Now showing items 1-4 of 4

    • Fatalities in wildland fires from 1945 to 2015 in Sardinia (Italy) 

      Cardil Forradellas, Adrián; Delogu, Giuseppe; Molina Terrén, Domingo (Universidade Federal de Lavras (UFLA), 2017)
      The worst outcome of wildland fires is the loss of human lives, a recurrent phenomenon over the last few decades in Sardinia, Europe and worldwide. This work analyzes all recorded fatalities in wildland fires in Sardinia ...
    • Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications 

      Yebra, Marta; Scortechini, Gianluca; Badi, Abdulbaset; Beget, María Eugenia; Boer, Matthias M.; Bradstock, Ross A.; Chuvieco Salinero, Emilio; Danson, F. Mark; Dennison, Philip; Resco de Dios, Víctor; Di Bella, Carlos M.; Forsyth, Greg; Frost, Philip; García, Mariano; Hamdi, Abdelaziz; He, Binbin; Jolly, Matt; Kraaij, Tineke; Martín, M. Pilar; Mouillot, Florent; Newnham, Glenn; Nolan, Rachael H.; Pellizzaro, G.; Qi, Yi; Quan, Xingwen; Riaño, David; Roberts, Dar; Sow, Momadou; Ustin, Susan (Springer Nature, 2019-08-21)
      Globe-LFMC is an extensive global database of live fuel moisture content (LFMC) measured from 1,383 sampling sites in 11 countries: Argentina, Australia, China, France, Italy, Senegal, Spain, South Africa, Tunisia, United ...
    • Physiological drought responses improve predictions of live fuel moisture dynamics in a Mediterranean forest. 

      Nolan, Rachael H.; Hedo, Javier; Arteaga López, Carles; Sugai, Tetsuto; Resco de Dios, Víctor (Elsevier, 2018)
      The moisture content of live fuels is an important determinant of forest flammability. Current approaches for modelling live fuel moisture content typically focus on the use of drought indices. However, these have mixed ...
    • Predicting dead fine fuel moisture at regional scales using vapour pressure deficit from MODIS and gridded weather data 

      Nolan, Rachael H.; Resco de Dios, Víctor; Boer, Matthias M.; Caccamo, Gabriele; Goulden, Michael L.; Bradstock, Ross A. (Elsevier, 2016)
      Spatially explicit predictions of fuel moisture content are crucial for quantifying fire danger indices and as inputs to fire behaviour models. Remotely sensed predictions of fuel moisture have typically focused on live ...