Browsing by Author "Almoustafa, Turkia"
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Pubmed Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research.(2024-04-04) Yebra, Marta; Scortechini, Gianluca; Adeline, Karine; Aktepe, Nursema; Almoustafa, Turkia; Bar-Massada, Avi; Beget, María Eugenia; Boer, Matthias; Bradstock, Ross; Brown, Tegan; Castro, Francesc Xavier; Chen, Rui; Chuvieco, Emilio; Danson, Mark; Değirmenci, Cihan Ünal; Delgado-Dávila, Ruth; Dennison, Philip; Di Bella, Carlos; Domenech, Oriol; Féret, Jean-Baptiste; Forsyth, Greg; Gabriel, Eva; Gagkas, Zisis; Gharbi, Fatma; Granda, Elena; Griebel, Anne; He, Binbin; Jolly, Matt; Kotzur, Ivan; Kraaij, Tineke; Kristina, Agnes; Kütküt, Pınar; Limousin, Jean-Marc; Martín, M Pilar; Monteiro, Antonio T; Morais, Marco; Moreira, Bruno; Mouillot, Florent; Msweli, Samukelisiwe; Nolan, Rachael H; Pellizzaro, Grazia; Qi, Yi; Quan, Xingwen; Resco de Dios, Victor; Roberts, Dar; Tavşanoğlu, Çağatay; Taylor, Andy F S; Taylor, Jackson; Tüfekcioğlu, İrem; Ventura, Andrea; Younes Cardenas, NicolasGlobe-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.