@article{fdi:010090578,
  title = {{G}lobe-{LFMC} 2.0, an enhanced and updated dataset for live fuel moisture content research},
  author = {{Y}ebra, {M}. and {S}cortechini, {G}. and {A}deline, {K}. and {A}ktepe, {N}. and {A}lmoustafa, {T}. and {B}ar-{M}assada, {A}. and {B}eget, {M}. {E}. and {B}oer, {M}. and {B}radstock, {R}. and {B}rown, {T}. and {C}astro, {F}. {X}. and {C}hen, {R}. and {C}huvieco, {E}. and {D}anson, {M}. and {D}egirmenci, {C}. {U}. and {D}elgado-{D}avila, {R}. and {D}ennison, {P}. and {D}i {B}ella, {C}. and {D}omenech, {O}. and {F}eret, {J}. {B}. and {F}orsyth, {G}. and {G}abriel, {E}. and {G}agkas, {Z}. and {G}harbi, {F}. and {G}randa, {E}. and {G}riebel, {A}. and {H}e, {B}. {B}. and {J}olly, {M}. and {K}otzur, {I}. and {K}raaij, {T}. and {K}ristina, {A}. and {K}uetkuet, {P}. and {L}imousin, {J}. {M}. and {M}artin, {M}. {P}. and {M}onteiro, {A}. {T}. and {M}orais, {M}. and {M}oreira, {B}. and {M}ouillot, {F}lorent and {M}sweli, {S}. and {N}olan, {R}. {H}. and {P}ellizzaro, {G}. and {Q}i, {Y}. and {Q}uan, {X}. {W}. and de {D}ios, {V}. {R}. and {R}oberts, {D}. and {T}avsanoglu, {C}. and {T}aylor, {A}. {F}. {S}. and {T}aylor, {J}. and {T}uefekcioglu, {I}. and {V}entura, {A}. and {C}ardenas, {N}. {Y}.},
  editor = {},
  language = {{ENG}},
  abstract = {{G}lobe-{LFMC} 2.0, an updated version of {G}lobe-{LFMC}, is a comprehensive dataset of over 280,000 {L}ive {F}uel {M}oisture {C}ontent ({LFMC}) measurements. {T}hese measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. {I}n contrast to its prior version, {G}lobe-{LFMC} 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises {LFMC} values obtained from samples collected until the calendar year 2023. {E}ach entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. {M}oreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. {G}lobe-{LFMC} 2.0 can facilitate advanced {LFMC} research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. {T}his dataset represents a valuable resource for researchers exploring the diverse {LFMC} aspects, contributing to the broader field of environmental and ecological research.},
  keywords = {{MONDE} ; {ETATS} {UNIS} ; {FRANCE}, {ESPAGNE} ; {TURQUIE} ; {ITALIE} ; {TUNISIE} ; {ARGENTINE} ; {AUSTRALIE} ; {CHINE} ; {PORTUGAL} ; {SENEGAL} ; {AFRIQUE} {DU} {SUD} ; {ECOSSE} ; {PORTUGAL} ; {ISRAEL} ; {ANGLETERRE}},
  booktitle = {},
  journal = {{S}cientific {D}ata},
  volume = {11},
  numero = {1},
  pages = {332 [12 p.]},
  year = {2024},
  DOI = {10.1038/s41597-024-03159-6},
  URL = {https://www.documentation.ird.fr/hor/fdi:010090578},
}