Search

Your search keyword '"Quan, Xingwen"' showing total 3 results
Start Over Author "Quan, Xingwen" Journal scientific data
3 results on '"Quan, Xingwen"'

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

Author

Yebra, Marta, Scortechini, Gianluca, Adeline, Karine, Aktepe, Nursema, Almoustafa, Turkia, Bar-Massada, Avi, Beget, María, Boer, Matthias, Bradstock, Ross, Brown, Tegan, Castro, Francesc, Chen, Rui, Chuvieco, Emilio, Danson, Mark, Değirmenci, Cihan, 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, Monteiro, Antonio, Morais, Marco, Moreira, Bruno, Mouillot, Florent, Msweli, Samukelisiwe, Nolan, Rachael, Pellizzaro, Grazia, Qi, Yi, Quan, Xingwen, Resco de Dios, Victor, Roberts, Dar, Tavşanoğlu, Çağatay, Taylor, Andy, Taylor, Jackson, Tüfekcioğlu, İrem, Ventura, Andrea, and Younes Cardenas, Nicolas

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.

Published
2024

2. Author Correction: Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications.

Author

Yebra, Marta, Scortechini, Gianluca, Badi, Abdulbaset, Beget, María Eugenia, Boer, Matthias M, Bradstock, Ross, Chuvieco, Emilio, Danson, F Mark, Dennison, Philip, de Dios, Victor Resco, Di Bella, Carlos M, Forsyth, Greg, Frost, Philip, Garcia, Mariano, Hamdi, Abdelaziz, He, Binbin, Jolly, Matt, Kraaij, Tineke, Martín, M Pilar, Mouillot, Florent, Newnham, Glenn, Nolan, Rachael H, Pellizzaro, Grazia, Qi, Yi, Quan, Xingwen, Riaño, David, Roberts, Dar, Sow, Momadou, and Ustin, Susan

Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

3. Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications.

Author

Yebra, Marta, Scortechini, Gianluca, Badi, Abdulbaset, Beget, María Eugenia, Boer, Matthias M, Bradstock, Ross, Chuvieco, Emilio, Danson, F Mark, Dennison, Philip, Resco de Dios, Victor, Di Bella, Carlos M, Forsyth, Greg, Frost, Philip, Garcia, Mariano, Hamdi, Abdelaziz, He, Binbin, Jolly, Matt, Kraaij, Tineke, Martín, M Pilar, Mouillot, Florent, Newnham, Glenn, Nolan, Rachael H, Pellizzaro, Grazia, Qi, Yi, Quan, Xingwen, Riaño, David, Roberts, Dar, Sow, Momadou, and Ustin, Susan

Subjects
Plant Leaves, Water, Algorithms, Forecasting, Databases, Factual, Remote Sensing Technology, Wildfires, Earth, Planet
Abstract

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 Kingdom and the United States of America. The database contains 161,717 individual records based on in situ destructive samples used to measure LFMC, representing the amount of water in plant leaves per unit of dry matter. The primary goal of the database is to calibrate and validate remote sensing algorithms used to predict LFMC. However, this database is also relevant for the calibration and validation of dynamic global vegetation models, eco-physiological models of plant water stress as well as understanding the physiological drivers of spatiotemporal variation in LFMC at local, regional and global scales. Globe-LFMC should be useful for studying LFMC trends in response to environmental change and LFMC influence on wildfire occurrence, wildfire behavior, and overall vegetation health.

Published
2019

Catalog

Books, media, physical & digital resources
See catalog results