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Títol:
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Modelling temporal variation of fire-occurrence towards the dynamic prediction of human wildfire ignition danger in northeast Spain
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Autor/a:
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Martín, Yago; Zúñiga Antón, María; Rodrigues Mimbrero, Marcos
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Notes:
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Models of human-caused ignition probability are typically developed
from static or structural points of view. This research analyzes the
intra-annual dimension of fire occurrence and fire-triggering factors
in NE Spain and moves forward towards more accurate predictions.
Applying the Maximum Entropy algorithm (MaxEnt) and using wildfire
data (2008–2011) and GIS and remote sensing data for the
explanatory variables, we construct eight occurrence data scenarios
by splitting wildfire records into the four seasons and then separating
each season into working and non-working days. We assess model
accuracy using a cross-validation k-fold procedure and an operational
validation with 2012 data. Results report a substantial contribution of
accessibility across models, often coupled with Land Surface
Temperature. In addition, we observe great temporal variability, with
WAI strongly influencing winter models, whereas distance to roads
stands out during working days. Model performances stand consistently
above 0.8 AUC in all temporal scenarios, with outstanding predictive
effectiveness during summer months. The comparison among
static-to-dynamic approaches reveals superior performance of simulations
considering temporal scenarios, with AUC values from 0.7 to
0.85. Overall, we believe our approach is reliable enough to derive
dynamic predictions of human-caused fire occurrence.
This research was funded jointly from a predoctoral Fulbright-Iberdrola grant, a ‘Juan de la Cierva’ postdoctoral fellowship grant (FJCI-2016-31090) at the Univesity of Lleida, and the research group GEOT, from the University of Zaragoza. |
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Matèries:
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-Wildfire
-Ignition danger
-Human drivers
-Temporal dimension |
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Drets:
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cc-by, (c) Martín et al., 2018
http://creativecommons.org/licenses/by/4.0/
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Tipus de document:
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Article
Article - Versió publicada |
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Publicat per:
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Taylor & Francis
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Compartir:
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