensing ; {GIS} ; {C}hagas ; disease},
  booktitle = {},
  journal = {{I}nfection {G}enetics and {E}volution},
  volume = {9},
  numero = {1},
  pages = {54--61},
  ISSN = {1567-1348},
  year = {2009},
  DOI = {10.1016/j.meegid.2008.09.008},
  URL = {https://www.documentation.ird.fr/hor/fdi:010044271},
}