@article{fdi:010074086,
  title = {{M}onitoring vegetation dynamics in southern {T}unisia using {SPOT}-5 ({T}ake5) data : a case study of the {T}ozeur oases},
  author = {{B}en {K}halfallah, {C}. and {D}ela{\^i}tre, {E}ric and {O}uerchefani, {D}. and {D}emagistri, {L}aurent and {A}llouche, {F}. {K}. and {D}arragi, {F}. and {S}eyler, {F}r{\'e}d{\'e}rique},
  editor = {},
  language = {{ENG}},
  abstract = {{S}patial data on vegetation dynamics are sparse for the {D}jerid oases of {T}unisia, but such data are urgently needed by policy makers for natural resource management purposes. {T}hese data can be collected by remote sensing and analyzed using {G}eographic {I}nformation {S}ystem software. {W}e analyzed the changing dynamics of the {T}ozeur oases in southwestern {T}unisia using normalized difference vegetation index ({NDVI}) index data that were generated from {SPOT}-5 ({T}ake5) satellite imagery taken from {A}pril to {S}eptember, 2015. {W}e used agglomerative hierarchical clustering ({AHC}) to produce a dendrogram that segmented the area into similar {NDVI} classes, then analyzed these clusters with reference to ground-truth data collected by field surveys. {T}he unsupervised classification map produced by {AHC} represents a spatial model of the {NDVI} distribution in the oases. {T}he results revealed seven different clusters with very high spatial heterogeneity that were linked to biophysical parameters in the field.},
  keywords = {oases ; {SPOT}-5 ({T}ake5) ; normalized difference vegetation index ; agglomerative hierarchical clustering ; {TUNISIE} ; {ZONE} {SEMIARIDE} ; {TOZEUR}},
  booktitle = {},
  journal = {{J}ournal of {A}pplied {R}emote {S}ensing},
  volume = {12},
  numero = {4},
  pages = {art. 046002 [14 p.]},
  ISSN = {1931-3195},
  year = {2018},
  DOI = {10.1117/1.jrs.12.046002},
  URL = {https://www.documentation.ird.fr/hor/fdi:010074086},
}