scholarly journals Empirical Models for Spatio-Temporal Live Fuel Moisture Content Estimation in Mixed Mediterranean Vegetation Areas Using Sentinel-2 Indices and Meteorological Data

2021 ◽  
Vol 13 (18) ◽  
pp. 3726
Author(s):  
José M. Costa-Saura ◽  
Ángel Balaguer-Beser ◽  
Luis A. Ruiz ◽  
Josep E. Pardo-Pascual ◽  
José L. Soriano-Sancho

Live fuel moisture content (LFMC) is an input factor in fire behavior simulation models highly contributing to fire ignition and propagation. Developing models capable of accurately estimating spatio-temporal changes of LFMC in different forest species is needed for wildfire risk assessment. In this paper, an empirical model based on multivariate linear regression was constructed for the forest cover classified as shrublands in the central part of the Valencian region in the Eastern Mediterranean of Spain in the fire season. A sample of 15 non-monospecific shrubland sites was used to obtain a spatial representation of this type of forest cover in that area. A prediction model was created by combining spectral indices and meteorological variables. This study demonstrates that the Normalized Difference Moisture Index (NDMI) extracted from Sentinel-2 images and meteorological variables (mean surface temperature and mean wind speed) are a promising combination to derive cost-effective LFMC estimation models. The relationships between LFMC and spectral indices for all sites improved after using an additive site-specific index based on satellite information, reaching a R2adj = 0.70, RMSE = 8.13%, and MAE = 6.33% when predicting the average of LFMC weighted by the canopy cover fraction of each species of all shrub species present in each sampling plot.

Author(s):  
Francois Pimont ◽  
Julien Ruffault ◽  
Nicolas Martin ◽  
Jean-Luc Dupuy

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC  data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.


2019 ◽  
Vol 28 (2) ◽  
pp. 127 ◽  
Author(s):  
F. Pimont ◽  
J. Ruffault ◽  
N. K. Martin-StPaul ◽  
J.-L. Dupuy

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behaviour in laboratory experiments. However, field evidence linking LFMC to fire behaviour are very limited, despite numerous field experiments. In this study, we reanalyse a shrubland fire dataset with a special focus on LFMC to investigate this counterintuitive outcome. We found that this controversy might result from three causes. First, the range of experimental LFMC data was too moist to reveal a significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the number of fire experiments was smaller than 40. Finally, an analysis suggested that 10 to 15% measurement error – arising from the estimation of environmental variables from field measurements – could lead to an underestimation by 30% of the LFMC effect. The LFMC effect in field experiments is thus stronger than previously reported in the range of LFMC occurring during the French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behaviour to refine fire-danger predictions.


Author(s):  
Kellen Nelson ◽  
Daniel Tinker

Understanding how live and dead forest fuel moisture content (FMC) varies with seasonal weather and stand structure will improve researchers’ and forest managers’ ability to predict the cumulative effects of weather on fuel drying during the fire season and help identify acute conditions that foster wildfire ignition and high rates of fire spread. No studies have investigated the efficacy of predicting FMC using mechanistic water budget models at daily time scales through the fire season nor have they investigated how FMC may vary across space. This study addresses these gaps by (1) validating a novel mechanistic live FMC model and (2) applying this model with an existing dead FMC model at three forest sites using five climate change scenarios to characterize how FMC changes through time and across space. Sites include post-fire 24-year old forest, mature forest with high canopy cover, and mature forest affected by the mountain pine beetle with moderate canopy cover. Climate scenarios include central tendency, warm/dry, warm/wet, hot/dry, and hot/wet.


2020 ◽  
Vol 245 ◽  
pp. 111797 ◽  
Author(s):  
Krishna Rao ◽  
A. Park Williams ◽  
Jacqueline Fortin Flefil ◽  
Alexandra G. Konings

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 887 ◽  
Author(s):  
Kaiwei Luo ◽  
Xingwen Quan ◽  
Binbin He ◽  
Marta Yebra

Previous studies have shown that Live Fuel Moisture Content (LFMC) is a crucial driver affecting wildfire occurrence worldwide, but the effect of LFMC in driving wildfire occurrence still remains unexplored over the southwest China ecosystem, an area historically vulnerable to wildfires. To this end, we took 10-years of LFMC dynamics retrieved from Moderate Resolution Imaging Spectrometer (MODIS) reflectance product using the physical Radiative Transfer Model (RTM) and the wildfire events extracted from the MODIS Burned Area (BA) product to explore the relations between LFMC and forest/grassland fire occurrence across the subtropical highland zone (Cwa) and humid subtropical zone (Cwb) over southwest China. The statistical results of pre-fire LFMC and cumulative burned area show that distinct pre-fire LFMC critical thresholds were identified for Cwa (151.3%, 123.1%, and 51.4% for forest, and 138.1%, 72.8%, and 13.1% for grassland) and Cwb (115.0% and 54.4% for forest, and 137.5%, 69.0%, and 10.6% for grassland) zones. Below these thresholds, the fire occurrence and the burned area increased significantly. Additionally, a significant decreasing trend on LFMC dynamics was found during the days prior to two large fire events, Qiubei forest fire and Lantern Mountain grassland fire that broke during the 2009/2010 and 2015/2016 fire seasons, respectively. The minimum LFMC values reached prior to the fires (49.8% and 17.3%) were close to the lowest critical LFMC thresholds we reported for forest (51.4%) and grassland (13.1%). Further LFMC trend analysis revealed that the regional median LFMC dynamics for the 2009/2010 and 2015/2016 fire seasons were also significantly lower than the 10-year LFMC of the region. Hence, this study demonstrated that the LFMC dynamics explained wildfire occurrence in these fire-prone regions over southwest China, allowing the possibility to develop a new operational wildfire danger forecasting model over this area by considering the satellite-derived LFMC product.


2013 ◽  
Vol 136 ◽  
pp. 455-468 ◽  
Author(s):  
Marta Yebra ◽  
Philip E. Dennison ◽  
Emilio Chuvieco ◽  
David Riaño ◽  
Philip Zylstra ◽  
...  

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