Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research

Marta Yebra, Gianluca Scortechini, Karine Adeline, Nursema Aktepe, Turkia Almoustafa, Avi Bar-Massada, María Eugenia Beget, Matthias Boer, Ross Bradstock, Tegan Brown, Francesc Xavier Castro, Rui Chen, Emilio Chuvieco, Mark Danson, Cihan Ünal Değirmenci, Ruth Delgado-Dávila, Philip Dennison, Carlos Di Bella, Oriol Domenech, Jean Baptiste FéretGreg Forsyth, Eva Gabriel, Zisis Gagkas, Fatma Gharbi, Elena Granda, Anne Griebel, Binbin He, Matt Jolly, Ivan Kotzur, Tineke Kraaij, Agnes Kristina, Pınar Kütküt, Jean Marc Limousin, M. Pilar Martín, Antonio T. Monteiro, Marco Morais, Bruno Moreira, Florent Mouillot, Samukelisiwe Msweli, Rachael H. Nolan, Grazia Pellizzaro, Yi Qi, Xingwen Quan, Victor Resco de Dios, Dar Roberts, Çağatay Tavşanoğlu, Andy F.S. Taylor, Jackson Taylor, İrem Tüfekcioğlu, Andrea Ventura, Nicolas Younes Cardenas

Research output: Contribution to journalArticlepeer-review

Abstract

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-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. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, 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. Globe-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. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.

Original languageAmerican English
Article number332
JournalScientific data
Volume11
Issue number1
DOIs
StatePublished - 4 Apr 2024

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Education
  • Library and Information Sciences
  • Statistics and Probability
  • Computer Science Applications
  • Statistics, Probability and Uncertainty

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